Doc 5.3, ver. 1.0 | March 21, 2017

ALMA Cycle 5 Technical Handbook

ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC(Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile.
The Joint ALMA Observatory is operated by ESO, AUI/NRAO and NAOJ.

2User Support
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Revision History
Cycle

Version Date

Editors

Remarks

1

1.0

2013-10-01

2

1.1

2013-10-15

3
4
4
5

1.0
1.0
1.1
1.1

2015-03-20
2016-03-22
2016-09-07
2017-03-21

A. Hales, A. Lundgren, A. Biggs,
J. Di Francesco, B. Vila Vilaro,
S. Leon, D. Barkats, E. Fomalont,
S. Asayama, S. Komugi
A. Lundgren, S. Leon, J. Hibbard,
E. Müller, J. Di Francesco
A. Remijan, M. Adams, R. Warmels
J. Mangum and R. Warmels
J. Mangum and R. Warmels
R. Warmels and A. Remijan

Cycle 3
Cycle 4
Replace figs 7.9 and 7.10
Cycle 5

Editors
Rein Warmels and Tony Remijan

Authors of this Edition
Itziar de Gregorio - Chapter 1; Antonio Hales - Chapter 2 and Appendix A; James Di Francesco - Chapter 3;
Gianni Marconi and Bill Dent - Chapter 4; Seiji Kameno - Chapter 5; Bill Dent - Chapter 6; Eric Villard - Chapter
7; Baltasar Vila Vilaro - Chapters 8 ,11 and 12; Andy Biggs - Chapter 9; Ed Fomalont - Chapter 10; John
Hibbard - Chapter 13; Felix Stoehr - Chapter 14; Shin’ichiro Asayama - Appendix B

Contributors to this Edition
Eiji Akiyama, Rodrigo Amestica, Yiping Ao, Yanett Contreras, Todd Hunter, Woojin Kwon, Mark Lacy, Harvey Liszt, Jeff Mangum, Brian Mason, Ralph Marson, Rie Miura, Arielle Moullet, Jennifer Donovan Meyer,
Hiroshi Nagai, Kouichiro Nakanishi, Se-Heon Oh, Rosita Paladino, Anita Richards, Rachel Rosen, Kazy Rygi,
Kamaljeet Saini, Richard Simon, Gie-Han Tan, Ken Tatematsu, Carmen Toribio, Lance Utley, Catherine Vlahakis, Al Wootten, Kijeong Yim, Llsang Yoon
In publications, please refer to this document as:
ALMA Partnership, 2017, S. Asayama, A. Biggs, I. de Gregorio, B. Dent, J. Di Francesco, E. Fomalont,
A. Hales, J. Hibbard, G. Marconi, S. Kameno, B. Vila Vilaro, E. Villard, F. StoehrISBN 978-3-923524-66-2

Contents
1 Introduction

9

2 Array Components
2.1 The ALMA Telescope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 The 12-m Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 The Atacama Compact Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3.1 The 7-m Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3.2 The TP Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

11
11
12
13
13
14

3 Principles and Concepts of Interferometry
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Single-dish Response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Visibilities and Aperture Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 The Visibility or uv-Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5 Fields-of-view and Mosaics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.6 Spatial Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.7 Multi-configuration Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.8 Units and Conversions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15
15
16
19
22
23
24
26
28

4 Receivers
4.1 Local Oscillators and IF Ranges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 The Cycle 5 Receivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.1 Band 3 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.2 Band 4 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.3 Band 5 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.4 Band 6 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.5 Band 7 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.6 Band 8 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.7 Band 9 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.8 Band 10 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

31
33
33
35
38
41
43
46
49
52
55

5 The Correlators
5.1 The 64-input Correlator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.1.1 TDM mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.1.2 FDM mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.1.3 Correlation and Realtime Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 The ACA Correlator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1 The 7-m Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.2 The Total Power Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.3 Digitizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4 Online WVR Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5 Capabilities of the Correlators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5.1 Polarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59
60
60
61
62
62
64
64
64
66
66
66

3

4

CONTENTS

5.5.2 Spectral Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5.3 Time Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5.4 Phase Switching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Practical Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.1 Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.2 Linearity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Final data product - the ASDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66
69
70
72
72
72
72

6 Spectral Setups
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2 Frequency Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3 Spectral Setups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1 Observing Frequencies for Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.2 Multiple Spectral Windows in the Same Baseband . . . . . . . . . . . . . . . . . . . . . .
6.3.3 Spectral Setups for Lines near the Edge of the Bands . . . . . . . . . . . . . . . . . . . .
6.3.4 Spectral Setup in Bands 9 and 10: DSB Considerations and 90-degree Phase Switching .
6.4 Usable Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.5 Spectral Resolution and Channel-averaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.6 Spurious Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.7 Doppler Setting and Velocity Reference Frames . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.8 Limitations and Rules for Spectral Setups in Cycle 5 . . . . . . . . . . . . . . . . . . . . . . . . .

75
75
77
77
78
80
81
81
82
82
83
83
84

5.6
5.7

7 Imaging with ALMA87
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
7.2 Cycle 5 Configurations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
7.3 Shadowing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
7.4 Resolution and Beam Shape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
7.5 Response and Snapshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
7.6 Spatial Scale Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
7.7 Mosaicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
7.8 Multi-array and Multi-configuration Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
7.9 Multi-array and Multi-configuration Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
8 Observing Modes
109
8.1 Observing Project Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
8.2 Program Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
8.3 The Observing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
8.3.1 The Source Selection Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
8.4 Single Field Interferometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
8.5 Pointed Mosaic Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
8.6 Single Dish (Total Power) Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
8.7 Polarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
8.7.1 Sessions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
8.8 Multiple Region Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
8.9 Observation of Ephemeris Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
8.10 Solar Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
8.10.1 Solar Observing Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
8.10.2 Array Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
8.10.3 Single Dish Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
8.11 VLBI Observing Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
8.11.1 General VLBI Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
8.11.2 ALMA Considerations for VLBI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
8.12 High Frequency Observing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

CONTENTS

59 ALMA Sensitivity Calculator
131
9.1 Calculating the System Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
9.1.1 Sky Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
9.1.2 CMB Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
9.1.3 Receiver Temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
9.1.4 Ambient Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
9.1.5 DSB Receivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
9.1.6 System Temperature (OT version) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
9.1.7 System Temperature (Stand-alone ASC and GUI (OT) version) . . . . . . . . . . . . . . . 136
9.2 The Sensitivity Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
9.2.1 12-m and 7-m Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
9.2.2 Total Power Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
9.3 User Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
9.4 Total Time Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
10 Calibration and Calibration Strategies
141
10.1 The True and Observed Visibility Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
10.1.1 The Data Format and the Correlator Model . . . . . . . . . . . . . . . . . . . . . . . . . . 141
10.1.2 The Visibility Function Dependence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
10.2 Main Interferometric Calibration Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
10.2.1 Phase Referencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
10.2.2 Antenna-based Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
10.2.3 Major Calibrations Affecting Interferometric Data . . . . . . . . . . . . . . . . . . . . . . 143
10.2.4 The Organization of the Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
10.3 ALMA-Supplied a-priori Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
10.3.1 Antenna Beam/Surface Characteristics (P) . . . . . . . . . . . . . . . . . . . . . . . . . . 144
10.3.2 Antenna Pointing Models (P) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
10.3.3 Focus Models (P) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
10.3.4 Antenna Delay Offsets (D) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
10.3.5 Antenna Positions (M) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
10.4 On-Line Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
10.4.1 Water Vapor Radiometer Measurements (M) . . . . . . . . . . . . . . . . . . . . . . . . . 147
10.4.2 System and Receiver Temperature(T) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
10.4.3 Additional Antenna Pointing Checks (P) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
10.5 Off-Line Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
10.5.1 On-Line Flagging (F) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
10.5.2 Calibration-based Flagging (F) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
10.5.3 Bandpass Calibration (B) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
10.5.4 Gain Calibration (G) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
10.5.5 Flux Density Calibration (T) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
10.5.6 Polarization Calibration (p,X) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
10.6 Additional Calibration Concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
10.6.1 Observations at Frequencies > 400 GHz . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
10.6.2 Observations with Baselines > 3 km . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
10.6.3 Phase Calibration with Narrow Bandwidths . . . . . . . . . . . . . . . . . . . . . . . . . . 153
10.6.4 Band-to-Band Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
10.6.5 Check Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
10.6.6 Astrometric Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
10.6.7 Self-Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
10.6.8 Total-Power Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
10.6.9 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

6

CONTENTS

11 Quality Assurance
157
11.1 Cycle 5 Quality Assurance Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
11.2 QA0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
11.3 QA1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
11.4 QA2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
11.5 QA3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
11.6 The Quality Assurance Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
11.7 QA Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
12 Data Flow and Logical Data Structure163
12.1 Data and Control Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
12.2 The ALMA Science Data Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
13 Pipeline Processing
169
13.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.2 Pipeline In ALMA Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.2.1 Standard and Non-standard Observing Modes . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.2.2 Pipeline Triggering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
13.2.3 Pipeline Runs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
13.3 Details on Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
13.3.1 Pipeline Runtime Database Queries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
13.3.2 Observatory “Fixes” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
13.3.3 Flagging Heuristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
13.3.4 Treatment of Multiple Execution Observations . . . . . . . . . . . . . . . . . . . . . . . . 175
13.3.5 Low SNR Heuristics in Interferometric Pipeline Processing . . . . . . . . . . . . . . . . . 175
13.3.6 Total Power Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
13.3.7 Imaging – interferometric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
13.4 Pipeline and the ALMA Quality Assurance Process . . . . . . . . . . . . . . . . . . . . . . . . . . 176
13.5 Output of the Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
14 Data Archiving
179
14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
14.2 Data Flow and Archive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
14.3 PI Data and Data Delegation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
14.4 Archive Query . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
14.5 Request Handler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
A Antennas
185
A.1 Design and Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
A.2 Antenna Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
A.3 Antenna Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
A.4 Cryostat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
A.5 Amplitude Calibration Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
A.5.1 Atmospheric Calibration Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
A.6 Water Vapor Radiometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
B The LO and IF System
197
B.1 Functions of the LO and IF System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
B.2 Summary of Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
B.3 Frequency Generation and Distribution in ALMA . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
B.3.1 Reference and LO Signal Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
B.3.2 LO1 Signal Generation and Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
B.3.3 Line Length Corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
B.3.4 The First Local Oscillator (LO1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
B.3.5 LO2 and the IF Processor Units and IF Switch . . . . . . . . . . . . . . . . . . . . . . . . 204

CONTENTS

7

B.3.6 Digitization and Signal Transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
B.4 Other functions of the LO/IF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
B.4.1 Delay Corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
B.4.2 Sideband Suppression - LO Offsetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
B.4.3 Interference Rejection - 180 degree Phase Switching . . . . . . . . . . . . . . . . . . . . . 207
B.4.4 Sideband Separation - 90 degree Walsh Switching . . . . . . . . . . . . . . . . . . . . . . . 207
C Acronym Dictionary

209

8

CONTENTSThis page was intentionally left almost blankChapter 1

Introduction
The Atacama Large Millimeter/Submillimeter Array (ALMA) is an aperture synthesis telescope consisting of 66
antennas arranged in a series of different configurations. It operates over a broad range of observing frequencies
in the millimeter and submillimeter regime. ALMA Early Science Operations started with Cycle 0 in September
2011 and the official inauguration took place in March 2013.
Cycle 5 operations will include standard and non-standard observing modes. Non-standard modes areobserving modes for which the data cannot be processed by the pipeline and need to be reduced manually by
ALMA staff. Up to 20% of the PI observing time in Cycle 5 will be allocated to proposals requesting nonstandard modes. Users should refer to Appendix A (ALMA Capabilities) in the ALMA Cycle 5 Proposer’s
Guide, for the latest information and a description of standard and non-standard modes.
The Technical Handbook provides additional information on technical aspects and their limitations of the
Cycle 5 setup for ALMA users. It should, however, not be necessary to use the Technical Handbook to prepare
an ALMA proposal.
The handbook is divided into three main sections: The concepts of interferometry and the ALMA hardware
components (Chapters 2–5), the observing concepts and software (Chapters 6–9), and finally the data quality
and handling (Chapters 10–14). It also includes a number of appendices with expanded information on specific
ALMA hardware components and calibration, and an acronym list.
Chapter 2 describes the ALMA Array components: The 12-m Array and the Atacama Compact Array(ACA), also known as the Morita Array which is comprised of the 7-m and Total Power (TP) Arrays. A generaldescription on the different array elements and their components is provided.
Chapter 3 gives a brief introduction to interferometry, including a description on the concepts of basic radio
astronomy and the principles of aperture synthesis.
Chapter 4 describes the details of the seven receivers offered in Cycle 5. The general technical specifications
and a brief explanation on local oscillators and IF range is presented. Plots with the atmospheric transmission
and the typical system temperatures per receiver are also included.
Chapter 5 describes the correlators and the data processing taking place in these special purpose supercomputers. A description of the 64-input Correlator (used for the 12-m Array) and the ACA Correlator (used by
the 7-m and the TP Arrays) is provided. Modes for continuum and spectral line observations are presented.
Chapter 6 describes how the spectral setup is done in the correlators. It covers a description of the signal
path and local oscillator chain used between the frontends and the correlators, and how these are used to define
spectral setups for the user.
Chapter 7 describes several aspects of imaging to consider in ALMA observations. A short description on
the different configurations proposed for Cycle 5 is included. Concepts of shadowing, beam shape, and spatial
scale filtering are revisited. Mosaicing, and 12-m and 7-m Array data combination are also presented.

910

CHAPTER 1. INTRODUCTION

Chapter 8 describes the observing modes offered for Cycle 5 and how projects are observed. Single field interferometry, mosaics, single-dish observations, polarization, multiple region modes, solar, VLBI, and ephemeris
observations are detailed in this section.
Chapter 9 gives a brief overview how sensitivities and integration times are calculated at ALMA.
Chapter 10 describes how calibration is performed at ALMA, providing a description on how to calibrate
long-term and short-term effects as well as how calibrators are selected.
Chapter 11 describes the data quality assurance process. It also provides the criteria used for passing thequality assurance.
Chapter 12 describes the structure of the data.
Chapter 13 includes a description on the ALMA pipeline, its infrastructure, the pipeline heuristics and theuse of the pipeline in data calibration.
Chapter 14 describes how the data are stored, the data flow and the ALMA Archive.
The Technical Handbook concludes with two appendices, which contain supplemental material about theantenna design and transportation transporter (Appendix A), and the Local Oscillator (LO) and Intermediate
Frequency (IF) system (Appendix B).

Figure 1.1: ALMA antennas on the Chajnantor Plateau.
Credit: ALMA (ESO/NAOJ/NRAO), O. Dessibourg

Chapter 2

Array Components
This chapter describes the main characteristics of each ALMA array. Unless otherwise noted, the description isappropriate for the fully completed ALMA telescope

2.1

The ALMA Telescope

ALMA is composed of 66 high-precision antennas. Fifty of these antennas are 12 meter dishes in the 12-m
Array, used for sensitive, high-resolution imaging. These fifty 12 m antennas are complemented by the Atacama
Compact Array (ACA), also known as the Morita Array1 , composed of twelve closely spaced 7 m antennas (the7-m Array), and four 12 m antennas for single-dish (or Total Power) observations (the TP Array), to enhancewide-field imaging of extended structures. In Cycle 5, ALMA will cover most of the wavelength range from 3.6
to 0.32 mm frequency), and when ALMA is completed the coverage will be from 10 to 0.32 mm (31-950 GHz).
The array is located on the Chajnantor plain of the Chilean Andes (lat.=–23.02917 deg., long.=–67.754649
deg.), a site that normally offers the exceptionally dry and clear sky conditions required to observe at millimeterand sub-millimeter wavelengths2 . The ALMA antennas, weather stations, the two correlators and their computer interfaces, Local Oscillator generation hardware, timekeeping hardware, and the related array Real-Time
Machine computer are all located at the 5000-meter altitude site referred to as the Array Operations Site (AOS).
This site is connected via Gigabit fiber links to the Operation Support Facility (OSF), located at an altitude of2900 meters, about 22 km from the AOS and 40 km from the town of San Pedro de Atacama. Science operations
are conducted from the OSF and coordinated from the JAO Central office in Santiago. All three ALMA arrays
are controlled via control software developed on the ALMA Common Software3 (ACS).
There are 192 antenna foundations (stations) distributed over the Chajnantor and Pampa la Bola plateaus.
The antenna foundation distribution yields baselines (distances between two antennas) ranging from 15 m to
∼16 km, which are crucial in determining the image quality and spatial resolution of ALMA (see Chapter 7).
The antenna foundations provide the stiffness required for precise antenna pointing, as well as electrical powerand digital connectivity to the main AOS building (See Appendix A.2). The antennas can be re-configured into
the different array configurations (Chapter 7) using the two special purpose ALMA antenna transporters (seeAppendix A.3).
The number of antennas in each array component (12-m, 7-m and TP Arrays), and the specific configurations available for an observing season (e.g. Cycle 5) will be published in the Capabilities section of the
document ALMA Proposer’s Guide. Complementary background information on ALMA and its capabilities
for Cycle 5 can be found in the document A Primer for Cycle 5. Both documents can be found on the link
http://www.almascience.org/documents-and-tools/.
1 dedicated to the honour of K.-I. Morita
2 http://www.almascience.org/about-alma/weather
3 http://www.eso.org/projects/alma/develop/acs/

11

12

CHAPTER 2. ARRAY COMPONENTS

Figure 2.1: The ALMA 12-m Array in its compact configuration (left hand side of the image). The ACA withall 7 m antennas (dashed orange circles) and four single-dish 12 m antennas (blue circles) are distributed in theright hand side of the image. A few unoccupied stations can be seen, to which antennas of the 12-m Array canbe moved by the transporter as the array is being reconfigured. At its most extended configuration, antennas
in the 12-m Array will be about 16 km apart.

2.2

The 12-m Array

The 12-m Array consists of fifty 12 m diameter antennas designed and built by the European and North
American ALMA partners (each providing 25 units), according to the stringent ALMA Antenna Performance
specifications (see Appendix A). Each antenna contains one front end, including a cryostat (see Appendix A.4),
amplitude calibration device (ACD; A.5), water vapor radiometer (WVR; A.6), and back-end electronics (analog
and digital racks). The WVRs are used to correct the phase fluctuations caused by water in the atmospherealong the line of sight of each 12-m Array element. The cryostat can contain up to ten cartridges, each covering
one frequency band (see Chapter 4). Only one band observes at any time, but up to three can be switchedon simultaneously, and rapid switching between them is possible. Each band receiver (Chapter 4) detects two
orthogonal linear polarizations and down-converts the signals to an intermediate frequency with eight GHz of
bandwidth per polarization. Bands 3-8 cartridges are dual sideband (2SB) and Bands 9 and 10 are double
sideband (DSB).
The Local Oscillator (LO) signals (Appendix B) are transmitted to the antennas on optical fibers with around trip measurement to correct for changes in the fiber length. There are four independent LO reference
systems so that the 7-m Array, the TP array and two subsections of the 12-m Array (e.g., two ‘sub-arrays’) canconduct simultaneous independent observations. Please note that the sub-arrays feature of the 12-m Array is
not yet a capability that is offered. The 8 GHz total IF bandwidth from the selected receiver is divided into four
2 GHz-wide basebands which are digitized at four Gsamples/s, with three-bit resolution, and transmitted on
optical fibres. Total data rates are therefore 96 Gbits/s per antenna. With formatting, the bit rate is 120 Gbits/s.
On arrival at the central building, the data are recovered and processed in one of the two correlators: the64-input Correlator and the ACA Correlator (see Chapter 5). All antennas can feed either correlator. The
64-input Correlator (Section 5.1) is normally used for the 12-m Array, but it can also take inputs from the
7-m Array or TP antennas. It is an XF correlator (cross-correlates first, then Fourier transforms), but thecorrelator proper is preceded by Tunable Filter Banks, which makes it a digital hybrid XF correlator or FXF.
These can select sub-bands from the 2 GHz-wide basebands in a very flexible manner. From each of these,
the correlator then generates 2016 cross-correlations and 64 auto-correlations (requiring 1.7×1016 operations
per second). Either 2-, 3- or 4-bit resolution is used, and the sampling can be Nyquist or twice Nyquist. See
Table 6.1 for an example table of spectral setups. These correlated data are fed to a group of processors which2.3. THE ATACAMA COMPACT ARRAY

13

do the transforms and carry out integration and data compression.
Both correlators have minimum dump rates of 16 ms for cross-correlation and 1 ms for auto-correlation,although these dump rates can only be achieved using a reduced number of channels to prevent exceeding the
maximum transmission and storage rates. The systems are designed for a maximum data rate of 64 MB/s,
although the mean data rate will be considerably less.
The 12-m Array configurations have been designed so that in the most extended configurations the spatial
angular resolution will be as small as 5 milliarcseconds at 950 GHz.

2.3

The Atacama Compact Array

Using an interferometer to obtain images of extended or large-scale structures leads to the well known “zerospacing” problem. This problem arises from the constraint that, to avoid collisions, it is not possible to packantennas closer than their diameter, leaving a hole in the distribution of baselines at short and zero baseline
separations (corresponding to large angular structure). As a result, spatial information from baselines shorter
than the closed-packing ratio is not recovered4 . This problem has considerable impact on observations ofextended objects, particularly those in which the emitted power is dominated by their large-scale structures.
To achieve high-fidelity imaging of sources with emission on angular scales larger than those corresponding
to the minimum spacing of the 12-m Array (the “Maximum Recoverable Scale" for that array - see Section 7.6),
ALMA has been designed to include the Atacama Compact Array (ACA), also known as the Morita Array.
The ACA is composed of twelve 7 m antennas for interferometry (the 7-m Array) and four 12 m antennas
for single-dish observations (TP Array). The four single-dish antennas provide spatial information samples
equivalent from 0 m up to 12 m spacings as auto-correlations. The 7-m Array samples baselines from 9 m to
30 m, bridging the baseline sampling gap between the 12-m Array and the TP Array. The number of arrayelements available is published for each observing cycle.
The ACA is controlled via control software developed on the ALMA Common Software (ACS) platform andis operated in a similar fashion to the 12-m Array. To achieve this unified operation, the ACA system is ascompatible with the 12-m Array as possible at the level of hardware, interface, data, and observing modes. The
standard observing modes for the TP Array include spectral line and continuum observations with raster or
Lissajous on-the-fly (OTF) scans, or position switching. The raw time-series signals from the ACA antennas
are processed in the ACA Correlator (see Section 5.2) to produce the cross-correlated and auto-correlated data.

2.3.1

The 7-m Array

The 7-m Array is composed of twelve 7 m diameter antennas designed and built by East Asia to the ALMA
specifications (see Appendix A). Similar to 12-m Array antennas, each antenna contains one front end, including
a cryostat, amplitude calibration devices, and one back end. Unlike the antennas of the 12-m Array, the 7 mantennas do not contain Water Vapor Radiometers (WVRs). The 7 m antenna cryostats are fitted with receivers
nearly identical to those on the 12 m antennas, with small differences in the warm optics. The Local Oscillator
signals transmitted to the 7 m antennas are originated identically to the ones sent to the 12-m Array, i.e., frominside the AOS building.
The ACA Correlator is normally used for the ACA, and can work with two sub-arrays. It is an FX correlator(Fourier transform first, then cross-correlate) with 3−bit input and 4 bits in the correlation. The correlator
generates 120 cross-correlations and 16 auto-correlations for each baseband. These are passed to a (specialpurpose) data processing computer at up to ∼0.6 Gbits/s per baseband.
No baseline coverage from even the most compact configuration of the 12-m Array is obtained for spacings
smaller than 15 m. The array configuration of the 7-m Array is designed to fill in missing spacings from about
9 m to ∼30 m (see Chapter 7). Each cartridge (see Chapter 4) receives two orthogonal polarizations.
4 Strictly speaking, mosaicing with imaging using a joint-deconvolution algorithm allows the recovery of more spatial information
than normal synthesis imaging, but the problem caused by absent short and zero spacing information still remains.

14

2.3.2

CHAPTER 2. ARRAY COMPONENTS

The TP Array

The TP Array can fill in baseline coverage from 0 m to about 12 m, complementing the 7-m and 12-m Array’s
baseline coverage. It consists of four 12 m diameter antennas built by East Asia (A). The specifications of the
TP antennas are almost identical to the ones for the 12-m Array. The TP antennas are located on stations
surrounding the 7-m Array.
The TP Array is usually connected to the ACA Correlator, but its antennas can also be connected to the
64-input Correlator and used for cross-correlation. The ALMA Proposer’s Guide describes the observing modes
and capabilities offered for the TP Array for each cycle.
Due to the poorer point-source sensitivity of the 7-m Array, during Full Operations, the TP Array will beroutinely used in the calibration observations of the 7-m Array, but this is not yet implemented. Since the 7-m
Array is quite compact, atmospheric phase fluctuations will be smaller than for the 12-m Array.

Figure 2.2: The Morita Array - In remembrance of Professor Koh-Ichiro Morita. Koh-ichiro Morita, a professor
at the NAOJ Chile Observatory, was one of the world’s renowned scientists in the field of aperture synthesis.
He made a great contribution to designing the configuration of 16 antennas composing the Atacama Compact Array (ACA) manufactured by Japan, as well as to realizing high-resolution and high-quality imaging at
millimeter/submillimeter wavelengths to further enhance the performance of ALMA. The picture above shows
Professor Koh-Ichiro Morita taken at his office in the Joint ALMA Observatory.

Chapter 3

Principles and Concepts of Interferometry
3.1

Introduction

Interferometry is the technique ALMA uses to obtain very high angular resolution observations of astronomical phenomena. In this Chapter, the principles and concepts behind interferometry are described, so that
ALMA users can plan and understand their observations better. If more information is desired, the topic ofinterferometry is covered in more detail in the following seminal texts:• Interferometry and Aperture Synthesis in Radio Astronomy - Second Edition, by Thompson, A. R., Moran,
J. M., & Swenson, G. W. (Wiley-VCH)• Tools of Radio Astronomy - Fifth Edition, by Wilson, T. L., Rohlfs, K., & Hüttemeister, S. (Springer)• Synthesis Imaging in Radio Astronomy II, PASP Conference Series, Vol. 180, eds. G. B. Taylor, C. L.
Carilli, & R. A. Perley (San Francisco - ASP)
• Millimeter Interferometry: Proceedings of the IRAM Millimeter Interferometry School, ed. A. Dutrey,
available online at http://iram.fr/IRAMFR/IS/IS2002/archive.html.
The Chapter first provides a very basic picture of the core concepts behind how interferometry works.
Interferometry involves the combination of signals received from the sky by two or more physically separated
antennas. The signals are interfered, allowing a sky brightness distribution to be sampled on an angular scale
smaller than possible with a single antenna. The interference modifies the angular sensitivity of the antennas
to include a sinusoid of constructive and destructive nodes. In this sense, the only emission measured by theinterferometer is that from the scale defined by the angular extent of the sinusoidal wavelength, equivalently,
the ”spatial frequency”. This wavelength is inversely proportional to the projected distance between the twoantennas. Each datum, called a visibility, consists of the brightness of the emission on the angular scale sampled,i.e., related to the amplitude of the sinusoid, and the relative position of that brightness on the sky, i.e., related
to the phase of the sinusoid.
A range of discrete angular scales can be sampled by including many pairs of antennas in an array. Importantly, by tracking a source across the sky, the rotation of the Earth can be used to change the projected
separations of the antenna pairs, allowing more angular scales to be sampled. An ensemble of the data, i.e.,
sinusoids of various amplitude and phase, can be then ”summed” via the Fourier transform to produce an imageof the sky brightness distribution. How well this image reflects the actual sky brightness distribution depends on
how completely the relevant angular scales have been sampled. Interferometry, however, works extraordinarily
well for observing intrinsically compact targets.
The following expands upon these basic ideas. It begins by introducing the basic concepts of radio astronomy,
and then moves to the principles of aperture synthesis.

15

16

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

Figure 3.1: The Plateau de Bure Interferometer (top) and the Submillimeter Array (SMA) (bottom) are theprecursors to the ALMA telescope; both are still in full operation and pioneered the science of millimeter wave
interferometry.

3.2

Single-dish Response

As in all astronomy, brightness, or equivalently specific intensity, Iν , is defined as the electromagnetic (EM)power δP within a range of frequencies (a bandwidth) δν received from a solid angle δΩ and intercepted bysurface area δA, i.e.,δP = Iν δΩδAδν,(3.1)

where Iν has typical units of W m−2 Hz−1 sr−1 . In addition, the flux density, Sν , is defined as the integrationof brightness over the solid angle of the emitting source, i.e.,ZSν =Iν dΩ,(3.2)

where Sν has typical units of W m−2 Hz−1 . In millimeter/radio astronomy, the power received is typicallyso weak that a convenient unit to use for Sν is the Jansky (Jy), where 1 Jy = 10−26 W m−2 Hz−1 . A radio
telescope with effective area Ae receives power Prec per unit frequency from an unpolarized source, i.e.,
Prec =1Iν Ae δΩ.
2

(3.3)

The coefficient of 1/2 in Equation 3.3 comes from the fact that a receiver is generally sensitive to only one
mode of polarization. (Note that ALMA receivers are constructed with two independent receptors so that bothmodes of polarization can be detected simultaneously.) The antennas bring incident electromagnetic (EM) power
to a focus after reflecting it off a primary surface. The antenna response, i.e., its sensitivity, is a summation of
all EM power brought to the focus.
Antenna response is actually dependent on angle from the on-axis pointing direction of the antenna, due todiffraction. To demonstrate the angular dependence, Figure 3.2 shows in the top panel the case for EM powerof wavelength λ arriving along the axis of an unobstructed antenna of diameter D. Since the source of the17

3.2. SINGLE-DISH RESPONSE

Figure 3.2: Schematic of an incoming plane-parallel wavefront reflecting off a antenna of diameter D and beingbrought to a focus. The top panel shows the case for a wavefront arriving on-axis. The bottom panel shows
the case for a wavefront arriving off-axis. Note that the paths of incident EM power in the first case are all of
equal length, and hence the power is summed constructively at the focus. In the second case, the path lengths
differ, leading to less constructive summations at the focus.
EM power is very distant, the EM power arrives at the primary surface essentially as plane-parallel wavefronts.
Note that the antenna surface is parabolic in shape, so the path that each part of the front travels to the focus
is constant. With zero path difference, the EM power arriving on-axis is coherently summed at the focus. This
arrangement is only true, however, along the axis of the antenna. In the lower panel of Figure 3.2, the casefor EM power arriving from an off-axis direction is shown. In this situation, the EM power does not add asconstructively. In addition, the diameter of the antenna projected along the off-axis direction is less than thetrue diameter, decreasing the amount of power received from that direction. As a result, the antenna power
response, i.e., its relative sensitivity, will be less than that found on-axis. In particular, at the off-axis angle of
λ/D radians, the path difference across the antenna diameter, the aperture, will equal one wavelength of theincident emission. The combination of such emission at the focus leads to destructive interference at that angle.
As an illustration, Figure 3.3 shows an example of a one-dimensional antenna power response with angle fora 12 m diameter parabolic antenna uniformly illuminated by emission of wavelength ≈ 0.85 mm (350 GHz). The
power response is largest on-axis but it declines to zero in ∼18 arcseconds. The central Gaussian-like feature iscalled the primary beam or the antenna beam size and it has a Half Power Beam Width (HPBW) given by:
HPBW Primary Beam = 1.02 × λ/D,

(3.4)

18

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

where λ is the wavelength of observation and D is the diameter of the antenna. For example, the HPBW of a
uniformly illuminated antenna of 12 m diameter at λ = 0.85 mm is 14.9500 . HPBW is sometimes referred to as
Full Width at Half Power or FWHP.
Note that the antenna power response rises and declines repeatedly at ever larger angles. The constructive
and destructive interference at larger angles leads to successive sidelobes (whose maxima decline with increasing
angle) and nulls respectively. The first sidelobes have a relative response of only 1.74% that of the primarybeam. Nevertheless, incident emission, if bright enough, coming in at angles well beyond those of the primarybeam can make a large contribution to the received EM power. The angular distance between nulls is termed
the Full Width Between Nulls (FWBN), and is given by:
FWBN Primary Beam = 2.44 × λ/D.

(3.5)

Half the FWBN of the primary beam, ∼1.22 λ/D, is considered the Rayleigh resolution of the antenna, i.e.,
its ability to distinguish objects on the sky separated by some angular distance. For convenience, the antenna
power response is typically normalized to 1.0 along the axis. Figure 3.3 illustrates the antenna power response in
one dimension (in log units); on the actual sky, the antenna power response is two-dimensional, and is obtainedby rotating the function shown in Figure 3.3 about its central axis.

Figure 3.3: Normalized 1-D antenna power response for a 12 m antenna uniformly illuminated at 300 GHz.
The power is in log units to emphasize the sidelobes. The HPBW of the primary beam is ∼1.02 λ/D and the
FWBN is ∼2.44 λ/D. The angle of the first null, i.e., the resolution, is 0.5×BWFN = ∼1.22 λ/D. Note thatthe HPBW measured from actual 12 m ALMA antennas is ∼1.13 λ/D because the illumination is not uniform.
Up until now, an idealized antenna was described. Actual antenna power response can be altered by various

19

3.3. VISIBILITIES AND APERTURE SYNTHESIS

effects, including the degree by which the secondary is illuminated, diffraction by the arms supporting thesecondary, and surface imperfections. For ALMA, each 12 m antenna has a secondary reflector and support
arms that block an effective area of 0.75 m diameter on the primary surface. The actual ALMA feedhorns
were designed to provide an antenna power response with a nearly Gaussian primary beam and low sidelobes,
preserving as much resolution and sensitivity as possible. The actual ALMA 12 m antennas have measured
primary beam HPBW values of ∼1.13 λ/D.
An equivalent way to consider the antenna power response is in terms of the voltage response, V (θ), whereP (θ) ∝ V 2 (θ). In the far-field, i.e., under the Fraunhofer approximation, a diffraction pattern at the pointof observation is the Fourier transform of the field distribution at an aperture. Hence, the voltage responseat the focus is the Fourier transform of the aperture shape. For an unobstructed antenna, the aperture is a
uniform circle, and V (θ) = J1 (θ)/θ, where J1 (θ) is the Bessel function of the first kind. P (θ), is correspondingly
proportional to (J1 (θ)/θ)2 . The normalized version of the antenna power response, PN , is also known as the
Airy function. Observing at millimeter/radio wavelengths is essentially diffraction-limited.
Defining θ and ϕ as orthogonal directional variables (e.g., sky coordinates), Iν (θ, ϕ) and PN (θ, ϕ) can be
defined as the directional functions of the sky brightness and the normalized antenna power, respectively. The
total received power of an antenna at a given pointing is the integration over the sky of the product of the skybrightness distribution and the antenna power response:
Prec =

1
Ae
2

ZIν (θ, ϕ)PN (θ, ϕ)δΩ.

(3.6)

4π

In addition, the solid angle of the antenna power response PN (θ, ϕ) can be found as:ZΩA =PN (θ, ϕ)δΩ.

(3.7)

4π

3.3

Visibilities and Aperture Synthesis

For millimeter/radio astronomy, the angular resolution of a single-dish observation is very low compared to thosefound at optical wavelengths since λ is larger by many orders of magnitude. Though the D of millimeter/radio
telescopes can also be much larger than those of optical wavelengths, the increase in D possible for single-dishtelescopes is generally never enough to obtain the angular resolutions of ground-based optical telescopes, e.g.,
100 or better. For example, the JCMT 15-m diameter antenna has an angular resolution at 850 µm of ∼1400 ,and the Arecibo 300 m diameter antenna has an angular resolution at 21 cm of ∼30 .
To obtain higher angular resolution images than are possible with individual millimeter/radio telescopes,
signals from physically separated antennas can be combined through interferometry. With this technique, sometimes called aperture synthesis, the resolution benefits of a large diameter aperture can be obtained. Observers,
however, must contend with the reality that only certain angular scales, i.e., those determined by the projected
separations of each pair of antennas, will be sampled. This section builds on the concepts introduced previously
to discuss aperture synthesis in more detail.
Earlier, how a plane-parallel wavefront arriving on-axis to an antenna is brought to a focus by a parabolic
surface was described. Since there are no path differences in that case, EM power from across the antennais brought together in phase at the focus. Now imagine that the parabolic surface is divided into N smaller
contiguous areas, i.e., elements. In this situation, the received voltage V (t) is the sum of contributions ∆Vi (t)from each of element i, i.e.,
V (t) =X

∆Vi (t)(3.8)

i

The power received by the antenna is proportional to the running time average of the square of the contributions
from each element. Assuming illumination is the same for each element, the expression for received power in

20

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

terms of the sum of time averages of the products of voltages from element pairs can be rewritten, i.e.,
XXX
hP i ∝ h(∆Vi )2 i =h(∆Vi ∆Vk )i.

(3.9)

Next, this expression can further be rewritten in terms of the sums of element pairs which are the same andthose which are not, i.e.,hP i ∝Xh∆Vi2 i +XXh∆Vi ∆Vk i.

(3.10)

i6=k

The first and second sets of terms in Equation 3.10 are called auto-correlation and cross-correlation terms,
respectively, since the voltages multiplied in each term are from either the same or different elements, respectively.
From Equation 3.10, any measurement with a large filled-aperture telescope can be understood as being
a sum in which each term depends on contributions from only two of the N elements. As long as the contributions from each element arrive at the focus in phase, there is no need for the elements to be physicallycontiguous. Generalizing, each cross-correlation term h∆Vi ∆Vk i in Equation 3.10 can be measured with two
smaller, physically separated antennas (at locations i and k) by measuring the average product of their output
voltages with a correlating, i.e., multiplying, receiver. Moreover, if the source properties are unchanging, there
is no need to measure all pairs at the same time. A given parabolic surface with N elements has N (N − 1)/2
pairs of elements, and these could be observed sequentially to ”synthesize” a measurement by a large filledaperture telescope. Alternatively, numerous pairs of antennas, with each antenna considered an element, canbe distributed to positions at distances much larger than it is possible to build a single filled-aperture telescope,and the signals received by these antennas can be combined in phase to approximate the resolving power of asingle filled-aperture telescope.
The above situation only describes the emission received on-axis from antenna pairs. Of course, as noted
above, emission arrives at the antennas from other directions, leading to phase differences. To understandthe power response expected from a pair of antennas, let’s look at the ideal 1-D situation of a two-antennainterferometer.
Figure 3.4 shows a schematic picture of a two-antenna interferometer separated by distance b, known as abaseline. This distance can be measured in units of the observing wavelength, λ. In terms of familiar unitsof length, b = L/λ, where L is the distance between antennas and λ is the wavelength in the same unit, e.g.,meters. Both antennas observe a common position so located at an angle θ from the meridian. The projected
separation of the two antennas towards so from the perspective of the source is u = b cos θ. In this example, an
on-axis wavefront incident to both telescopes reaches antenna 2 first and the wavefront reaches antenna 1 a little
later, having traversed an extra path length of b · so = b sin θ. In other words, emission received by antenna 1
experiences a geometrical delay relative to that received by antenna 2, where the time equals τg = b·so /c. To
compensate for the geometrical delay, an artificial delay can be inserted into the signal path of antenna 2 (e.g.,
electronically) so that the signals from both antennas arrive at the correlator with the same phase.
Moving slightly off-axis, a small angle from the axis can be described as α, and its 1-D sky position as l =sin α. At angle α, an off-axis signal reaching antenna 1 will have to travel a slightly longer path than an off-axis
signal reaching antenna 2, even with the geometrical delay introduced to compensate for an on-axis signal. This
extra path length is x = u sin α = ul. Indeed, all distances can be considered in this situation in units of the
wavelength of the emission, λ, so that x is the number of wavelengths within a given distance. The extra path
lengths result in phase differences with α that can be characterized where the voltage response of antenna 2,
V2 , can be written in terms of the product of the voltage response of antenna 1, V1 , and a phase delay factor
sinusoidally varying as a function of angle, i.e.,
V2 = V1 e2πi(ul) .

(3.11)

Expanding to two dimensions, introduces β, a direction on the sky orthogonal to α. Also, m = sin β is definedas the small angle analog to l in this new direction, and v = b cos ϕ where ϕ is the angle of the position so on

3.3. VISIBILITIES AND APERTURE SYNTHESIS

21

Figure 3.4: An ideal 1-D two-antenna interferometer consisting of two antennas, 1 and 2, separated by physicaldistance (i.e., a baseline) b. The antennas are both pointed towards a sky location given by so , which is at
an angle θ from the meridian. The projected distance between the two antennas in that direction is thus u =b cos θ. The two antennas are connected to a correlator where the voltages detected from each are combined.
the sky from the reference position orthogonal to θ. Finally, y is defined as the extra path length introducedin this new direction, in units of the wavelength of emission, i.e., y = v sin β = vm. With these changes, thetwo-dimensional voltage response of antenna 2 is:V2 = V1 e2πi(ul+vm) .

(3.12)

Where u and v are identified as specific spatial frequency components of the sinusoid in the E-W and N-S
directions respectively, and these are the projected lengths of the antenna separations measured in units of the
wavelength at the time of observation. Also, l and m are identified as direction cosines relative to a reference
position in the E-W and N-S directions, respectively. Typically, the on-axis position so has l = 0 and m = 0
and is called the phase center.
The correlator acts as a multiplying and time-averaging device for the incoming signals from antennas 1 and2. Hence, its output is:ZZ
ZZ
hV1 V2 i = h
V1 (l, m)dldm
V2 (l, m)dldmi(3.13)

Under the assumption that signals emanating from different parts of the sky are incoherent, the time averagesof the correlation of those signals will be zero. Thus, the product of the integrals in Equation 3.13 can be
simplified to:22

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRYZZ
hV1 V2 i = h
V1 (l, m)V2 (l, m)dldmi
ZZ
hV1 (l, m)V2 (l, m)idldm(3.15)hV1 (l, m)2 ie2πi(ul+vm) dldm.

(3.16)

hV1 V2 i =ZZ
hV1 V2 i =(3.14)As V 2 ∝ P (see Equation 3.9), and P ∝ Iν (see Equation 3.3),
ZZ
hV1 V2 i ∝I(l, m)e2πi(ul+vm) dldm

(3.17)

where I(l,m) is the intensity distribution on the sky. The correlator therefore measures a quantity known as
the complex visibility, V, which is formally the Fourier transform of the intensity distribution on the sky:
ZZ

I(l, m)e2πi(ul+vm) dldm = Aeiφ .

V(u, v) =(3.18)

Note that V is a complex number, and can be described by an amplitude, A, and a phase, φ. The amplitude andphase contain information about the source brightness and its location relative to the phase center, respectively,
at spatial frequencies u and v.

3.4

The Visibility or uv-Plane

The relationship between the sky brightness distribution and the complex visibility distribution is governed by
the van Cittert-Zernike theorem and it is the basis of aperture synthesis. Given that the complex visibility is
the Fourier transform of the sky brightness distribution in the image plane, it follows that the sky brightness
distribution is in turn the inverse Fourier transform of the complex visibility distribution in the visibility plane:
ZZ
V(u, v) =ZZ
I(l, m) =I(l, m)e2πi(ul+vm) dldm

(3.19)V(u, v)e−2πi(ul+vm) dudv

(3.20)

By measuring the distribution of complex visibilities (in the visibility or uv-plane), in principle the sky brightness
distribution can be recovered. In essence, an image is a ”sum” (i.e., the Fourier transform) of the visibilities
where each has an amplitude and phase representing the brightness and relative position of emission on a specificangular scale. The image and its Fourier transform are conjugates of each other, and each contains the sameamount of information.
Two antennas at a given physical distance b can have signals interfered to sample the sky brightness distribution on a scale inversely proportional to the projection of that distance on the sky. As shown above, theresponse of the interferometer is sinusoidal, and is sometimes referred to as a fringe, with spacing on the sky inthe 1-D case of:Fringe Spacing = 1/u (radians) = 1/(b cos θ) = λ/(L cos θ).

(3.21)

In effect, the interference of the signals modifies the angular response of the antennas and the antennas can”see” the true sky brightness distribution only on the scale defined by the wavelength of the sinusoid. As the23

3.5. FIELDS-OF-VIEW AND MOSAICS

fringe spacing depends inversely on the projected distance, antennas closer together measure emission on larger
scales. Conversely, those antennas spaced further apart measure emission on smaller scales. Since fringe spacing
also depends on the wavelength of emission, as b is measured in numbers of wavelengths, observing shorter or
longer wavelengths also can sample smaller or larger scales, respectively. These ideas can be easily generalized
to two dimensions, with the fringe spacing and on-sky orientation depending on the relative magnitudes of uand v.
A given pair of antennas will only instantaneously sample a single scale of the sky brightness distribution.
Given the E-W and N-S separations of the pair, a visibility in the uv-plane is measured. Since visibilities are
samples of a complex-valued function with Hermitian symmetry, a single sampling gives two visibilities, one at(u, v) and its complex conjugate at (−u, −v). To recover the true sky brightness distribution, however, knowledgeof the distribution of visibilities across the uv-plane would be needed. Improving coverage of visibilities overthe uv-plane can be done in several ways. First, multiple antennas can be incorporated into an array, with eachat a different distance from the others to prevent redundancy. An array of N antennas will have N (N − 1)/2
independent baselines, with each pair providing a single pair of samples in the uv-plane. Second, a target can beobserved repeatedly by the array as it appears to move across the sky due to the Earth’s rotation. Though thephysical distances between the antennas do not change, their projected distances do change depending on thealtitude and azimuth of the target. Hence, repeated observations by all the pairs in an array can sample many
visibilities across the uv-plane. Finally, antennas in the array may be arrangeable in several configurations sothat pairs of antennas have different distances and can sample different parts of the uv-plane. Assuming thesource emission is not variable, the combination of these schemes can reasonably sample the uv-plane, yielding
an image that can resemble the true sky brightness distribution.

3.5

Fields-of-view and Mosaics

Note that an interferometer with idealized antennas was described. Each antenna of an actual interferometer,
however, has finite diameter. As described earlier, such antennas have their own power response on the sky PN= A(l, m) (e.g., the Airy function for an unobstructed, uniformly illuminated aperture). Indeed, the individual
antenna response fundamentally limits the extent of an interferometric image made with a single pointing. In
practice, the HPBW of the primary beam serves as the ”field-of-view” of the single-pointing interferometricimage. Moreover, A(l, m) is actually included formally in the correlator output:
ZZ
V(u, v) =A(l, m)I(l, m)e−2πi(ul+vm) dldm.

(3.22)

Hence, an interferometer actually measures the Fourier transform of the sky brightness distribution multipliedby the antenna power response. To recover I(l, m), the image resulting from the Fourier transform of thecomplex visibilities must be divided by A(l, m) as the last step of image processing. This so-called primarybeam correction, however, is only necessary if the resulting image contains extended emission or emission located
far from the phase center.
To counteract the angular fall-off of sensitivity due to the primary beam response, or even to sample emission
over areas on the sky larger than the primary beam, an interferometer can observe adjacent positions, producing
a mosaic. Sensitivity across a mosaic depends on the spacing of the individual positions observed. A mosaic canhave close to uniform sensitivity with a minimum
number of pointings if the positions observed are arranged in√a grid of equilateral triangles spaced by λ/( 3D), where D is the diameter of the antenna. With this spacing,
the fall-off of the primary beam response at one pointing is made up by the responses of the primary beams at
adjacent pointings, except of course at the edge of the mosaic. Also, this grid allows Nyquist sampling to beachieved and all information can be retrieved. Mosaics can be made with adjacent positions that are spaced
either closer or more distant, with non-uniform sensitivities. Mosaics provide increased areal coverage but comewith a cost to observing time. For example, to obtain uniform sensitivity across the primary beam of just one
pointing requires observations of six other pointings arranged in a hexagonal pattern on the sky and spaced at
the Nyquist spacing around the one pointing. A single image is produced by combining the visibilities obtainedat all pointings into a single ensemble that is simultaneously Fourier transformed.

24

3.6

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

Spatial FilteringThough the principles described in Sections 3.3-3.5 should enable the true sky brightness distribution to be recovered, it is impossible in practice to sample completely the uv-plane and obtain all visibilities. The incomplete
uv-plane sampling effectively provides a fundamental limit to the level of detail discernible in the sky brightness
distribution, i.e., down to a minimum scale defined as the resolution. In addition, incomplete sampling resultsin spatial filtering of the true sky brightness distribution, i.e., the resulting images do not contain information
on angular scales unobserved by the interferometer. In particular, the lack of coverage at the shortest baselines(i.e., lower than those sampled by the smallest baselines) results in an intrinsic lack of sensitivity to large-scale
emission. It is crucial for ALMA users to understand these limitations. Further examples can be found in
Chapter 7 (”Imaging”), Sections 7.6 and 7.7.
First let’s discuss resolution. The resolution of any interferometric image depends on the distribution ofvisibilities sampled. Assuming a finite number of M visibilities has been obtained, the uv-plane has beensampled at 2M discrete points. The sampling distribution can then be characterized as an ensemble of 2M(Dirac) delta functions, i.e.,B(u, v) =2MX

δ(u − uk , v − vk ).

(3.23)

k=1

The inverse Fourier transform of this ensemble of visibilities can then be written as:
I D (l, m) = F T −1 {B(u, v)V(u, v)}.

(3.24)

Using the convolution theorem, Equation 3.24 can be rewritten as:
I D (l, m) = b(l, m) ∗ I(l, m)A(l, m).

(3.25)

In effect, the image obtained is the convolution of the true sky brightness distribution (modified by theantenna power response A(l, m)) with the point spread function, b(l, m) = F T −1 {B(u, v)}, the Fourier transformof the uv-plane sampling distribution. The point spread function is sometimes called the synthesized beam or
the dirty beam. It is important to distinguish this beam from the single-dish response function A(l, m), whichin the interferometry context is called the primary beam. The image resulting from the Fourier transform of afinite number of visibilities, I D (l, m), is sometimes referred to as the dirty image.
The measure of how similar an image is to the true sky distribution is sometimes referred to as image fidelity.
Image fidelity depends on the specifics of coverage of the uv-plane sampled by the interferometer. Since thenumbers of samples are necessarily finite and discrete, there are invariably gaps in any practical sampling of
the uv-plane. These gaps mean that no information is obtained about the true sky brightness distribution on
those specific angular scales. Note that visibilities corresponding to those unobserved scales can have any value.
With no information, however, it is typically assumed that V(u, v) = 0 at unsampled locations in the uv-plane.
Including these visibility domain gaps through the Fourier transform produces aliased features in the resulting
image, the magnitude of which depends on the extents and locations of gaps in the uv-plane and the brightnessof emission on sampled scales. If the uv-plane has been reasonably well sampled, the synthesized beam willconsist of a compact positive feature surrounded by positive and negative features of lower relative amplitude.
These latter features, also called sidelobes, can complicate the image since brightness is distributed via the point
spread function throughout the image. The resulting image can have significant artifacts depending on the skybrightness distribution and the sampling of the uv-plane. A dirty image, however, can be improved throughdeconvolution techniques to minimize the effect of incomplete spatial frequency sampling (e.g., CLEAN and its
variants; see Chapter 7).
Though speaking generally about true sky brightness distributions so far, a special note should be made forthe case of point sources. Obviously, a point source is a distribution of emission that is not extended relative
to the resolution of the observation. In this case, the morphology of the dirty image will equal that of the dirty

3.6. SPATIAL FILTERING

25

Figure 3.5: Imaging concepts. Panel a (upper left): Example of a dirty beam, b(l, m). Panel b (upper right):
The related ensemble of discrete points sampled in the uv-plane, B(u, v). The black points were obtained froma compact configuration while the red ones were obtained from an extended configuration. Panel c (lower left):
Example of a true sky distribution, I(l, m). Panel d (lower right): The dirty image I D (l, m) resulting fromobserving I(l, m) over the baselines of B(u, v), or equivalently the convolution of I(l, m) by b(l, m). The antenna
power response, A(l, m), has been ignored in this illustration since it is much wider than the true sky brightness
distribution. (Figure courtesy of D. Wilner.)
beam (e.g., see Equation 3.25). Moreover, the complex visibilities of the point source have the same amplitudes
on all observed angular scales. Of course, sources may appear point-like at low resolutions but may appear
extended in higher-resolution observations.
Figure 3.5 illustrates the concepts of dirty beam and dirty image and their impact on the recovered image.
Panels a and b (upper pair) show respectively the dirty beam and the related ensemble of locations observedin the uv-plane, i.e., the uv-coverage. Note in panel a the positive feature in the center of the dirty beam
distribution and the surrounding positive and negative features of lower amplitude. These latter features arise
from the incomplete sampling of the uv-plane seen in panel b. As an aside, note that two sets of uv-plane samples
are identified in panel b; these result from observations by the same antennas in two different configurations,a compact one (black) and an extended one (red). Panels c and d (lower pair) show respectively an example
of a true sky distribution (here, a model of a ring of emission) and the dirty image. The dirty image is the
convolution of the true sky distribution by the dirty beam, and one can easily see how incomplete sampling of
the uv-plane leads to the appearance of significant artifacts in the resulting dirty image.
The resolution of the dirty image is defined effectively by the compactness of the central feature of the dirty
beam, e.g., half its FWBN. Since the structure of the dirty beam is generally more complicated than that ofa single-dish antenna, e.g., the beam from a uniformly illuminated antenna shown in Figure 3.3, it is not soeasy to measure FWBN. Instead, the resolution is typically approximated to first order by the FWHM of a
Gaussian fit to the central feature of the dirty beam. The resolution of the dirty image depends ultimately on

26

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

how the interferometer antennas are arranged in configurations. In general, distributions connected through a
Fourier transform scale inversely to each other. For example, narrow distributions in one domain have wideones in the other, and vice versa. By analogy, an ensemble of discrete points, B(u, v), clustered around theuv-plane origin provided by a compact configuration yields a low-resolution image since the central beam featureb(l, m) is wide. Conversely, an ensemble of discrete points distributed more widely from the uv-plane origin
yields a high-resolution image since the central beam feature is narrow. Indeed, resolution is fundamentally
limited by the extent of the longest baselines in a given configuration. The minimum scale discernible in theimage is limited by these maximum baselines. A handy formula for the approximate resolution provided by aninterferometer is:Interferometer Resolution = θres = k λ/Lmax ,(3.26)

where k is a factor that depends on the how the visibilities are weighted during inversion (typically ∼1; see
Figure 7.6) and Lmax is the longest baseline in the array.
Another important limitation of interferometric array observations is insensitivity to large angular scales.
This insensitivity arises because interferometric arrays alone cannot sample spatial frequencies lower than thosethat can be sampled by a baseline equal to an antenna diameter. In effect, visibilities at locations on the uvplane at or near its origin are not sampled, leading to the so-called zero-spacing problem. The lack of sensitivity
to larger scale emission due to the zero-spacing problem biases the resulting image to the compact, small-scale
emission of the true sky brightness distribution. As a guideline, the interferometer image has a maximum
recoverable scale given roughly by:
Maximum Recoverable Scale = θM RS ≈ 0.6λ/Lmin ,(3.27)

where Lmin is the minimum baseline in the array configuration. (Strictly speaking, for an input Gaussian
visibility distribution of FWHM θM RS , the ratio of the brightness at source center of an image made by anarray with Lmin to the same made with no central hole in visibility sampling is 1/e; see Wilner & Welch 1994.)
The smallest baseline possible in an array occurs when two antennas are adjacent to each other. Of course, theantennas cannot be moved physically closer together than their diameters. Note that in projection antennas
can appear closer than their diameters. In those cases, found typically when observing low elevation sourcesin compact configurations, the antenna in front blocks the reception by the antenna in the rear. The resulting
visibilities are distorted, e.g., the antenna in the rear receives less power than the one in front. This situation
is called shadowing and affected data are typically removed from the ensemble of observed visibilities.
Figure 3.6 illustrates the idea of spatial filtering using simulations of actual ALMA configurations. Here,panel a shows an optical image of the galaxy M51 used as an example of a true sky brightness distribution,
after changing the frequency of the image to 100 GHz and placing the image center at δ = -40◦ , a declination
easily observable with ALMA. Panels b, c, and d show the recovered images obtained by simulating 32-antenna
observations of the galaxy using the CASA task simobserve only in very extended, moderately extended, andcompact configurations, respectively, and CLEANing. Angular resolutions of 0.5500 , 1.100 , and 3.600 are obtained,
respectively, and the corresponding maximum recoverable scales are 6.600 , 14.400 , and 36.400 , respectively. Larger
scale emission from the galaxy has been filtered out in the very extended configuration observations (panelb), leaving only the compact structures of its arms. On the other hand, these compact structures are notvery discernible in the compact configuration observations (panel d). A reasonable compromise is found in themoderately extended configuration observations (panel c), yet some small-scale detail and larger-scale emission
remain missing. Note that though these images are missing angular scales, good science can still be obtainedwith them, as long as their limitations are properly understood. Combining data obtained from multiple
configurations, or having more antennas, would increase the fidelity of recovered images.

3.7

Multi-configuration Observations

As previously discussed, a given configuration with baselines ranging from Lmin to Lmax is sensitive to angularscales from ∼θM RS to θres . Sensitivity to a broader range of angular scales is possible by combining data

3.7. MULTI-CONFIGURATION OBSERVATIONS

27

Figure 3.6: Examples of spatial filtering using the CASA task simobserve and actual ALMA configurations from
Cycle 1. Panel a (upper left): An optical image of the galaxy M51 used as a template for a true sky brightness
distribution for the simulations. The frequency of the emission has been changed to 100 GHz, the image sizehas been scaled to ∼30 × 30 , and its declination has been changed to -40◦ to allow ALMA observations to be
simulated. For the simulations, the galaxy was “observed" over a mosaic of 39 pointings, for ∼10 hours intotal. The resulting dirty images were CLEANed. Panel b (upper right): The high-resolution image of thegalaxy obtained when observed in an ALMA (Cycle 1) configuration with minimum and maximum baselinesof 40.6 m and 1091.0 m, respectively (C32-6). The resulting synthesized beam is ∼0.5500 and the maximum
recoverable scale is 6.600 . Panel c (lower left): Medium-resolution image of the galaxy when observed in an
ALMA configuration with minimum and maximum baselines of 20.6 m and 558.2 m, respectively (C32-4).
The resulting synthesized beam is ∼1.100 and the maximum recoverable scale is 14.400 . Panel d (lower right):
Low-resolution image of the galaxy when observed in an ALMA configuration with minimum and maximum
baselines of 14.2 m and 81.4 m, respectively (C32-1). The resulting synthesized beam is ∼3.800 and the maximum
recoverable scale is 36.400 .

28

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

obtained in multiple configurations, where more extensive coverage of the uv-plane is attained. For example, thesame source can be observed in different configurations of the 12-m Array, with more extended configurations
providing higher angular resolutions. For sensitivity to extended structures, the more compact 12-m Arrayconfigurations or the more tightly clustered 7-m Array can be used. Finally, the individual Total Power (TP)Array antennas of the ACA can be used to map the largest angular scales and address the zero-spacing problem.
During proposal preparation, ALMA users should take note of the maximum recoverable scale needed to ensurethat the proposed observations will be able to recover the scales needed to address the science in question.
The ALMA Observing Tool will determine which combination of configurations will yield the desired angularresolution and maximum recoverable scale.
Data combination appears to work best when the signal-to-noise ratios (SNR) of the datasets are similar.
Otherwise, information on scales covered by lower SNR data is relatively less reliable, making interpretationof the images difficult. In addition, the accuracies of the astrometry and calibration of the different datasets
are crucial. Assuming the SNR of the individual datasets is high, combination is best done in the visibility
domain rather than the image domain to minimize the effect of artifacts produced by aliasing, i.e., incomplete
uv-coverage, in either dataset. For example, interferometer data obtained from different configurations should
be combined in the visibility domain and then the new ensemble should be Fourier transformed to produce a
new dirty image.
Combining single-dish data and interferometer data also works best in the visibility domain, as long as bothdatasets have high SNRs. In this case, the single-dish image can be Fourier transformed into the visibility
domain and the resulting visibilities added to the ensemble of those obtained by the interferometer. The newensemble can be then Fourier transformed en masse to produce a new image. Such data combination works
best if the single-dish and interferometric datasets have significant uv-coverages in common. For example, areasonable overlap in uv-coverage can provide enough data to reveal amplitude calibration differences that canbe minimized by re-scaling the single-dish visibilities relative to the interferometric ones. In general, a reasonable
overlap of uv-coverage will occur if the single-dish data are obtained by an antenna that has a diameter twice
the minimum baseline of the interferometer, e.g., approximately the interferometer antenna diameter. Multiple
interferometer pointings, i.e., mosaics, can also partially recover missing low spatial frequency information.

3.8

Units and Conversions

Finally, this Chapter ends with a discussion of various units used in millimeter and radio astronomy anddescribe some useful conversions. Returning to the concept of specific intensity, this quantity can be describedalternatively in terms of a temperature:Iν (θ, ϕ) =2kν 2
TB (θ, ϕ).
c2(3.28)In this equation, TB is the brightness temperature, the temperature of a blackbody with the same specificintensity at a given frequency in the Rayleigh-Jeans limit, i.e., hν/kT  1. Brightness temperature serves as anequivalent way of expressing the specific intensity of an astronomical source. The unit of brightness temperature
is Kelvin (K).
In turn, brightness temperature can be included into the definition of flux density, Sν (Equation 3.2), where

Sν =

2kν 2
c2

Z
TB dΩ.

(3.29)

Assuming the beam is Gaussian, one can then connect brightness temperature to flux density following:


T
1K




=

Sν
1 Jy

"

2  00   00 #
300 GHz
1
1
13.6
.
ν
θmax
θmin

(3.30)

3.8. UNITS AND CONVERSIONS

29

Note again that flux densities observed by ALMA are typically in units of Janskys, where 1 Jy = 10−26 W
m−2 Hz−1 = 10−23 erg s−1 cm−2 Hz−1 . The ALMA Observing Tool converts between temperatures and flux
densities using these formulae.
An important point ALMA users must consider when proposing their projects is the dependence of brightness
temperature sensitivity on synthesized beam size. Using Equation 3.30, one sees that an rms value in flux density(∆S) can translate to an rms value in brightness temperature (∆T ), assuming a given synthesized beam size.
Larger beam sizes correspond to lower ∆T , i.e., the surface brightness sensitivity increases. In turn, extended low
surface brightness objects may be harder to detect at higher angular resolutions as the corresponding sensitivities
may be too low. Typically, a compromise must be obtained between angular resolution and brightness sensitivity
when planning interferometric observations.
References
Wilner, D. J., & Welch, W. J. 1994, ApJ, 427, 898

30

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

Chapter 4

Receivers
The ALMA front end can accommodate up to 10 receiver bands covering most of the wavelength range from10 to 0.3 mm (30–950 GHz). Each receiver band is designed to cover a tuning range which is approximately
tailored to the atmospheric transmission windows. These windows and the tuning ranges are outlined in Figure4.1. In Cycle 5, Bands 3, 4, 5, 6, 7, 8, 9, and 10 are available (see available frequency and wavelength ranges
for these bands in Table 4.1). The receivers are described in more detail in the following sections as well as in
the references listed in Table 4.2.

Figure 4.1: The ten ALMA receiver bands. Receiver bands for Cycle 5 are shown in red or purple superimposedon a zenith atmospheric transparency plot at the Array Operation Site (AOS) for 0.5 mm of Precipitable Water
Vapor (PWV). Band 5 (shown in purple) is newly available in Cycle 5.
The ALMA receivers in each antenna are situated in a single front-end assembly (see Appendix A, Section
A.4). The front-end assembly consists of a large cryostat containing the receiver cold cartridge assemblies(including Superconductor-Insulator-Superconductor (SIS) mixers and Local Oscillator (LO) injections) and theIntermediate Frequency (IF) and LO room-temperature electronics of each band (the warm cartridge assembly,

31

32

CHAPTER 4. RECEIVERSBand

Frequency/
Wavelength
range(GHz)1 /(mm)LO range(GHz)

Sidebandmode2

IF range
(GHz)

Inst.
IF bandw.
(GHz)4Trx over80% ofband(K)6

Trx atany frq.
(K)63

84.0-116.0/
2.59-3.57
125.0-163.0/
1.84 - 2.40
163.0-211.0/
1.84 - 2.40
211.0-275.0/
1.09-1.42
275.0-373.0/
0.80-1.09
385.0-500.0/
0.60-0.78
602.0-720.0/
0.42-0.50
787.0-950.0/
0.32-0.38

92 - 108

2SB

4–8

7.5

<417

<457

133 - 155

2SB

4–8

7.5

<51

<82

171 - 203

2SB

4–8

7.5

<65

<105

221 - 265

2SB

5–103

7.5

<83

<136

283 - 365

2SB

4–8

7.5

<147

<219

393 - 492

2SB

4–8

7.5

<196

<292

610 - 712

DSB

4–12

7.5(15)5

795 - 942

DSB

4–12

7.5(15)5

<175
(DSB)
<2308
(DSB)

<261
(DSB)
<344
(DSB)

4
5
6
7
8
9
10

Table 4.1: Receiver Specifications. Notes to Table: 1. Frequency range is the maximum available, at theextreme upper and lower limits of the IF passband. For FDM mode, the coverage is a bit smaller (See Section
6.4) 2. Sideband modes: SSB means single sideband receiver, 2SB means dual sideband receiver where the two
sidebands are available simultaneously, DSB means double sideband receiver. See text for details. 3. Usable
IF range is extended to allow simultaneous observations of multiple lines. However, the autocorrelation noise
performance is degraded by a factor of up to about 1.5 below 5.5 GHz (Section 4.2.4) 4. Maximum instantaneous
IF bandwidth, limited by the back-end filters and spectrometers. As both upper and lower sidebands both passthrough the same IF bandwidth but are subsequently separated, the effective signal bandwidth given in thiscolumn for 2SB receivers is twice the actual IF filter bandwidth. In addition, this is per polarization, so thetotal effective bandwidth for each receiver is then another factor of 2 higher. Note that the effects of theanti-aliasing filters have been included (see Section 6.4). 5. In Cycle 5, the maximum bandwidth will beapproximately double in cross-correlation mode, because both sidebands can be separated and correlated using
90-degree phase switching (see Section 6.3.4 and Section B.4.4). 6. List of the minimum specification of the
SSB receiver temperature (Trx ), unless otherwise noted, is shown. These values are the average over the IF
band. The sections on individual receiver bands describe the typical values measured, which in many cases are
better than specifications. 7. The specification for Band 3 receivers is Trx <41 K at LO=104 GHz, and Trx <45
K for any other valid LO setting. Both values should be the average over all four IFs and 4 GHz bandwidth.
8. The specification for Band 10 receivers is Trx <230 K within a selected 80 % portion of that band (787-950
GHz).

Topic

Author/YearTechnical papers or Meeting proceedings

ADS identifier

B3
B4
B5
B6
B7
B8
B9
B10
Optics
WVR

Claude et al. 2008
Asayama et al. 2014
Bhushan et al. 2010
G. A. Ediss, et. al 2004
Mahieu et al. 2012
Sekimoto et al. 2008
Baryshev et al. 2007
Uzawa et al. 2009
Rudolf et al. 2007
Emrich et al. 2009SPIE 7020
PASJ, 66 (3), 57(1-13)
21th Intl Symp Space Terahertz Tech
15th Intl Symp Space Terahertz Tech
Trans. THz Sci. and Tech., 2(1) 29-39
19th Intl Symp Space Terahertz Tech
19th Intl Symp Space Terahertz Tech
20th Intl Symp Space Terahertz Tech
IEEE Trans. on Antennas & Propagation
20th Intl Symp Space Terahertz Tech

2008SPIE.7020E..33C
2014PASJ...66...57A
2010stt..conf..137B
2004stt..conf..181E
2012ITTST...2...29M
2008stt..conf..253S
2008stt..conf..258B
2009stt..conf...12U
2007ITAP...55.2966R
2009stt..conf..174E

Table 4.2: Technical papers describing the receiver bands, optics and the water vapor radiometer.

4.1. LOCAL OSCILLATORS AND IF RANGES

33

WCA). The cryostat is kept at a temperature of 4 K through a closed cycle cooling system. The Amplitude
Calibration Device (ACD) is mounted above the front end (see Appendix A.5). Each receiver cartridge contains
two complete receiving systems sensitive to orthogonal linear polarizations. The designs of the mixers, optics,
LO injection scheme, and polarization splitting vary from band to band, depending on the optimum technology
available at the different frequencies; each receiver is described in more detail in the sections below.
Up to three bands can be switched on at a time (more would risk overloading the cryostat cooler). Froma hardware point of view, it takes only about 1-2 seconds to switch between two bands which are powered up(limited by the LO locking and antenna movement). For bands that are not switched on, the time to fully
thermally stabilize a receiver from an off state is up to ∼15 minutes - this is mainly to ensure the optimum
flat bandpass shape. All of the receivers are mounted off axis in order to avoid extra rotating band selection
mirrors, which necessitates an offset of the antenna to change band. It means that only one receiver can beused at a given time.

4.1

Local Oscillators and IF Ranges

The observed sky frequencies need to be down converted to frequency bands between 2-4 GHz in order to send
the digitized signals to the correlator (see Section 6.1). This frequency down conversion involves a set of LOs,
and the LO and IF systems are described in detail in Appendix B.
The front-end mixer uses LO1 to down-convert the sky frequencies into an IF band with a range of 4–12
GHz. This covers the needs of all the ALMA bands, since the mixers for Bands 3, 4, 5, 7, and 8 have an output
range of 4–8 GHz, Band 6 a range of 5–10 GHz and Bands 9 and 10 a range of 4–12 GHz (Table 4.1). The
possible sky frequency ranges covered by each receiver with the first LO, LO1, set to a frequency FLO1 are:
• For the lower sideband (LSB): (FLO1 - IFlo ) to (FLO1 - IFhi )• For the upper sideband (USB): (FLO1 + IFlo ) to (FLO1 + IFhi )where IFlo and IFhi are the lower and upper IF ranges in the “IF Range” column of Table 4.1, and the IF
bandwidth (per sideband) is IFhi –IFlo . The ranges of LO1 are given in column 3 of Table 4.1. This is illustrated
in Figure 4.2. Note that the maximum IF bandwidth in Table 4.1 may be a few percent less than the IF rangein Table 4.1 (see Section 6.4).

Figure 4.2: IF ranges for the two sidebands in a heterodyne receiver.

4.2

The Cycle 5 Receivers

The receivers for Bands 3 to 8 are two-sideband (2SB) receivers, where both the upper and lower sidebands areprovided separately and simultaneously. There are 4 outputs from each of the receivers, comprising the upper

34

CHAPTER 4. RECEIVERS

and lower sidebands in each of the two polarizations. Each output has a bandwidth of 4 GHz (slightly more forBand 6) which is reduced to an effective total bandwidth of 3.75 GHz due to the anti-aliasing filters, etc., see
Appendix B.3.5. The mixers give 10 dB or more unwanted sideband rejection, which is adequate for reducing
the degradation of S/N from noise in the unwanted sideband, but not adequate for suppressing astronomicalsignals in the unwanted sideband. Further suppression is performed by offsetting LO1 and LO2 (and eventually
the tunable filter LO, TFB LO) by small and opposite amounts, as well as 180-degree phase-switching, theoffsets of which depend on the antenna such that the signals from two antennas in the image sideband do notcorrelate (see Chapter 6).
Bands 9 and 10 use double sideband (DSB) receivers, where the IF contains noise and signals from bothsidebands. They only have two outputs, one per polarization. The IF effective bandwidth is 7.5 GHz perpolarization (after passing through the IF processing units), so the total instantaneous receiver bandwidth is
the same as Bands 3 - 8. In Cycle 5, however, both sidebands can be simultaneously correlated using 90-degree
phase switching (see Chapter 6), although this does not remove the noise from the opposite sideband. The
effective system bandwidth available in Bands 9 and 10 is therefore double that of the 2SB receivers.
Each of the ALMA receiver bands is different in several aspects, and the following sections describe theindividual receiver bands in more detail.
Figure 4.3 shows the layout of the ALMA receiver bands in the ALMA cryostat.

Figure 4.3: The layout of the ALMA receiver bands within the ALMA cryostat. Also shown is the orientationof the receiver polarization position angles.

4.2. THE CYCLE 5 RECEIVERS

4.2.1

35

Band 3 ReceiverBand 3 is the lowest frequency band available in Cycle 5, covering a frequency range of 84.0–116.0 GHz (inthe 3 mm atmospheric window). The cartridge is fed by a “periscope” pair of ellipsoidal pickoff mirrors locatedoutside the cryostat, which refocus the beam through the cryostat window, allowing for a smaller window
diameter (Figure 4.4). A single feedhorn feeds an ortho-mode-transducer (OMT) which splits the incoming
signal into two linear orthogonal polarizations and feeds the SIS mixers.

Figure 4.4: Input optics for Band 3, showing the warm pickoff mirrors. The location of the antenna beam fromthe secondary mirror is shown by the solid line, and the Cassegrain focus is shown by the small circle to theupper right.
A block diagram of the Band 3 receiver, including the cold cartridge and warm cartridge assembly, is shownin Figure 4.5. The Cold Cartridge Assembly (CCA) contains the corrugated feedhorn, OMT, SIS mixers andthe low-noise HEMT first IF amplifiers. At room temperature, the Warm Cartridge Assembly (WCA) includes
further IF amplification and the Local Oscillator covering 92–108 GHz.
The acceptance criteria for the Band 3 receiver noise performance (Trx ) is <41 K at LO1=105 GHz, and<45 K for any other valid LO setting (the OT assumes 45 K). The achieved performance is typically somewhat
better than this, with Trx ∼37 K. The atmospheric transmission over most of Band 3 is very high, even witha large PWV (Figure 4.6) which means observations in Band 3 can (and do) take place with up to 10 mm ormore of PWV. The system temperature (Tsys ) shows the expected rise at the higher end, due to an atmospheric
oxygen line (Figure 4.7), so that the increase is mostly independent of the PWV.

36

CHAPTER 4. RECEIVERS

Figure 4.5: Block diagram of the Band 3 receiver (left) including CCA (upper) and WCA (lower). Right image
shows a Band 3 CCA. Note the single feedhorn which feeds the OMT, splitting the two polarization signals forthe 2SB mixers. The Band 3 cartridges were constructed in Canada at NRC-HIA, Victoria.

4.2. THE CYCLE 5 RECEIVERS

37

Figure 4.6: Band 3 zenith transmission for 1, 5 and 15 mm of PWV. Frequency is in GHz.

Figure 4.7: Typical system temperature (Tsys ) at zenith for Band 3 with 1.262 mm of PWV. Tsys was computed
using only the receiver temperature values adopted in the OT and the atmospheric contribution. No spill-overor background terms have been included. Temperature is given in Kelvin.

38

4.2.2

CHAPTER 4. RECEIVERS

Band 4 Receiver

The Band 4 receiver covers the 125 to 163 GHz spectral window (in the 2 mm atmospheric window). The signal
collected by the telescope is focused to the Band 4 cartridge using a set of warm mirrors (Figure 4.8). A single
feedhorn feeds an OMT which splits the two linear polarizations and feeds the 2SB SIS mixers.

Figure 4.8: Optical layout of the Band 4. Red indicates Band 4 Gaussian beam of 5 times the beam width.
A block diagram of the Band 4 receiver, including the cold cartridge and warm cartridge assembly, is shownin Figure 4.9. The Band 4 CCA contains a feed horn, an OMT as a polarization splitter, 2SB SIS mixer
assemblies, cold IF amplifiers, isolators, and LO frequency doublers. The RF signal is down converted to 4–8
GHz using a 2SB mixer unit.
The atmospheric transmission in Band 4 is shown in Figure 4.10 for three typical PWV values. Most
observations in Band 4 will be done with PWV < 5 mm. The specification for Band 4 receiver noise performance(Trx ) is <51 K over 80% of the band, and <82 K over the whole band (SSB). The OT assumes 51 K. The resulting
system temperatures (Tsys ) for 1.262 mm PWV are shown in Figure 4.11. The on-array performance of thereceivers is often more typically ∼40 K over most of the band, so the achieved Tsys may be slightly lower.

4.2. THE CYCLE 5 RECEIVERS

39

Figure 4.9: Block diagram of the Band 4 receiver (left) including CCA (upper) and WCA (lower). Right image
shows a Band 4 CCA. A single feedhorn feeds the OMT, splitting the two polarization signals for the 2SB
SIS mixers. The LO is generated in the WCA, with the final x2 multiplier on the 110 K stage. The Band 4
cartridges were constructed at the Advanced Technology Center (ATC).

40

CHAPTER 4. RECEIVERS

Figure 4.10: Band 4 zenith transmission for 0.5, 1 and 5 mm of PWV. Frequency is in GHz.

Figure 4.11: System temperature (Tsys ) at zenith for Band 4 with 1.262 mm of PWV. Tsys was computed using
only the receiver temperature values adopted in the OT and the atmospheric contribution. No spill-over orbackground terms have been included. Temperature is given in Kelvin.

4.2. THE CYCLE 5 RECEIVERS

4.2.3

41

Band 5 Receiver

The Band 5 receiver covers the 163 to 211 GHz spectral window (in the 1.42-1.84 mm atmospheric window).
The signal collected by the telescope is focused to the Band 5 cartridge using a set of cold mirrors (Figure 4.12).
A single feedhorn feeds an OMT which splits the two linear polarizations and feeds the 2SB SIS mixers.

Figure 4.12: Optical layout of the Band 5. Placing the mixer assembly along the side of M 1 and streamlined
layout of the IF system are the key to fulfil the requirements on 5wo optical beam clearance.

Figure 4.13: Block diagram of the Band 5 receiver (left) including CCA (upper) and WCA (lower). Right image
shows a Band 5 CCA. Note the single feedhorn which feeds the OMT, splitting the two polarization signals forthe 2SB SIS mixers. The active multiplier (x3, a power amplifier, then x2) is mounted between the 300 K and
110 K stage.

42

CHAPTER 4. RECEIVERS

A block diagram of the Band 5 receiver, including the cold cartridge and warm cartridge assembly, is shownin Figure 4.13. The Band 5 CCA contains a feed horn, an OMT as a polarization splitter, 2SB SIS mixer
assemblies, cold IF amplifiers, isolators, and LO frequency doublers. The RF signal is down converted to 4–8
GHz using a 2SB mixer unit.
The atmospheric transmission in Band 5 is shown in Figure 4.14 for three typical PWV values. The specification for Band 5 receiver noise performance (Trx ) is <65 K over 80% of the band, and <105 K over the wholeband (SSB Trx ). The OT assumes 55 K. However, the performance of the receiver is considerably better than
50 K over the band. The resulting system temperatures (Tsys ) are shown in Figure 4.15.

Figure 4.14: Band 5 zenith transmission for 0.5, 1 and 5 mm of PWV. Frequency is in GHz.

Figure 4.15: Typical system temperature (Tsys ) at zenith for Band 5 for three typical PWV values. (Tsys wascomputed using only the receiver temperature values adopted in the OT and the atmospheric contribution. No
spill-over or background terms have been included. Temperature is given in Kelvin.)

4.2. THE CYCLE 5 RECEIVERS

4.2.4

43

Band 6 Receiver

The Band 6 receiver covers a frequency range of 211.0–275.0 GHz (the 1.3 mm atmospheric window). This
receiver has a window with a pair of off-axis ellipsoidal mirrors inside the cryostat (Figure 4.16). A single
feedhorn feeds an OMT which splits the two linear polarizations and feeds the SIS mixers. A block diagram of
the Band 6 receiver, including the cold cartridge and warm cartridge assembly, is shown in Figure 4.17.

Figure 4.16: Band 6 cold off-axis ellipsoidal mirrors feeding the single feedhorn. The off-axis beam from thetelescope secondary mirror (shown by the dashed line) feeds directly through the cryostat window, and theCassegrain focus is just inside the inner infrared blocking filter. Note the slightly inclined inner window,
designed to minimize standing waves.
The Band 6 IF frequency has been chosen to allow for multiple simultaneous line observations1 ; it covers therange 5.0–10.0 GHz. There is ∼10-25% excess receiver noise below 5.5 GHz due to LO1 (although the increaseof Tsys is less), however this multi-transition setup is still considerably more efficient than observing each line
separately. However, it is recommended that for continuum observations, the IF range 6-10 GHz is used. Also,
it should be noted that the full range 5–10 GHz cannot be completely sampled because of the limited 4 GHz
width of the two basebands per polarization.
The atmospheric transmission in Band 6 is shown in Figure 4.18 for three typical PWV values. Most of thenarrow absorption lines are from ozone.
The specification for Band 6 receiver noise performance (Trx ) is <83 K over 80% of the band, and <136 K
over the whole band (SSB Trx ). The achieved on-array results are considerably better, typically ∼40–50 K overmost of the band. The OT assumes 55 K. The resulting system temperatures (Tsys ) for 1.262 mm PWV areshown in Figure 4.19.

1 Specifically, the 12 CO/13 CO/C18 O J =2 -1 combination at 230.538/220.398/219.560 GHz, which has a minimum separationof 10.14 GHz and requires the IF to reach to 5.0 GHz in order to cover all three lines.

44

CHAPTER 4. RECEIVERS

Figure 4.17: Band 6 receiver block diagram, and (right) image of cartridge. Note the OMT used to split thepolarizations feeding the two 2SB mixers. The LO around 80 GHz requires an extra ×3 multiplier inside thecryostat. The Band 6 cartridges were built at NRAO, Charlottesville. Note that the IF output range is actually
5-10 GHz; the range shown is the one recommended for continuum observations (see text).

4.2. THE CYCLE 5 RECEIVERS

45

Figure 4.18: Band 6 zenith transmission for PWV=0.5, 1 and 5 mm. Frequency is in GHz. Most of the narrowabsorption lines are from ozone.

Figure 4.19: Typical Tsys at zenith for Band 6 with 1.262 mm PWV, based on measured values of the receivertemperatures. Tsys was computed using only the receiver temperature values adopted in the OT and theatmospheric contribution. No spill-over or background terms have been included. Temperature is given in
Kelvin.

46

4.2.5

CHAPTER 4. RECEIVERS

Band 7 Receiver

The Band 7 receiver covers the frequency range 275–373 GHz (the 0.85 mm atmospheric window). It has asimilar cold optics design as Band 6, but uses a wire-grid polarization splitter instead of an OMT (Figure 4.20).
A block diagram of the Band 7 receiver, including the cold cartridge and warm cartridge assembly, is shown in
Figure 4.21.

Figure 4.20: Band 7 cold optics arrangement, showing the off-axis ellipsoidal mirrors and the polarization
splitter wire grid.
The atmospheric transmission in Band 7 is shown in Figure 4.22 for three typical PWV values. The specification of the Band 7 receiver noise temperature is Trx <147 K over 80% of the range and <219 K over thewhole tuning range, except at the upper end of the band (370-373 GHz), where the specifications are <300 K
SSB. However, the performance of the receiver as measured in the lab and on the array is considerably better
than this, with typically 65 K achieved, in mid-band. The OT assumes 75 K over the whole band. The resulting
system temperatures (Tsys ) for 1 mm PWV are shown in Figure 4.23. Note that the atmospheric transmission(and hence Tsys ) at frequencies below 300 GHz is considerably better than that of the top half of Band 7; inthat respect the performance is closer to that of Band 6. Also to maximise continuum sensitivity, the deep
water absorption lines around 325 GHz should be avoided if possible.

4.2. THE CYCLE 5 RECEIVERS

47

Figure 4.21: Band 7 front-end receiver block diagram, and (right) annotated image of the Band 7 cartridge.
Note the polarization-splitting grid and LO injection in the cold optics above the mixers. The Band 7 cartridges
were built at IRAM in France.

48

CHAPTER 4. RECEIVERS

Figure 4.22: Band 7 atmospheric zenith transmission for PWV=0.5, 1.0 and 5.0 mm. Frequency is in GHz.
The deep atmospheric absorption at 325 GHz is due to water, and the narrower feature at 369 GHz is due tooxygen.

Figure 4.23: Typical Tsys at zenith for Band 7 with PWV=0.913 mm. Tsys was computed using only the receivertemperature values adopted in the OT and the atmospheric contribution. No spill-over or background terms
have been included. Temperature is given in Kelvin.

4.2. THE CYCLE 5 RECEIVERS

4.2.6

49

Band 8 ReceiverBand 8 covers the frequency range 385-500 GHz (650 µm atmospheric window). The cryogenic optics of thisreceiver adopts a single mirror to couple a feed horn in front of an SIS mixer block to the sub-reflector. A single
feedhorn feeds an OMT which splits the two linear polarizations and feeds the 2SB SIS mixers (Figure 4.24).

Figure 4.24: Optical layout of the Band 8 receiver.
A block diagram of the Band 8 receiver, including the cold cartridge and warm cartridge assembly, is shownin Figure 4.25. The Band 8 CCA consists of a cold optics, a feed horn, an OMT, 2SB SIS mixers assemblies,
cold IF amplifiers, isolators, and LO frequency sextuplers.
The atmospheric transmission in Band 8 is shown in Figure 4.26 for three typical PWV values. The specification of the Band 8 receiver noise temperature is Trx <196 K over 80% of the range and <292 K over the wholetuning range. However, the performance of the receiver as measured in the lab and on-array is considerably
better than this, with typical values of 70-120 K. The OT assumes 150 K. The resulting system temperatures(Tsys ) for 0.472 mm PWV are shown in Figure 4.27. Note that transmission in the lower part of the band isalmost as high as Band 7, whereas at the high-frequency end of the band (e.g. around the CI line at 492 GHz)
the transmission is as low as the centre of Band 9.

50

CHAPTER 4. RECEIVERS

Figure 4.25: Block diagram of the Band 8 receiver (left) including CCA (upper) and WCA (lower). Right image
shows a Band 8 CCA. Note the single feedhorn which feeds the OMT, splitting the two polarization signals forthe 2SB SIS mixers. The Band 8 cartridges were constructed at the Advanced Technology Center (ATC).

4.2. THE CYCLE 5 RECEIVERS

51

Figure 4.26: Band 8 atmospheric zenith transmission for PWV=0.5, 1.0 and 2.0 mm. Frequency is in GHz.
The atmosphere in the Band 8 frequency range has some deep absorption by water and oxygen.

Figure 4.27: Typical Tsys at zenith for Band 8 with PWV=0.472 mm. Tsys was computed using only the receivertemperature values adopted in the OT and the atmospheric contribution. No spill-over or background terms
have been included. Temperature is given in Kelvin.

52

4.2.7

CHAPTER 4. RECEIVERS

Band 9 ReceiverBand 9 covers the frequency range 602-720 GHz (450 µm atmospheric window). It uses a wire grid in order toseparate the two orthogonal polarizations, as well as to provide the LO injection scheme (Figure 4.28).

Figure 4.28: Basic Band 9 optics layout. The signal path is symmetrical for the vertical polarization (P0) andthe horizontal polarization (P1). For P1 the path is as follows: a telescope focal point followed by mirror M3,
grid, mirror M4, a beam splitter for LO insertion and finally the mixer horn U1. For P0 the signal follows fromFP to the same mirror M3 and then, reflected by the grid, comes to mirror M4, a beam splitter, and mixer horn
U1.
The mixers are double sideband (DSB), and therefore additional techniques must be employed during theobservations to either separate the sidebands or reject the unwanted sideband. LO offsetting can be used toreject one of the two sidebands, which can be chosen independently for each spectral window. Note that LO
offsetting does not reject the noise from the unwanted sideband, it simply moves any correlated signal to ahigh fringe rate so that the signal is smeared over a larger bandwidth increasing noise incoherently. In Cycle
5, 90-degree phase switching can also be used to correlate both USB and LSB simultaneously (see Chapter 6).
The IF bandwidth in this receiver is 8 GHz per polarization (7.5 GHz effective bandwidth after the IF Processor
units, see Section 6.4), covering 4-12 GHz. A block diagram of the Band 9 receiver, including the cold cartridge
and warm cartridge assembly, is shown in Figure 4.29.
The Band 9 atmospheric transmission is significantly dependent on the PWV, as illustrated in Figure 4.30
for three low values of PWV. The specifications for the receiver are Trx <175 K over 80% of the band and<261 K over all the band. However, the performance is considerably better than this, with engineering andtypical on-array values for Trx of 65-120 K. The OT assumes 110 K. Figure 4.31 shows the expected Tsys for0.472 mm of PWV, over most of the band given the OT default expected receiver noise, however, the achieved
value is extremely dependent on the line-of-sight PWV. Phase stability also limits when observations can bemade, therefore, most observations in Band 9 are done at night (most commonly during austral winter). As wellas having a lower atmospheric transmission and a less stable atmosphere, Band 9 observing provides several

4.2. THE CYCLE 5 RECEIVERS

53

Figure 4.29: Block diagram of Band 9 cartridge (left) and a schematic image (right). Note that there are only
two IF outputs, one from each polarization in this DSB receiver. The extra Faraday rotation mirror in the LO
system is part of the ALMA fibre-optic Line Length Corrector system (see Appendix B.3.3), and means thatthe Band 9 receiver must be available on all the antennas for this to work. The Band 9 receiver was built at
SRON in the Netherlands.

54

CHAPTER 4. RECEIVERS

challenges: finding sufficiently bright calibrators (most QSOs are relatively faint at this frequency), requiring
accurate pointing for the relatively small primary beam (although the actual pointing is done in Band 6), andthe need for the highest level of stability in the rest of the system.

Figure 4.30: Band 9 zenith transmission for PWV = 0.2, 0.5 and 1 mm. Frequency is in GHz.

Figure 4.31: Typical Tsys at zenith for Band 9 with PWV = 0.472 mm. Tsys was computed using only thereceiver temperature values adopted in the OT and the atmospheric contribution. No spill-over or backgroundterms have been included. Temperature is given in Kelvin.

4.2. THE CYCLE 5 RECEIVERS

4.2.8

55

Band 10 ReceiverBand 10 covers the frequency range 787-950 GHz (350 µm atmospheric window). Band 10 is the highest
frequency receiver of the ten bands envisioned for the ALMA front-end system. The development of the Band
10 receiver was extremely difficult and faced many technical challenges from its material selection. Niobium(Nb) superconducting tuning circuits, which are used in other ALMA receiver bands, cannot be used for Band
10 SIS mixers due to large losses from pair-breaking above a superconducting gap frequency of about 700 GHz.
Therefore, niobium-titanium-nitride (NbTiN) with a critical temperature of about 15 K, has been utilized in
the tuning circuit of Band 10 mixers. The Band 10 Nb/AlOx/Nb tunnel junctions with NbTiN-based tuning
circuitry achieved ALMA requirements and the best DSB receiver noise temperature was 125 K, corresponding
to about 3 times the quantum limits for 4 K operation.
It uses a wire grid in order to separate the two orthogonal polarizations, as well as to provide the LO
injection scheme (Figure 4.32). The mixers are double sideband (DSB), and therefore LO offsetting is used toreject one of the two sidebands. The IF bandwidth in this receiver is 8 GHz per polarization (7.5 GHz effective
bandwidth after the IF Processor units, see Section 6.4), covering 4-12 GHz. A block diagram of the Band 10
receiver, including the cold cartridge and warm cartridge assembly, is shown in Figure 4.33.

Figure 4.32: Schematic of ALMA Band 10 optics. ALMA Band 10 optics are composed of two elliptical mirrors,
M1 and M2, a wire grid and two corrugated horns.The wire grid is used to separate the two linear polarizations,P0 and P1, and it is located after the two elliptical mirrors to minimize the number of optical components
required.
The Band 10 atmospheric transmission is significantly dependent on the PWV, as illustrated in Figure 4.34
for three low values of PWV. The specifications for this receiver are Trx <230 K over 80% of the band and <344
K over all the band. Typical on-array Trx values are 175-275 K. The OT assumes 230 K. Figure 4.35 showsthe expected Tsys for 0.472 mm of PWV, over most of the band given the OT-assumed receiver noise. Phasestability also limits when observations can be made. Also the antenna surface accuracy has a significant effecton the aperture efficiency at this high-frequency band. Therefore, most observations in Band 10 will be done
at night (and mostly during austral winter), when the sky and the system is most stable. As well as having alower atmospheric transmission and a less stable atmosphere, Band 10 observing provides the most challenges
for observing: finding sufficiently bright calibrators (most QSOs are relatively faint at this frequency), requiring
accurate pointing for the relatively small primary beam (although pointing is done in Band 6), and the needfor the highest level of stability in the rest of the system.

56

CHAPTER 4. RECEIVERS

Figure 4.33: Block diagram of Band 10 cartridge (left) and a schematic image (right). Note that there are only
two IF outputs, one from each polarization in this DSB receiver. The Band 10 cartridges were constructed at
the Advanced Technology Center (ATC).

4.2. THE CYCLE 5 RECEIVERS

57

Figure 4.34: Band 10 zenith transmission for PWV = 0.2, 0.5 and 1 mm. Frequency is in GHz.

Figure 4.35: Typical Tsys at zenith for Band 10 with PWV = 0.472 mm. Tsys was computed using only thereceiver temperature values adopted in the OT and the atmospheric contribution. No spill-over or backgroundterms have been included. Temperature is given in Kelvin.

58

CHAPTER 4. RECEIVERS

Chapter 5

The Correlators
A correlator can be viewed as the virtual focal plane of an interferometer array where all voltage-based signals
from all individual antennas are processed to derive both the cross-correlation products from all independent
antenna pairs and the autocorrelation function of each antenna. It delivers complex fringe visibilities which, once
calibrated in amplitude and phase, allow the ALMA users to synthesize astronomical images. The correlator also
provides pre-correlation delay and phase tracking functions to adjust the response to the wavefronts of received
signals in order to maintain the coherence of the complex visibilities. Walsh-switching modulations for sideband
separation (90◦ phase switching) and spurious-signal suppression (180◦ phase switching) are demodulated in
the correlator.1
All signals received by ALMA antennas are processed in one of two correlators: the 64-input Correlator(also known as the Baseline Correlator or BLC) and the ACA Correlator. The 64-input Correlator is usedprimarily for the main 12-m Array, while the ACA Correlator is used for the Morita Array comprised of the
ACA 7-m Array and the Total Power Array (i.e. single-dish), respectively2 . Both correlators run simultaneously
and independently. Thus, while the 12-m Array observes an object using the 64-input Correlator, the ACA
Correlator can be used with the 7-m Array and/or the Total Power Array observing either the same or a different
object.
Celestial signals received by the antennas are down converted to lower frequency bands using a set of Local
Oscillators (LOs) and mixers as described in Appendix B. The outputs from the IF system form four BaseBands (BBs), each covering a bandwidth of 2 GHz in two orthogonal linear polarizations. These analog BB
signals are sampled at the sampling frequency of 4 GHz and quantized with eight quantization levels (3 bits per
sample) in digitizers, and then transferred via fiberoptic cable to one of the two correlators.
Both correlators generate auto-correlation and cross-correlation products at the same time. The autocorrelation is used not only for TP-Array observations but also for normalization of cross power spectra andmeasurements of system noise temperatures. The cross-correlations are used for interferometry with the 12-m
Array and the ACA 7-m Array, and also for pointing and focus calibrations for all Arrays.
This chapter addresses capabilities of the correlators to be offered for Cycle 5 observations. The specifications of the correlators determine a lot of observational performance such as bandwidth, spectral resolution,
time resolution, and polarimetry. The phase tracking performance, including online WVR correction, provides
coherence and improves phase stability in correlated data delivered to users. Imperfect correction for the nonlinear response in the correlators invokes systematic errors in complex visibilities. The response of digital signal
processing is also presented in this chapter.
1 Some of these features can be employed outside the correlator.

In the case of the ALMA correlators, the phase tracking istaken in the LO1 and LO2. The 180◦ phase switching is modulated in the LO1 and demodulated in the DTS transmitter after
digitization. See also Sections 5.5.4 and B.4.4, and also Emerson 2005, ALMA memo No. 537.
2 Crossbar switching allows for some flexibility in this arrangement.

59

60

CHAPTER 5. THE CORRELATORS

5.1

The 64-input Correlator

The 64-input Correlator employs hybrid design, also known as the FXF3 system (Escoffier et al. 2007, A&A
462, 801), that brings a 32× spectral resolution of the traditional lag (XF) correlators. It operates in two basic
modes, Time Division Mode (TDM) — equivalent to an XF correlator with a wide bandwidth and a coarse
spectral resolution for mainly continuum observations, and Frequency Division Mode (FDM) with fine spectral
resolutions for spectral-line observations. A simplified overview diagram of the 64-input Correlator is shown in
Figure 5.1. It consists of four quadrants, all of which are available for Cycle 5. Each quadrant can handle a 2
GHz dual-polarization BB for up to 64 antennas4 . The full set of four quadrants is capable of accepting fourBBs to cover a total 8 GHz bandwidth with a dual polarization.
One quadrant to process

4 GHz Digitizer
4 GHz Digitizer
4 GHz Digitizer
4 GHz Digitizer
4 GHz Digitizer
4 GHz Digitizer
4 GHz Digitizer
Digitizes analog signals andapplies ultra fine delay

DATA
Transmitter
DATA
Transmitter
DATA
Transmitter

12:1 Optical Splitter

4 GHz Digitizer

POL 2

12:1 Optical Combiner

POL 1

DATA
Transmitter

DATA
ReceiverTunable Filter Bank Card

DATA
ReceiverTunable Filter Bank Card

DATA
ReceiverTunable Filter Bank Card

DATA
ReceiverTunable Filter Bank Card

Tunable Filter Bank Card

Tunable Filter Bank Card

Tunable Filter Bank Card

Tunable Filter Bank Card

Three optic
carriers

Three optic
carriers

Fine delay andselects bandwidth

Station Card

Station Card

32-parallel outputs x 2-bits
per sample x 2-polarizaitons

Correlator station electronics one baseband, two polarizations

At antenna

Station Card

Station Card

Bulk delay, re-orders
and packetizes samples

Correlator baseline electronics

32-parallel outputs x 2-bits
per sample x 2-polarizaitons
Antenna 0

Plane 31
Plane 2

Plane 1

Plane 032-parallel outputs x 2-bits
per sample x 2-polarizaitons
Antenna 63

Horizontal drive to correlator matrix

Correlator array(one of 4 quadrants in system shown)Long term
accumulator(LTA)

LTA-addertree

Intra-quadrant
results cross bar
and real timecomputerinterface

Real timecomputersystem

4 PCB
Vertical drive to correlator matrix

Figure 5.1: Overview diagram of the ALMA digitizers, data transmission system and 64-input Correlator(Escoffier et al. 2007, A&A 462, 801). The digitized data from the individual BBs are transferred to the
Tunable Filter Banks (TFBs) and station cards (top right) for the parallelization and processing required oneach antenna data stream. The correlator array (lower half) produces auto-correlations on the main diagonal
and cross-correlations elsewhere in the correlator matrix. The correlations are then integrated in the Long-Term
Accumulators (LTAs, lower right).

5.1.1

TDM mode

TDM is mostly used for continuum observations. The simplicity, compared with FDM, offers advantages of alower data rate and better linearity. Therefore, it is used for standard setups such as pointing, focus, delay
calibration, system temperature measurements, sideband ratio measurements, etc.
The full 2 GHz BB is directly sent to the correlator bypassing the Tunable Filter Banks (TFBs). The
correlator cuts off the Least Significant Bit (LSB) to reduce quantization levels from 3- to 2-bits per sample
3 F, X and F stand for filtering, correlation and Fourier transform, respectively.
4

Nant (Nant − 1)
= 2016 baselines and 64 auto-correlations for Nant = 64.
2

5.1. THE 64-INPUT CORRELATOR

61

Figure 5.2: The ALMA 64-input Correlator. This view shows lights glowing on some of the racks of thecorrelator in the ALMA Array Operations Site Technical Building and shows one of four quadrants of thecorrelator. Credit: ALMA (ESO/NAOJ/NRAO), S. Argandoña(see Section 5.3).
The TDM mode provides a Spectral Window (SPW)5 that consists of up to 256/Npol channels per BB,
where Npol is the number of polarization products per BB6 . As the full 2000 MHz BB is covered, this requires
some truncation of the band-edge channels in offline data processing yielding 1875 MHz of usable bandwidth –see Section 6.4.

5.1.2

FDM mode

FDM is adequate for spectral-line observations that require a spectral resolution higher than that of TDM.
Each 2-GHz-bandwidth digitized signal stream is processed in a TFB card, where digital filtering and frequency
conversion with the LO4 are implemented in a Field Programmable Gate Array (FPGA). In a TFB there are
32 independent 62.5 MHz bandpass filters or sub-bands. To avoid edge artifacts, sub-band center frequencies
are set such that their edges overlap and the effective bandwidth is thus reduced by a factor of 15/16, that is,
58.59375 MHz of effective bandwidth per sub-band. The correlator software stitches together contiguous sub15
bands to output a seamless cross power spectrum to form an spw with as many as 16
× 8192/Npol channels. The
number of channels in each spw can be reduced by averaging 2, 4, 8, or 16 channels into one to accommodate
the maximum data rate. Table 5.1 lists the spectral setups for Stokes I (Npol = 2) observations. The number ofvalid sub-bands to form an spw is selectable from 32, 16, 8, 4, 2, or 1. That is, spw bandwidths of 1875, 937.5,
468.75, 234.375, 117.1875, and 58.59375 MHz, respectively. It is possible to have multiple (up to 4) spws in thesame BB. While different spectral setups can be set for spws in different BBs, all of spws in the same BB musthave the same channel spacing.
The center frequency of each spw can be tuned over the 2 GHz-wide BB using the digital LO (LO4) in the
TFB card. However, the edges of the full bandwidth of the sub-bands cannot fall outside the 2 GHz BB range,
and the frequency tuning is made in steps of 30.5 kHz set by the frequency resolution of the TFB digital mixer.
5 An SPW is a continuous spectrum composed of uniformly spaced frequency channels. See also Chapter 6 about the relation
between BB and spw.
6 N
pol = 2 for standard Stokes-I observations that employ XX and Y Y products, and Npol = 4 for full-Stokes observations.

62

CHAPTER 5. THE CORRELATORS

See also Section 5.5.2 for detail about spectral setting.

5.1.3

Correlation and Realtime Processing

The correlation cards perform the multiply-and-add operations to produce the correlation functions at a clock
rate of 125 MHz (4 GHz samples demultiplexed by 32). Four quadrants handle four BBs. A quadrant of
the correlator consists of 32 planes of 64 × 64 256-lag correlator circuits, and it yields auto-correlations andcross-correlations for 64 antennas7 . In FDM there are always 8192 spectral points per BB per polarization, andhigher spectral resolutions can be achieved by reducing the number of sub-bands (i.e. bandwidth) used to form
an spw. It is possible to set different modes in different quadrants (i.e. BBs); for example, while one BB is set
in TDM, other BBs can be set in FDM. For spectral setup details, see Chapter 6. The Long Term Accumulator(LTA; see Figure 5.1) takes short 1 ms or 16 ms integrations from the correlator circuits and provides longer
term integration. Further time averaging through multiple dump intervals is performed in the Correlator Data
Processor (CDP) computers. See also Section 5.5.3 about time resolution. Section 5.5 describes in detail thecorrelator data processing.

5.2

The ACA Correlator

The ACA Correlator is dedicated to observations with the Atacama Compact Array that consists of the 7m Array with twelve 7 m antennas and the Total Power Array (TP Array) with four 12 m antennas. The
ACA Correlator is based on the FX8 design in which the incoming time-domain data stream is converted intofrequency-domain spectrum via an FFT (Fast Fourier Transform) module before cross multiplication to form
the power spectrum. The FFT part always accepts a full 2 GHz bandwidth and outputs 524288 channel spectrawith a frequency resolution of 3.815 kHz. This design enables flexible spectral handling as shown in Figure 5.6
producing multiple spws with different channel spacings by averaging multiple channels (spectral binning). Since
the spectral resolution function is different from that of the 64-input Correlator, a frequency profile synthesis(FPS) is performed in the Correlator Data Processor computer so that the outputs of both correlators arematched (Kamazaki et al. 2008, ALMA Memo 580).
A detailed diagram of the signal processing in the ACA Correlator itself is shown in Figure 5.3. Similar to
the 64-input Correlator, each quadrant of the ACA Correlator processes a BB pair; so the complete system canprocess up to sixteen antennas independently from the 64-input Correlator.
After receiving the digitized BB signals in the Digital Transmission System Receiver (DTS-Rx), the DTSRx and FFT Processor (DFP) modules compensate for geometrical delays between antennas and perform the
220 -point FFT that produces a 219 -point complex spectrum9 (hereafter, voltage spectrum) for every BB per
antenna, with a channel separation of 3.815 kHz (= 2 GHz ÷ 524288 channels) in a 16-bit complex integer form.
The 16-bit complex voltage spectra are re-quantized into a 4-bit complex integer and sent to the Correlation
and Integration Processor (CIP) modules.
The CIP module trims the required frequency range and multiplies the antenna-based voltage spectra to
generate baseline-based cross power spectra that correspond to cross-correlations. Antenna-based power spectra,
corresponding to auto-correlation, are also generated in the same way. Cross-polarization power spectra can be
optionally produced. The (cross) power spectra are channel-averaged and time-integrated as designated before
they are sent to the ACA-CDP computers in the Computing subsystem through optical fibers.
The ACA-CDP performs further spectral processing such as non-linearity correction (see Section 5.6.2), FPS
and temporal integration, before data are sent to the archive.
The overall hardware design of the ACA Correlator is shown in Figure 5.5. The ACA Correlator is equippedwith high-speed FPGA chips rather than Application Specific Integrated Circuit (ASIC) chips used in the
7 2016 cross-correlations (real and imaginary) and 64 auto-correlations (real) totals 4096 real correlations.
8 F and X stand for Fourier transform and correlation, respectively.
9 220 -point FFT produces a 220 -point complex voltage spectrum of a double sideband including the image sideband that will bediscarded.

5.2. THE ACA CORRELATOR

63

Figure 5.3: Block diagram of the ACA Correlator. One of four quadrants is shown. Time-series data from eachantenna are divided in the time domain and processed in an 8-way parallel stream. FFT is performed in an
FPGA delivering signals in the spectral domain which are then multiplied. The auto and cross-correlation data
are then accumulated in time, and the parallel streams averaged together in the Correlation and Integration
Processor (CIP) module. The correlated spectra are then fed to the ACA-CDP for further accumulation andprocessing.

64

CHAPTER 5. THE CORRELATORS

Figure 5.4: Two quadrants of the ALMA Compact Array (ACA) correlator installed in the ACA correlator
room. Credit : ALMA (ESO/NAOJ/NRAO), S. Okumura
64-input Correlator. For technical detail, see Kamazaki et al. 2012, PASJ 64, 29.

5.2.1

The 7-m Array

The 7-m Array consists of twelve 7 m antennas whose correlation is performed in the ACA Correlator. The
purpose of the 7-m Array is to cover low spatial frequencies in the (u, v) plane and to enhance the image fidelity
in extended sources. Since the visibilities of the 7-m Array will usually be combined with those of the mainarray, these visibilities must be homogenized in terms of amplitude, phase, and spectral specifications. Whileamplitude and phase calibrations refer to standard flux and phase calibrators offline, the spectral profile will bematched via FPS in the CDP online processing.

5.2.2

The Total Power Array

The TP (Total Power) Array consists of four 12 m antennas in single-dish observation mode, for the purposeof obtaining zero-spacing visibilities to recover the spatially-integrated flux densities that are not obtained withcross-correlations. In the TP Array observations, the ACA Correlator generates only parallel polarization autocorrelations of XX and Y Y for Cycle 5. Cross-polarization products are not taken in Cycle 5. Single-dishdedicated observing modes such as position switching, raster scan, and OTF will be performed with the TP
Array. Fast switching (∼ 10 Hz) using the nutating subreflector will not be available during Cycle 5.

5.3

Digitizers

A digitizer is a device converting at discrete times continuous voltage waveforms into quantized voltage levels
encoded in a digital format. The ALMA digitizers are located in the antenna back ends (BEs) where they
convert BB signals into the ALMA digital format (Recoquillon et al. 2005, ALMA Memo No. 532). The Digital
Transmitter (DTX) on the BE transfers the digital signals through optical fibers to the data receivers (DRXs)
in the correlators.

5.3. DIGITIZERS

65

Figure 5.5: Overview diagram of the ACA Correlator. The signals from the BackEnd Subsystem are processedin the DFP and CIP modules and output to the Computing Subsystem (see text and Figure 5.3 for details ofthese). The modules are controlled by the Monitor and Control Interface (MCI), which communicates with thecorrelator control computer (ACA-CCC). The DTS-Rx is connected with the monitor and control computer(ACA-DMC) for the monitor and control compatibility with the 64-input Correlator.

Figure 5.6: Data capture sequence of the ACA Correlator. The design enables output with multiple spws withdifferent channel spacings by averaging multiple channels (spectral binning). The frequency range of an spw isselectable from the 524288-point (512K) spectra across 2 GHz bandwidth.

66

CHAPTER 5. THE CORRELATORS

Each antenna BE is equipped with 8 digitizers to accept 8 signal streams of 4 BBs × 2 polarizations.
To sample and quantize the 2-4 GHz BB signals, the ALMA digitizer samples at the Nyquist frequency of
4 GHz and uses 8 quantization voltage levels (3-bit per sample). However, the 64-input Correlator reduces
the quantization levels to 4 (2-bit). Signals through the TFBs are re-quantized in 4-bit before the correlation
process. The ACA Correlator handles 3-bit digital form in FFT and the spectrum is requantized in 4-bit before
cross multiplication. These quantization processes affect the sensitivity and linearity in the power spectra.
Compared to an ideal analog system, the 64-input correlator has a sensitivity loss of 12% (TDM) or 15.5%(FDM) due to the quantization including re-quantization. Similarly the ACA Correlator has a 4.8% sensitivity
loss. These numbers suppose that the digitizer input power is in the expected range and that the digitizer
adjustments are optimal. See also Section 5.6.1 about the quantization loss.

5.4

Online WVR Correction

The Water Vapor Radiometer (WVR; see Appendix A.6 for technical description) is a device mounted on each of
the 12 m antennas to measure the amount of Precipitable Water Vapor (PWV) in order to correct for pathlength
fluctuations in the troposphere. The WVR data are recorded together with the uncorrected visibilities, andin Cycle 5 (as in previous cycles), the WVR corrections are made offline in CASA. However, the CDP of the
64-input Correlator can also apply a realtime correction of the path length fluctuation for each dump duration(online correction). This online corrected data is currently used for QA0 checks whenever possible. Recording
both WVR corrected and uncorrected results impacts data rate and storage, and it needs to be dealt with bymeans of longer integration time.
The WVR correction will not be applied in the ACA Correlator because the array is so compact that PWVfluctuation is not significant.

5.5

Capabilities of the Correlators

5.5.1

Polarization

Both correlators offer polarimetry capability by delivering all correlation products of hXX ∗ i, hXY ∗ i, hY X ∗ i,and hY Y ∗ i where X and Y stand for two linear orthogonal polarization components. These correlations relate
to the Stokes visibilities of I, Q, U , and V as





hXX ∗ i /(GX G∗X )
1
0
0
1
I
 Q  1  cos 2ψ − sin 2ψ − sin 2ψ − cos 2ψ   hXY ∗ i /(GX G∗ ) 
Y
,




(5.1)
 U  = 2  sin 2ψ
cos 2ψ
cos 2ψ
− sin 2ψ   hY X ∗ i /(GY G∗X ) 
hY Y ∗ i /(GY G∗Y )
0
−i
i
0
V
where GX and GY stand for complex antenna-based gains in X and Y polarizations and ψ is the parallactic
angle. This formulation doesn’t include cross talk, also known as ‘D-terms’, whose calibration will be discussed
in Chapter 10.
The 64-input Correlator forms cross-polarization products of hXY ∗ i and hY X ∗ i only when polarimetry is
required. This is obtained at the expense of less spectral channels. Although the ACA Correlator is capable ofpolarimetry, the cross-polarization products of the 7-m Array or the TP Array observations will not be offered
for Cycle 5.

5.5.2

Spectral Setup

Both correlators are capable of accepting eight 2 GHz bandwidth signal streams consisting of four BBs and twopolarizations, and to output multiple spws within the bandwidths.

67

5.5. CAPABILITIES OF THE CORRELATORS

Each spw yields a continuous spectrum composed of uniformly spaced spectral channels. Table 5.1 summarizes the maximum number of spectral channels and the channel spacing of the correlators in dual linear
polarization mode (XX and Y Y ). The maximum number of channels per spw would by doubled (and the channel spacing halved) for single polarization (XX) observations. Conversely, for full polarization observations(XX, XY , Y X, and Y Y ), the maximum number of channels is halved and the channel spacing correspondingly doubled as compared to Table 5.1. The bandwidth and the number of channels available from the ACA
correlator are identical through the application of FPS (Frequency Profile Synthesis). Note that the channel
spacing is not the same as the spectral resolution because of the effects of the applied weighting function, as
listed in Table 5.2 and shown in Figure 5.7. See also Chapter 6 about multiple-spw setup.
Correlator/ ModeBandwidth(MHz)

Num. of ch.
(dual pol.)Ch. spacing(MHz)

Weighting

FWHM
(ch)

Max
sidelobe

BLC/TDM
BLC/FDM
BLC/FDM
BLC/FDM
BLC/FDM
BLC/FDM
BLC/FDM
ACA
ACA
ACA
ACA
ACA
ACA

2000∗
1875
938
469
234
117
58.6
2000∗
1000
500
250
125
62.5

128
3840
3840
3840
3840
3840
3840
4096
4096
4096
4096
4096
4096

15.625
0.488
0.244
0.122
0.061
0.03050.0153
0.488
0.244
0.122
0.061
0.03050.0153

Uniform
Hanning∗
Hamming
Bartlett
Blackmann
Welch

1.21
2.00
1.82
1.77
2.30
1.59

−0.217−0.026+0.007+0.047+0.001−0.086

Table 5.2: Spectral resolutions (FWHM) andthe maximum sidelobe levels for weighting
functions. Default is the Hanning window.

Table 5.1: Correlator modes and spectral performances per
BB for dual parallel polarization (XX and YY). ∗ Usable bandwidth excluding band edges is ∼ 1875 MHz.
The spectral profile which the correlators output is a convolution of the true spectrum with the spectral
resolution function shown in Figure 5.7. The spectral resolution function is given by Fourier transform of
the weighting function applied to the correlation function in the lag domain. The spectral resolution is often
characterized by the FWHM (full width at half maximum) of the spectral resolution function. Note that thechannel spacing in Table 5.2 is not the same as the spectral resolution, which depends on the weighting functionin the lag domain.
Uniform weighting in the lag domain results in the sinc function with the FWHM of 1.21× the channel
spacing and yields spectral sidelobes. This ‘ringing’ phenomenon affects the spectra when a narrow line, interference spike, or strong edge channels are present. Alternative weighting functions10 are applicable to suppress
the spectral sidelobes as listed in Table 5.2. Note that the sidelobes do not matter in most of astronomical
observations where a line profile spreads over several spectral channels. The choice of a weighting function isa trade off between resolutions and sidelobes. The default weighting function is the Hanning function, which
gives the spectral resolution of 2 × the channel spacing and the maximum sidelobe level of −2.6%. If a different
weighting function is required in a specific science goal, the proposer should justify it in the technical case, andselect the setup in the Phase 2 SB.
Spectral channel averaging is available to bin or average spectral channels in the CDP. Channels can beaveraged together; factors of N = 2, 4, 8, or 16 are available. The main purpose is to reduce the data rate
to the archive and the total data volume. It provides a broader spread of correlator functionality between thecurrent TDM (which has only 128 channels in dual polarization) and full FDM (with 3840 channels in dual
polarization mode). It might be quite acceptable for those who need something with more resolution than TDM,
but where the FDM channels at the full resolution are unnecessary. Table 5.3 shows the resolutions (in kHz)
10 For a full description, see http://mathworld.wolfram.com/ApodizationFunction.html.

68

0.6

Uniform
Hanning
Hamming
Bartlett
Blackmann
Welch

0.2

0.4

half maximum

-0.2

0.0

Spectral Response

0.8

1.0

CHAPTER 5. THE CORRELATORS

-3

-2

-1

0

1

2

3

Frequency [channel]

Figure 5.7: Spectral resolution functions corresponding to various weighting functions

for different values of N , using Hanning weighting, in the different bandwidth modes. The channel spacings arein parentheses. In Cycle 5, the default value is N = 2.
Usablebandwidth
(MHz)
1875
937.5
468.8
234.4
117.2
58.6

N=
Channels =Spectral resolution (channel spacing) [kHz]
1
2∗
4
8
3840
1920
960
480
977 (488)
488 (244)
244 (122)
122 (61)
61 (31)31 (15)1129 (977)564 (488)
282 (244)
141 (122)
71 (61)35 (31)

1938 (1953)
969 (977)
485 (488)
242 (244)
121 (122)
61 (61)3904 (3096)
1952 (1953)
976 (977)
488 (488)
244 (244)
122 (122)

16
240
7813 (7812)
3906 (3906)
1953 (1953)
977 (977)
488 (488)
244 (244)

Table 5.3: Spectral resolution and channel spacing (in parentheses) in kHz for different correlator bandwidthmodes (left column) and for different spectral channel averaging factors (columns, N = 1 to 16), using Hanningsmoothing. The number of channels can be reduced from 3840 (for the unaveraged case, N = 1) down to 240(for N = 16). As N increases, the spectral resolution functions of adjoining channels are combined and thenthe spectral resolution approaches the channel spacing. Values are given for the 2 polarization case. For Cycle
5 the default value for spectral averaging will be 2.
Note that the default Hanning window function gives a resolution 2 times the channel spacing, so using
N = 2 (cutting the number of spectral channels from 3840 to 1920) results in negligible loss of final resolution.
It is recommended that unless the maximum spectral resolution is required by the observations, to reduce thenumber of channels when feasible. This is selected in Phase 2 of the SB creation. However, note that this isa non-reversible operation. For Cycle 5 the default value for spectral averaging will be 2. The proposer mustspecifically request and justify the use of N = 1 for spectral averaging.
The ACA Correlator is an FX correlator where the uniform weighting in the FFT segment is equivalent to
the Bartlett weighting in the lag domain. FPS in the CDP can be applied to match the spectral resolutionfunction to that of the 64-input Correlator. The bandwidth and the number of channels in the ACA correlator
remain unchanged through FPS since Cycle 4.

5.5. CAPABILITIES OF THE CORRELATORS

5.5.3

69

Time Resolution

As shown in Figure 5.8 there are three stages where correlated data are accumulated or averaged within acorrelator sub-system:
1. Accumulator#1: implemented in the correlator itself. Data are accumulated without applying a proper
averaging factor. The accumulation period is called dump duration.
2. Accumulator#2: implemented in the CDP, this stage first truncates ∼ 5% band edges for each spw andthen averages the whole spectral channels into one. Those channel averages are then further averaged intime during a number of dump duration periods. This average period is called channel average duration,
which must be an integer multiple of the dump duration.
3. Accumulator#3: implemented in the CDP, this stage averages full resolution spectra during a number ofof dump duration periods. This average period is called integration duration, which must be an integer
multiple of the channel average duration. This also outputs WVR-corrected spectral data, after applying
WVR correction, for archives.
Most of the data produced by the correlator corresponds to full resolution spectra, and its data rate can beapproximated by the following expression:2
Rint = Nant
× NBB × Nch × Nbyte /Tint , (bytes/sec)(5.2)

where Nant , NBB , Nch are the number of antennas, BBs, and total number of spectral channels (for 1, 2, or 4
polarization products), respectively. Nbyte (bytes/visibility) is the byte size of the real or imaginary part of avisibility, and Tint is the integration duration in the Accumulator#3. For example, an array configuration with
Nant = 42, a spectral setup with NBB = 4, Nch = 3840 × 2 polarization products (XX and Y Y ), Tint = 6 sec,
and assuming Nbyte = 2 yields a data rate of 18.1 MB/sec.
In Cycle 5, ALMA regulates Rint at 40 MB/sec. The ALMA Observing Tool (OT) estimates the data rate
for each science goal and warns if it exceeds the limit. In this case, it is required to consider the optimal
trade between time and spectral resolutions, number of polarization products, number of BBs, and number ofantennas in the array.
Some specific considerations about different time duration follows:• Integration duration of spectral data with the 64-input Correlator
The basic integration time of the 64-antenna Correlator is 16 and 1 ms for cross- and auto-correlation,
respectively. The correlator integration duration can be, in TDM and FDM, any value that would keep
the integration data rate Rint under the regulated limit for a given science cycle. Note that the 64input Correlator sets Nbyte in real-time, based on the actual magnitude of the data produced (correlation
regime). For validation purposes, and only in FDM, a favorable condition of Nbyte = 2 is assumed.
• Integration duration of spectral data with the ACA Correlator
The ACA Correlator uses Nbyte = 4 and its dump time is a multiple of 1 ms and 16 ms for autocorrelationand cross-correlation, respectively. The maximum data rate from the ACA Correlator is 3.6 MB/s,
independently of the number of antennas. However, the average data rate to the archive will be lower
during typical observing modes, because of overheads and the use of TDM in calibration scans.
• Channel-averaged duration
The average power spectra across the whole bandwidth, in each spw, can be recorded in an independent
spw consiting of only one spectral channel. This single channel spw, without bandpass calibration, is not
used for astronomy, but for recording phase and amplitude variations through the observing time. Its
duration should normally be equal to or shorter than the WVR integration duration.

70

CHAPTER 5. THE CORRELATORS• Integration duration of online WVR Correction
If online WVR corrections are requested by a given spectral configuration, then the integration duration
Tint must be equal to or longer than that of the WVR system (1.152 sec). Given that for Cycle 5 neither
the 7-m Array nor the TP Array uses online WVR, the above restriction applies to the 64-input correlator
only.
A pulsar gating function is not implemented in the ALMA correlators. Timing sensitive analysis must
be taken offline under the time resolution limited by the actual integration duration, Tint , used during anobservation.

5.5.4

Phase Switching

The 180◦ phase switching capability is implemented to suppress spurious signals and IF cross talks between the
LO1 and the digitizers11 . Starting with Cycle 5, a new capability has been introduced to separate, in real-time,
upper and lower sidebands of DSB receivers (Bands 9 and 10). The expedient is based on 90◦ phase switchingat the LO1, and accumulation in different memory areas (bins) in the correlator12 . Walsh function series are
employed to make antenna-based switching patterns orthogonal to each other. The Walsh sequences permutes
every 16 ms, and the full cycle completes after 2048 ms to achieve orthogonality for all antennas in the array.
The dump duration, during a side band-separation observation, must be an integer number of the complete
Walsh cycle. See also Appendix B.4.3.

The 180◦ phase switchingThis function was already applied before Cycle 4. The phase switching capability (see principles in Figure 5.9)
is realized by phase modulation in the LO1 and demodulation in the DTS transmitter module after digitization.
State

Ant.

LO phase

IF signal

Demod.

1
2

φLO
φLO

−iφLO

0
1

S1 e
+N
S2 e−iφLO + N

00hS1 · S2∗ i + hN · N ∗ i

1
2

φLO
φLO + πS1 e−iφLO + N
S2 e−i(φLO +π) + N

0πhS1 · S2∗ i − hN · N ∗ iaverage

Cross Corr.

hS1 · S2∗ i

Table 5.4: Cross correlation of a baseline under 180◦ phase switching. The received signal of antenna 2, S2 , ismodulated by 180◦ by the LO1 and demodulated in the DTS transmitter module at each antenna. Spurious
signals, N , in the IF or cross talks are not modulated via the LO1 and thus are canceled via demodulation andaccumulation of data in states 0 and 1.

The 90◦ phase switchingThis function aims to separate USB and LSB for the DSB receivers of Bands 9 and 10. When the LO phase ofantenna 2 is offset by 90◦ , the phases of USB and LSB signals in IF will be −φLO − π2 and φLO + π2 , respectively.
The 90◦ -demodulation is taken by swapping real and imaginary parts of the cross correlations in the CDP.
After demodulation, the sign of LSB correlation will be inverted with respect to USB. Thus, the average andthe difference of cross correlations in two states gives the USB and the LSB visibilities, respectively.
11 Note that this scheme doesn’t work for autocorrelations.
12 See Thompson, Moran, and Swenson, “Interferometry and Synthesis in Radio Astronomy (2nd edition)”, §6.1 and §7.5.

71

5.5. CAPABILITIES OF THE CORRELATORSCorrelator
Accumulator#1

WVR data
every 1.15 second

Transfer data
every dump time

CDP
Accumulator#2
Truncate channels,
take average

WVR correction

Accumulator#3

BDF

BDF

Transfer data every
channel-average duration

Transfer data every
integration duration

Transfer data every
integration duration

Channel-averaged data

BDF

Spectral data

WVR-corrected spectral data

Archive

WVR data

Figure 5.8: Basic data processing and accumulation/averaging steps between the correlator and archive. The
CDP applies channel truncation, spectral averaging, and time averaging for the channel-averaged data. It also
applies online WVR correction for the WVR-corrected spectral data. They are packed in Binary Data Format(BDF) and are archived together with the WVR data.

Walsh series
S1

mod

LO

mod

S2

corr
demod

demod
accum

Figure 5.9: Schematic diagram of phase switching. The LO1 signal phase is modulated with the the Walshseries pattern and demodulated in the DTS before cross correlation. The Walsh function series are employed
to generate switching patterns that are orthogonal to each other.
State

Ant.

LO phase

0

1
2

φLO
φLO

1

1
2

φLO
φLO + π2(State 0 + State 1)/2
(State 0 − State 1)/2

IF signal

Demod.

S1,U e+ S1,L e
S2,U e−iφLO + S2,L eiφLO

00S1,U e−iφLO + S1,L eiφLOπ
π
S2,U e−i(φLO + 2 ) + S2,L ei(φLO + 2 )

0

−iφLO

iφLO

π
2

Cross Corr.
∗∗
S1,U · S2,U
+ S1,L · S2,L∗∗
S1,U · S2,U
− S1,L · S2,L∗
S1,U · S2,U∗
S1,L · S2,L

Table 5.5: Cross correlation of a baseline under 90◦ phase switching. The suffixes of 1, 2, U, L stand for antenna 1
and 2, and USB and LSB, respectively. The LO phase of antenna 2 is modulated by 90◦ . After 90◦ -demodulationand correlation, the cross correlations of USB and LSB have opposite signs. Thus, the average and the differenceof cross correlations in two states gives the USB and the LSB visibilities, respectively.

72

CHAPTER 5. THE CORRELATORS

5.6

Practical Performance

5.6.1

Sensitivity

A digitizer adds quantization noise to its input analog signal, with a consequent signal-to-noise reduction or
sensitivity loss. The ALMA digitizer employs 3-bit (8-level) quantization13 , and additional re-quantization
processes are applied in the correlators.
In Cycle 5, the 64-input Correlator TDM mode makes use of 2-bit quantization that yields a quantization
efficiency of ηQ = 0.88. In the FDM case, digital filtering is applied to 3-bit quantized signals followed by 2-bit
re-quantization. The two stages of quantization would cause the net quantization efficiency of ηQ = 0.96×0.88 =0.85 if they were independent (see mode chart tables of Escoffier et al., ALMA Memo 556), nevertheless, thereal efficiency can be slightly better than the multiplication (Iguchi et al. 2005, PASJ 57, 259)14 .
The ACA Correlator feeds 3-bit quantized signals into the FFT processors where butterfly arithmetic is
performed with 16-bit precision. The FFT output spectrum is re-quantized into 4-bit (16 levels) before crossmultiplication. The combination of these quantizations results in a loss of 4.8% (i.e. ηQ = 0.952; Kamazaki etal. 2012, PASJ 64, 29).
The quantization efficiencies above are theoretical values under optimal conditions of the input signal level
and threshold voltages. Although the signal level is adjusted for every scan, significant variation of power level(e.g. observation of strong sources, unstable weather, or a frequency band near atmospheric absorption lines)
can violate the conditions required to optimize the quantization efficiency.

5.6.2

Linearity

Digital quantization also causes non-linearity in the visibility measurements. The relationship between thecorrelation coefficient of quantized signals with that obtained for analog signals (i.e. infinite quantization levels)
is known as the Van Vleck relationship, which is used for the non-linearity correction.
Figure 5.10 shows the Van Vleck relationships in 2-, 3-, and 4-bit quantizations. The correlation coefficientsof quantized signals keep adequate linearity for small correlation coefficients15 . This indicates that for mostsources the cross-correlation response is effectively linear.
However, auto-correlations are affected by the non-linearity because the correlation coefficient at zero lagmust be unity by definition. The non-linearity in auto-correlation power spectra influences system temperature
measurements and the TP Array observations. In both correlators, the CDPs measure total power of digitizedsignals and determine the Van Vleck relationship to correct the (cross) power spectra.

5.7

Final data product - the ASDM

The final product from each observation in the archive is known as the ASDM (the ALMA Science Data
Model), each of which has an unique hexadecimal name (e.g. uid://A002/X2fed6/X3f). The ASDM contains
the metadata (headers, descriptions of the observation setup, ancillary data, etc), and the binary data (the raw
data itself), and is described in more detail in Section 12.2. The following describes the spectral data in the
ASDM and how it related to the correlator output.
In the ASDM, the binary data are saved in a structure of spws. All of the data in a single spw must
share the same frequency setup, including the number and width of spectral channels, and the integration
time. The observed spws will be a combination of the science spectral windows set up by the proposers in
13 The quantization efficiency would be η = 0.96 if optimal signal levels, threshold voltages, and perfect signal processing wereQ
performed (Thompson 1998, MMA Memo 220).
14 It is reported that the combination of 2-bit quantization, digital filtering, and 2-bit re-quantization yields η
Q = 0.81, better
than 0.88 × 0.88 = 0.77.
15 The departure from linear relation is δρ/ρ < 10−3 for ρ < 0.2

73

5.7. FINAL DATA PRODUCT - THE ASDM

Optimal Threshold Level
0.12

1.0

Optimal Threshold Level

0.08
0.06
0.04

Departure from Linear Relation

0.0

0.00

0.02

0.8
0.6
0.4
0.2

Digital Correlation Coefficient

2−bit
3−bit
4−bit

0.10

2−bit
3−bit
4−bit

0.0

0.2

0.4

0.6

Analog Correlation Coefficient

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

Analog Correlation Coefficient

Figure 5.10: Van Vleck relationship of 2-, 3-, and 4-bit quantizations at the optimal signal power level andthreshold voltages. (Left): Correlation coefficient of digitized signals as a function of analog correlation coefficients, ρ. (Right): Departures of the Van Vleck relationship from linear relation using the single factors ofη4 = 0.881, η8 = 0.963, and η16 = 0.988 for 2-, 3-, and 4-bit quantizations, respectively.
Phase 1 of the OT, and additional spws from observations needed for calibration (pointing, and sometimes
system temperature) set up during Phase 2. Additionally, the WVR data are stored in a spectral window
with 4 channels around the water line at 183 GHz. In the ASDM, except for the WVR spectral window, eachrequested spectral window maps into two output spws in the data: one with the requested dimensions of N
channels per polarization product (for example 128 or 3840), and a second channel averaged version with one
channel per polarization product (this averaging is done in the correlator). The channel averaged data are usedby the online telescope calibration system (TELCAL) and for realtime diagnostic purposes (QuickLook), andare typically not used downstream in the data reduction. Overall, this can lead to ASDMs with a large numberof spectral windows. For example, a typical science observation in FDM mode can have more than 25 spectral
windows. Every scan/spw combination has an “intent” associated with it that indicates its purpose (pointing,system temperature, science, etc). The intent can be used in CASA to decode how to utilize each spectral
window in the data reduction process.

74

CHAPTER 5. THE CORRELATORSChapter 6

Spectral Setups
This chapter describes the frequency setup of ALMA. In particular it shows how spectral setups are defined fromthe user viewpoint and how these then set up the ALMA hardware. It summarises the functions and operationof the local oscillator (LO) and Intermediate Frequency (IF) systems, as well as outlining some of the otherpoints pertaining to the frequency setup. For those interested in more details of the LO and IF components
and how the hardware works, please jump to Appendix B. The main changes for Cycle 5 are the addition of
the Band 5 spectral coverage, and the inclusion of 90-degree phase switching.
To the ALMA system, a spectral setup includes the hardware LO, IF and correlator settings, such that eachSpectral Window (spw) covers the desired lines and/or continuum frequencies. To the end-user, however, thespectral setup is normally defined in the Observing Tool (OT) just in terms of the desired lines or observing
frequencies, spectral window bandwidths and spectral resolutions: there is no need for the user to worry about
the details of each hardware setting. For full details of the OT and how to use it, see the user manual andreference manuals, available from the ALMA website1 (and also in the OT itself). In this chapter, we try toreconcile these two viewpoints.

6.1

Introduction

ALMA uses two stages of heterodyne conversion to shift the signals from the sky or observing frequency down
to a range where electronics can be used to perform the digital sampling and cross-correlations. In general, thesignals of observing frequency fsig are mixed to IF signals of frequency fIF using a narrow Local Oscillator
signal (LO, at fLO ). fIF is the difference frequency between fLO and fsig , where fIF is always, for ALMA,
much lower than fsig . The output signal is split into two separate sidebands at frequencies offset from fLO ,known as the upper and lower sideband (USB or LSB) .
Figure 6.1 illustrates the ALMA signal path and basic principle of operation. The first heterodyne stage
uses the SIS mixer and LO1 to mix (or downconvert) the astronomical signal to 4 GHz- to 8 GHz-wide IF
bands, giving both USB and LSB. Up to four 2 GHz wide Basebands (or BBs) can be placed in the available
IF range in either or both the USB or LSB IFs using the second stage of downconversion. Within each of thesebasebands it is possible to place up to four Spectral Windows. Each spw forms a final contiguous spectrum,with bandwidths from 58.594 MHz up to 1.875 GHz wide (see Section 6.3).
Using the OT during both the proposal preparation (Phase 1) and scheduling block (SB) creation (Phase2), the user chooses the frequencies (or spectral lines) to be observed in each spw and their required bandwidths
or spectral resolutions. During the spectral tuning, there are effectively four different LOs set up by the system(Figure 6.1):• LO1 which sets the frontend tuning frequency. This has continuous coverage.
1 http://almascience.org/documents-and-tools/

75

76

CHAPTER 6. SPECTRAL SETUPS

Figure 6.1: Summary block diagram of ALMA signal path and LO system for one spectral window, one baseband, one polarisation. The Backend IF system is located in each antenna, and the digitised signal for eachbaseband/polarisation is fed to the correlator in the central technical building through buried optical fibers.
See Appendix B for a more detailed description of the components and the other tasks that the LO systems
perform.
• LO2 which positions the basebands within the frontend receiver IF (each baseband uses a different LO2,
hence there are four LO2s). This does not have continuous frequency coverage, as it is generated by a 125
MHz frequency comb plus a 20-42.5 MHz continuous frequency synthesizer.
• LO3 which is the clock frequency of the digitizers (fixed at 4 GHz),• LO4 (also known as the tunable filterbank LO, or TFB LO), which is a digital LO synthesized in thecorrelators allowing positioning of the spectral windows within each baseband. Each spw has effectively aseparate LO4.
The OT and the realtime system have a tuning algorithm that attempts to find the best tuning solution for
LO1, LO2 and LO4 based on the requested observing frequencies. Because the LOs themselves are generated
by combinations of frequency synthesizers, several different tuning solutions may be possible, and the algorithm
picks the best one.2 If no solution is possible, the OT will notify the user. A more detailed description of the
LO operation is given in Appendix B.2.
Cycle 5 has similar restrictions on the spectral setups and tuning as Cycle 4 (see Table 6.2 in Section 6.8).
2 Note that with tuning setups having multiple basebands, only the hardware LO1 and LO2, the requested frequencies may notappear in exactly the center channel in all the spws, because of the non-continuous coverage of LO2. Normally the tuning algorithm
will use LO4 to compensate for this and re-center the lines. However in the widest bandwidth modes (FDM 1875 MHz and TDM)
the spws cannot be shifted using LO4. Then the sum of the absolute frequency offsets in all basebands can be as much as 26.38
MHz for 4-baseband setups, giving a worst-case average baseband offset of 6.6 MHz; this is considered small compared with the
bandwidth (and the frequency labelling will still be correct). See section B.2 and “ALMA LO System Setup Algorithms” (Scott,2009) for more details.

77

6.2. FREQUENCY DEFINITIONS

The main limits are that the edges of the 2 GHz-wide basebands and cannot lie outside the receiver tuning
range listed in Table 4.1, and the edges of the (untruncated) spectral windows cannot lie outside the 2 GHz-wide
basebands. The settings of each baseband in the correlator are independent, so the bandwidth, resolution andcorrelator mode as well as the value of LO4 can be different for each baseband. For example, it is possible tohave a 58 MHz-wide spw centered on a particular line in baseband 1, and simultaneously use a broadband time
division multiplexing mode (or TDM mode - see correlator chapter) for all the other basebands. It is possible tohave multiple FDM spectral windows within each baseband, described in Section 6.3.2 below; however, currently
the underlying resolution of all spws within the same baseband has to be equal. The spectral setups of the ACA
Correlator and the 64-input Correlator are - to the end user - effectively the same, with the ACA Correlator
having the same allowable spectral functions as the 64-input Correlator.

6.2

Frequency Definitions

There are several frequency definitions used in the ALMA system, in the OT Phase 1 and Phase 2. Most
important to the user are:Center Frequency (Rest) (fSP W ) This is set by the user in the OT Phase 1, and is the central frequencyof the spw in the requested rest frame of the source. Note that the source rest frame is selectable, but iscommonly set to the local kinematic standard of rest (LSRK), which is the conventional local standard ofrest based on the average motion of the Sun with respect to the solar neighborhood (see Section 6.7).
Center Frequency (Sky) This is seen in the OT Phase 1, and is the actual central frequency of the spw inthe local ALMA (i.e. sky) velocity frame, after including the velocity of the source. However, it does notinclude the velocity shift of the chosen coordinate frame with respect to ALMA (i.e. the extra velocity
from Earth rotation and orbit) as this is not known until actual runtime.
Baseband desired Center Frequency (fBB ) This is the frequency center of the baseband, shown in OT
Phase 2. Both the Sky and Rest Baseband center frequencies are seen. If the spws are centered on the
basebands, these will be the same as the Phase 1 Center Frequencies (above). Otherwise they can bedifferent because of the TFB LOs (see below).
Center Offset Frequency (fof f set ) Used in the OT Phase 2, this is the offset due to the TFB LO. The center
frequency of the spw, fspw , is given in terms of this and Baseband Center Frequency by:
fspw = fBB ± (fof f set − 3.0GHz)(6.1)

where the sign depends on the observing sideband.

6.3

Spectral Setups

The wide IF bandwidth and tuning ability allows for routine simultaneous imaging of multiple lines. Some
examples (with the approximate line frequencies in GHz) are shown in Table 6.1 (for a source of redshift zero).
Note that in many cases the lines will not necessarily appear in the center of the spws (for example, in the Band
6 combination given). When <4 spectral windows are required for the primary lines, the others can be set up tocover fainter lines or to observe the continuum, potentially in TDM mode. The continuum spw frequencies need
to be setup manually, and one method of doing this is described in the next section. The selection of secondarylines to be observed can be done using the OT spectral interface. In the case of continuum spws, to maximize
the sensitivity, the widest bandwidth mode should be chosen (i.e. in TDM, or 1.875 GHz in FDM - preferablywith some channel-averaging, see Section 6.4). Also the continuum spws should cover as much of the IF band as
possible. Not only will this maximize the continuum SNR on the science target, but these continuum data canbe used to improve phase and amplitude calibration. Note that there is no gain in sensitivity by overlapping
spws in frequency, since the input signal is the same in the overlap region; the OT uses the unique aggregate
bandwidth in calculating the sensitivity, taking any spw overlap into account.

78

CHAPTER 6. SPECTRAL SETUPS

6.3.1

Observing Frequencies for Continuum

For optimum sensitivity, continuum spws should be set to the frequencies with the lowest system temperature.
Because the mixer frequency responses are fairly flat, normally this corresponds to the best atmospheric transmission. For full continuum observations (without any required lines, or with only low resolution) the OT has
standard optimized frequencies for each band which are used in the OT Phase 1 when continuum is selected;
these are noted in Table 6.1 and illustrated by the red in Figure 6.2.

Figure 6.2: ALMA bands available in Cycle 5 (Bands 3 - 10), showing the frequency of the standard continuum
settings as red shading. This gives the coverage of both USB and LSB, except for Bands 9 and 10, which have
8 GHz of bandwidth using the USB only. The available frequency coverage of each band is shown by the grey
shading, and atmospheric transmission for 0.6 mm of PWV is given by the blue line.
If mixed line+continuum operation is desired, for example with a single line in BB1 observed at frequency
f (GHz), the other BBs (2-4) can be set up for continuum observing using TDM mode3 . For 2SB receivers,
normally this would have BB2 in the same sideband (offset by 2 GHz from f ) and BB3 and BB4 in the opposite
sideband (offset by the front end center IF frequency, fIF ). To maximise sensitivity the continuum BBs should
cover the maximum aggregate unique bandwidth, i.e. they should not overlap in frequency. If sb is the sign ofthe sideband of BB1 (sb = +1 for USB, sb = −1 for LSB), then the four BBs could be set up as follows:• BB1: f (BB covering the primary line)
3 Note - this case assumes one spw per BB

79

6.3. SPECTRAL SETUPS

Band/setup
3a
3b*
3c*
4a
4b
5a
5b
6a
6b*
7a
7b*
7c
8a
8b
9a
9b
10 a
10 b *-

Species/transition
Standard cont.
HCO+ 1-0
HCN 1-0
CH3 OH/H2 CO
continuum spw
CO 1-0CN
C17 O 1-0
continuum spw
continuum spw
Standard cont.
CS 3-2
DCO+ 2-1
SO2 4(2,2)-4(1,3)
H2 CO 2(0,2)-1(0,1)
Standard cont.
H2 O 3(1,3)-2(2,0)
continuum spw
H2 S 1(1,0)-1(0,1)
continuum spw
Standard cont.
12
CO 2-1
continuum spw
C18 O 2-1
13
CO 2-1
continuum spw
Standard cont.
continuum spw
12
CO 3-2
HC15 N
H13 CNHCN 4-3
HCO+ 4-3
NHD2 2(2,0)-2(1,2)
12
CO 3-2
continuum spw
13
CO 3-2
continuum spw
Standard cont.
CI 3P1-3P0
CS 10-9
continuum spw
continuum spw
Standard cont.
12
CO 6-5
CS 14-13
H2 S
C17 O 6-5
Standard cont.
CO 7-6
HCO+ 9-8
continuum spw
continuum spw

Freq. (GHz)1

97.5
89.18888.632101.293/101.333
101.3
115.271113.499112.359102.5
100.5
145.01146.969
144.077
146.605145.603
203.0
183.31
181.4
168.763170.8
233.01230.538231.6
219.560
220.399218.5
343.51343.0
345.796344.200
345.340354.505356.734
356.230
345.796344.8
330.588331.6
405.01492.160
489.751
477.5
479.5
679.0
691.472685.436687.303674.009875.0
806.652802.458805.5
803.65

Sideb.

bandwidth

dual
LSB
LSB
USB
USB
USB
USB
USB
LSB
LSB
dual
LSB
LSB
LSB
LSB
dual
USB
USB
LSB
LSB
dual
USB
USB
LSB
LSB
LSB
dual
LSB
LSB
LSB
LSB
USB
USB
USB
USB
USB
LSB
LSB
dual
USB
USB
LSB
LSB
USB
USB
USB
USB
LSB
USB
LSB
LSB
USB
USB

TDM
58 MHz58 MHz
125 MHzTDM
58 MHz58 MHz117 MHz
TDM
TDM
TDM
117 MHz117 MHz117 MHz117 MHzTDM
250 MHzTDM
250 MHz
TDM
TDM
117 MHzTDM
117 MHz117 MHz
TDM
TDM
TDM
469 MHz234 MHz234 MHz469 MHz117 MHz234 MHz58 MHzTDM
58 MHzTDM
TDM
117 MHz117 MHz
TDM
TDM
TDM
469 MHz117 MHz234 MHz469 MHzTDM
469 MHz117 MHz
TDM
TDM

BB

spw

1
2
3
4
1
1
2
3
4

1
1
1
1
1
2
1
1
1

1
2
3
4

1
1
1
1

1
2
3
4

1
1
1
1

1
2
3
3
4

1
1
1
2
1

1
2
2
2
3
4
4
1
2
3
4

1
1
2
3
1
1
2
1
1
1
1

1
2
3
4

1
1
1
1

1
2
3
4

1
1
1
1

1
2
3
4

1
1
1
1

Notes
LO1=97.5
HCO+ /HCN/H2 CO

CO/CN/C17 O

LO1=145.0
CS/DCO+

LO1=203.0

LO1=233.0
J=2-1 CO isotopes

LO1=343.5
CO/HCO+ /HCN
1/2-corr
1/4-corr
1/4-corr
1/4-corr
1/2-corr
J=3-2 CO/13 CO

LO1=405.0
CI/13 CI

LO1=671.0
CO/CS

LO1=867.0
CO/HCO+

Table 6.1: Examples of spectral setups possible in Cycle 5. This includes the standard continuum-only setups
for each band, and some multiple line/continuum configurations. Notes: 1. Frequency for standard continuum
setups are the mean observing frequency of all spws, ≈LO1 in dual-sideband (2SB) receivers, so this frequency
is not actually covered if both sidebands are used. See Figure 6.2. * Based on a template spectral setup released
with Cycle 5 version of the OT.

80

CHAPTER 6. SPECTRAL SETUPS• BB2: f − 2.0 (continuum BB in the same sideband, 2 GHz below the primary line)• BB3: f − (2.sb.fIF ) (continuum BB in the opposite sideband)• BB4: f − (2.sb.fIF ) − 2.0 (continuum BB in the opposite sideband)
where fIF is the front-end IF frequency (6.0 GHz for Bands 3, 4, 5, 7 and 8, and normally 8.0 GHz forBands 6, 9 and 10). For DSB receivers, it is common to keep all the BBs in the same sideband, so BB3 and BB4
would be at f − 4.0 GHz and f − 6.0 GHz. Note that this is an approximate rule - if possible, adjustment of thecontinuum BBs (for example, choosing whether the opposite sideband is LSB or USB) should be done using the
OT spectral display, to avoid deep atmospheric absorption features. This is particularly important at Bands 8,
9 and 10, and near the water lines around 183 GHz in Band 5 and 325 GHz in Band 7 (see Figure 6.2). Also,
if contiguous spectral coverage of the continuum is desired, the BBs should be offset by 1.875 GHz rather than
2.0 GHz as suggested above. Adding TDM spws in otherwise unused BBs (at non-overlapping frequencies) will
improve the overall sensitivity for calibration and is recommended whenever possible.

6.3.2

Multiple Spectral Windows in the Same Baseband

The system allows the capability to have up to four spws in each baseband, and each baseband can have completely different setups. This is useful for projects where several lines need to be observed simultaneously athigh spectral resolution. However, in cases where four lines or fewer are observed in total, if the full bandwidth/resolution is needed for each line and they are well-separated, it may be preferable to place each in adifferent baseband. Alternatively, in cases where the lines are close to one another, or less spectral resolution/bandwidth is acceptable, it may be better to include multiple lines in the same baseband or even in thesame spw, and use the other basebands in TDM mode to maximize the total (aggregate) bandwidth for phasecalibration. An example of this is shown in Table 6.1 for spectral setup 6 b, where both C18 O and 13 CO areobserved in the same baseband (3.1 and 3.2). Channel-averaging can be applied to each spw, which simply bins
spectral channels together in the correlator data processing (see Section 6.5).
Multiple spws per baseband does have some restrictions: each spw within the same baseband must have thesame correlator channel width (i.e. before channel-averaging)4 , and the sum of the correlator resources in eachbaseband should add up to 1.0 (or less). Given these restrictions, it is possible to set up different bandwidths
and/or different channel-average values for each spw. Multiple spws are set up in the Phase 1 OT simply byadding more spectral lines in the same baseband, and setting the spws to have a correlator fraction less than
1.0 (so for 4 spws, each has a correlator fraction of 1/4). There may be up to 4 spws per baseband, however,
the total number of spectral channels in each baseband is limited by the correlator resources. So doubling thenumber of spws in one baseband will result in half the number of channels per spw, i.e. a lower resolution.
Figure 6.3, which is adapted from the Phase 2 Spectral Editor of the Observing Tool (OT), illustrates a more
complex spectral setup with multiple spws and basebands. The lines observed are given in Table 6.1, example
7 b. In this case, the frequency of LO1 is 350.0 GHz, and the upper and lower sidebands of the Band 7 receiverare shown as green shaded areas. The four basebands, illustrated in this case by the red horizontal bars, can be
moved around, but only within the two sidebands. The spectral windows are also shown, labelled by the name ofthe primary spectral line or continuum. In this example, baseband 1 is set for a TDM spw covering the whole 2
GHz baseband for a continuum measurement, whereas in other basebands, FDM is used. Baseband 2 has three
spws with 0.56 MHz resolution and channel-average of 2; two of 234 MHz bandwidth and 1/4 of the correlator
resources per spw, and one with 469 MHz and 1/2 of the correlator resources. At the same time, in BB3 oneline is observed with 469 MHz bandwidth and 0.49 MHz resolution (with a factor of 4 channel-averaging). In
BB4, one spw has 234 MHz bandwidth and 0.28 MHz resolution (with 2 channel-average) and one spw has
117 MHz bandwidth and 0.48 MHz resolution (with 4 channel-average). Basebands (and spws) are allowed topartially overlap, although the overlapping region only counts once in the aggregate bandwidth and estimateof continuum sensitivity. So it may be preferable to observe closely-spaced lines with a single baseband (e.g.
C18 O and 13 CO in example 6 b above) or better, with a single spw, as this can free an additional TDM spw for
improved continuum sensitivity. Many combinations of spws and basebands can be set up in this way.
4 although, as before, spws in different basebands can have different channel widths

6.3. SPECTRAL SETUPS

81

Figure 6.3: Illustration of a frequency setup, based on the OT spectral display. Green areas are the IF ranges,
horizontal red bars are the 2 GHz-wide basebands (BB1-BB4), and smaller horizontal lines represent the spectral
windows (up to 3 per baseband in this example). The frequency of LO1 is shown by the central vertical line.
The blue hashed area represents the tuning range of the front end (in this case a section of Band 7), and thecurved line represents the nominal atmospheric transmission for the chosen PWV. The bandwidths of the spws
are illustrated by the widths of the horizontal lines. The lines observed are given in example 7 b in Table 6.1.

6.3.3

Spectral Setups for Lines near the Edge of the Bands

The restriction that the baseband coverage cannot fall outside the maximum or minimum tuning range of thereceiver is an issue for certain lines at the edge of the tuning range. One obvious example is the 12CO(J=1-0)line at a redshift of zero (rest frequency of 115.271 GHz). This is close to the maximum tuning range of Band 3(116.000 GHz, see Table 6.1). A setup using the wide bandwidth modes (TDM or FDM/1875 MHz) centered at
the line frequency with zero redshift will not validate in the OT, because some of the basebands will fall outside
the maximum Band 3 frequency (116.0 GHz). Narrower modes will not go over the edge and are allowed.
There are two possible solutions: If the full bandwidth is absolutely required, the center rest frequency canbe set to the closest valid frequency, resulting in an offset of the line from the spw center (in this case, set to115.0 GHz and the line will be offset by 0.271 GHz). Another solution is to choose a narrow spw bandwidth(e.g. 1 GHz or less); in this case the spw will be offset from the center of the baseband, and the line will be at
the center of the spw.

6.3.4

Spectral Setup in Bands 9 and 10: DSB Considerations and 90-degree Phase
SwitchingBands 9 and 10 use double-sideband (DSB) receivers, so the image sideband can either be suppressed using LO
offsetting (currently using LO1 and LO2), or both sidebands can simultaneously be recorded using 90-degree
phase switching. These can only be used in interferometric mode - see Section B.4.2.

82

CHAPTER 6. SPECTRAL SETUPS

Observing a single sideband
The choice of which sideband a particular baseband is configured to observe (and which sideband is suppressed)
depends only on the relative sign of the LO1 and LO2 offset. This can be arbitrarily different for different
basebands. So it is possible to set up two basebands at approximately the same LO1/LO2 frequency, butobserve one line in the upper sideband in one baseband, and another in the lower sideband using the next
baseband, just by having different signs in the LO2 offsetting. However, in this case it might be better to use
90-degree switching (see next section) to record both using the same baseband. Note that different spws in thesame baseband must have the same sideband, as image suppression uses LO2, which is common to the whole
baseband.
Observing both idebands - 90-degree switching
In Cycle 5 it is possible to double the continuum bandwidth by simultaneously recording both signal and image
sidebands from the DSB receivers using 90-degree phase switching. This is enabled by phase modulation of
LO1, with +/-90 degree demodulation in the correlator, controlled with a Walsh sequence (see Chapter 5; also
ALMA Memo 287). It has the advantage of doubling the continuum bandwidth to a nominal 16 GHz perpolarisation (2 x 2 GHz per baseband)- particularly helpful in these high-frequency bands as it can improve√the continuum sensitivity by ∼ 2 - as well as making available the lines in the opposite sideband. The actual
improvement however, depends on the atmospheric transmission in the image sideband, which in Bands 9-10
can result in image system temperatures 20% (or more) higher or lower than the signal sideband. Even though
this doubles the number of spectral windows there is no loss of correlator spectral resolution, so the correlator
data rate is doubled. This may cause correlator data rate limitations in FDM mode, which could be mitigatedby longer integration times, lowering resolution by increasing the channel-averaging factor, and/or using TDM
in the continuum-only basebands. For Cycle 5, there is a restriction that this mode can only be used with
TDM or the maximum-bandwidth (1875 MHz) FDM configuration, and the spw can only be centered on eachbaseband. It also requires that the integration duration should be a multiple of 2048 ms.

6.4

Usable Bandwidth

The IF system contains an anti-aliasing filter which limits the bandwidth of the basebands. Nominally this filter
has -1 dB points at 2.10 and 3.90 GHz, giving a maximum bandwidth of 1.8 GHz. However, the IF response issuch that the usable bandwidth is slightly wider – i.e. closer to 1.9 GHz. In FDM mode, the correlator outputs
a maximum bandwidth of 15/16 of the nominal bandwidth, and reduces the number of channels by the same
factors, from 4096 to 3840 (or 2048 to 1920 after the default channel-average factor - see correlator chapters).
So for 2 GHz nominal, the correlator outputs a bandwidth of 1.875 GHz. Thus in FDM wideband, the filters
do not truncate the spectrum, and the full available correlator bandwidth in wideband mode can be used. In
TDM the correlator outputs a bandwidth of 2.000 GHz, but typically the edges of the spectra are affected by
low power due to this filter and some ringing effects (see upper panel in Figure 6.4). It is recommended that 4(in double-polarization) or 8 (single-polarization) channels are removed or flagged manually offline. This results
in approximately the same usable bandwidth in both TDM and FDM modes and is illustrated in Figure 6.4.
Note that if the centers of two basebands are separated by 1.875 GHz it is possible to set up spws that can bejoined in data reduction to yield a contiguous 3.75 GHz spectrum.

6.5

Spectral Resolution and Channel-averaging

The spectral resolution of each spw is set by a combination of the inherent resolution/bandwidth setup in thecorrelator, the correlator weighting function (also known as the smoothing function) and the channel-averaging(also known as spectral-averaging) factor (which is carried out at a late stage of processing in the correlator).
This is described in the correlator Section 5.5.2. The default FDM setup from the OT in Cycle 5 uses Hanningsmoothing with a channel-averaging factor of 2 (see Section 5.5.2). This is changed from previous Cycles, which

6.6. SPURIOUS SIGNALS

83

Figure 6.4: Comparison of TDM (left) and FDM (right) autocorrelation bandpass showing the dropoff in total
power at the edges in the two modes. Colors represent the two polarizations from the example antenna. In
TDM, 128 channels covering 2.0 GHz bandwidth are displayed, which illustrates the drop in power in the upperand lower 4 channels due to the anti-aliasing filter. In this case the FDM spectrum has 3840 channels covering
only the central 1.875 GHz, and the drop in power at the edges of this bandwidth is negligible (and comparablewith the variations in the bandpass). (The narrow spike in the center of the FDM data is a test signal).
had a channel-average factor of 1, and has been introduced to reduce the size of the FDM datasets with negligible
loss of spectral resolution. Hanning smoothing plus a channel-average of 2 results in a spectral resolution equal
to the final channel spacing x 1.15 - only ∼15% worse than Hanning without channel-averaging but has theadvantage of halving the data rate. If the line is well resolved, with ≥3 channels covering the linewidth, thenthis will not cause a problem It is recommended to keep this default, in order to reduce the data rate and sizeof the final product; this is more critical where fast dump times are needed, e.g. for long baseline observing. If
the extra 15% resolution is required, a justification for using channel-average=1 should be made. Note that for
TDM mode, Hanning smoothing without channel-averaging (1) is the default.

6.6

Spurious Signals

Most spurious signals in the cross-correlation data are suppressed using a combination of 180-degree phasemodulation of LO1 and using different LO offsets for different antennas, both indexed with a Walsh pattern(see Section B.4.4). Not only does this effectively suppress signals generated after the front ends, but it also
improves the image sideband rejection for 2SB receivers by an additional factor of ∼20 dB. However, it does not
reduce spurious signals coming in at the observing frequency. Results from tests using these Walsh functions
show very few remaining spurious signals, and these are further reduced by the fringe tracking. However,
harmonics of the LO in the WVRs (ie 91.66, 183.32, 274.98, 366.64, 458.3 ... GHz) are very bright and cannot
be removed through these methods. These are very narrow and may require a few spectral channels to be
flagged out during data reduction. Observing lines at these frequencies should be avoided if possible.

6.7

Doppler Setting and Velocity Reference Frames

In most cases the system will be set up to provide on-line correction for the science target velocity in a particularreference frame and the Earth motion in that frame. The primary velocity reference frames recommended foruse in ALMA are:

84

CHAPTER 6. SPECTRAL SETUPS

Topocentric In this case no correction for the source or Earth motion is made. The Center Frequency (bothRest and Sky) will be identical.
Barycentric This is with respect to the center of mass of the Earth-Sun system, and is very close to theheliocentric frame.
LSRK Velocity with respect to the Kinematic local standard of rest, at 20.0 km/s−1 in the direction 18h , +30o
[B1900.0]. This frame is based on the mean velocity of the stars in the Solar neighbourhood.
If a target velocity and reference frame other than topocentric is selected in the OT, at the start of theobservation, the velocity of the science target in the chosen reference frame and the velocity of the observatory
relative to the chosen reference frame are used to set the center frequencies of the science spws5 . For example,
for a source of radial velocity 100 km/s in the LSRK frame, the difference between rest and sky frequency in
the OT will be the equivalent of 100 km/s. At runtime, the extra velocity from the Earth orbit and rotation(up to ±30.3 km/s and ±0.46 km/s), plus the motion of the LSRK (20.0 km/s toward RA=18 hrs, δ =30◦ forepoch 1900.0) will be included. This means that the LO solutions are slightly different at runtime comparedwith those from the OT, although this is normally transparent to the user6 . It is also possible to just make thecorrection for the motion of the observatory relative to the chosen reference frame, ignoring the source velocity
in that frame. The frequency setting for the science target will normally also be used in the same execution forboth the bandpass and amplitude calibration.
For sources with an external ephemeris file, the rate of change of distance between the target and theobservatory taken from the ephemeris is used to compute the source velocity at the start of the execution. Thisvelocity is used throughout the observation (like non-ephemeris observations, the velocity from the ephemeris
is not updated). Combining executions with different velocities must be done in CASA offline.
The user can specify either the velocity or the redshift of the target. Note that velocities can be defined inthree different ways, resulting in different conversions to frequency. These differences only become significant
at high velocities. The velocity formulae are:Radio v = c(fo − f )/fo . This is the default.
Optical v = c(fo − f )/f
Relativistic v = c(fo2 − f 2 )/(fo2 + f 2 ).
In these equations, v is the source velocity, and f and fo are the observed and the rest frequencies of theline. If a redshift z is specified, the conversion to frequency uses z = (fo − f )/f . For further details, see theKnowledgebase article “What are the frequency reference frames in CASA?"

6.8

Limitations and Rules for Spectral Setups in Cycle 5

The correlators already allow for a broad flexibility of spws in a single observation, however, the full capabilities
are gradually being introduced and tested by the observatory before release. The current rules for spectral
setups are given in Table 6.2.

5 Note that ALMA does not do Doppler tracking, where the frequency would be continuously updated for Earth motion during
the observation. Doppler corrections are only set once at the start of each execution. Compensation for the small changes during
an observation (<0.1 km/s for an execution lasting 2 hours) are made during CASA offline reduction.
6 The system allows for a small (< 1 MHz at Band 6) overhang of the spectral windows outside the 2 GHz-wide basebands atruntime, to allow for the very slightly different Doppler corrections in different spws, which will shift the spws with respect to one
another.

6.8. LIMITATIONS AND RULES FOR SPECTRAL SETUPS IN CYCLE 5

Rule

Description

1.
2.

LO1 must lie within the LO tuning ranges given in Table 6.1.
No part of the 2.0 GHz-wide basebands can extend over the edge of the IF passband. So,
the baseband centers cannot be closer than 1.0 GHz to the IF passband edge. For example,
with a 4.0-8.0 GHz IF range, the baseband center frequency must lie between 5.0-7.0 GHz.
The system actually does allow a small extension of the edges of the basebands over the
IF edges, to cope with the differential Doppler shifts in the different basebands, but this issmall (< 1 MHz at Band 6) and is transparent to the OT user (see Section 6.7).
For 2SB receivers (Bands 3-8), the number of basebands in one sideband can only be 0, 1,
2 or 4 (i.e. not 3). For DSB receivers (Bands 9 and 10), there is no such restriction (thenumber can be 0, 1, 2, 3 or 4).
For > 2 basebands, BB1 and BB2 should be in the same sideband, as should BB3 andBB4.
No part of the full nominal bandwidth of the spw can extend over the edge of the 2
GHz-wide baseband. For a mode with nominal bandwidth B (e.g. 62.5 MHz), that means
the spw center IF frequency (a.k.a. Center Offset Frequency in the OT, Phase 2) must be>(2000+B/2) and <(4000-B/2) MHz. The current version of the OT forces this restriction.
For 2 GHz FDM and TDM modes, this means that the spw must be at the center of thebaseband. However there is a further restriction on this, as noted in the next rule.
The spw usable bandwidth (ie 15/16 of the nominal spw bandwidth of a multiple of 62.5
MHz) should be in an allowed region of the baseband. This is in addition to (5). In practicethis means that the required range of the spw should normally be inside the range ∼2050- 3950 MHz (i.e. >50 MHz from the edges of the 2-4 GHz second IF) to ensure that theedge of the anti-aliasing filter does not significantly affect the IF power. In practice it ispossible to extend some fraction of the spw to <50 MHz of the IF edges; this is necessary
for the Band 6 setup 6 b in Table 6.1, where the 12 CO and 13 CO lines are only 70 MHz
from the IF band edges.
The line frequency does not need to be in the center of the spw in Phase 1 of the OT: if aline like 12 CO 1-0 is requested, it will generate an SB with the correct TFB LO offset, aslong as rule 5 is obeyed (which may require using a narrower spw). This is mentioned in
more detail in Section 6.2
Only 2-bit, Nyquist sampling is allowed in the correlator.
It is possible to have multiple targets with different redshifts within the same Science Goalin the OT. For SGs including sources with more than one redshift, all the observations
must be achievable using five or fewer tunings within the same receiver band, considering
the source redshifts and, in the case of spectral lines, the line widths and configuration ofspectral windows.
The number of spws per baseband can be 1, 2, 3 or 4. For 3 spws, the correlator resources
per spw should be set to 1/4, so only 3/4 of the available resources are used in this case.
All the spws within the same baseband are required to have the same correlator channel
width (before channel-averaging). An individual spw within a baseband may occupy 1, 1/2
or 1/4 of the resources available in the baseband and the sum of the fractional resources
within one baseband must be ≤1. The correlator resources are proportional to the numberof correlator spectral channels.
With DSB receivers (Band 9 and 10), 90-degree phase switching is allowed, giving bothsidebands simultaneously. This is only available for TDM and FDM 1875 MHz bandwidthmodes.

3.
4.
5.

6.

7.

8.
9.

10.
11.

12.

Table 6.2: Rules for spectral setups.
FWHM

85

86

CHAPTER 6. SPECTRAL SETUPSChapter 7

Imaging with ALMA
7.1

Introduction

As described in Chapter 3, the van Cittert-Zernike theorem (e.g., Rohlfs & Wilson 2004) describes a fundamental
relationship between the sky brightness distribution (I), the beam pattern (A) and the visibility distribution V:
Z Z
A(l, m)I(l, m) =V(u, v)e2πi(ul+vm) dudv

(7.1)

An ALMA observation can be represented by N discrete points in the uv-plane Vk (uk , vk ) where k = 1, . . . , N
and N can reach a few million. In addition to the visibilities Vk obtained, a weighted visibility function V W
can be defined (see Briggs, Schwab & Sramek, 1999) that enables the resulting synthesized beam size and thesensitivity to be controlled:
V W (u, v) =N
X

Rk Tk Dk δ(u − uk , v − vk )Vk (uk , vk ).

(7.2)

k=1

In Equation 7.2, Rk , Tk and Dk are weights, which control the relative weighting of individual visibilities
in imaging. Rk is a noise-variance weight derived from the sensitivity of the k th visibility measurement. It
accounts for variables such as the integration time, the system temperature, and the bandwidth. These factors
are determined by the instrument, technical set-up, and observing conditions, and are not controlled by theimaging process. Tk is a “taper” weight— by convention usually a multiplicative, Gaussian factor in the uv
plane— that can be used to down-weight the longest baselines, suppress small-scale sidelobes, and increase
the synthesized beam width and surface brightness sensitivity. Finally, Dk is a (uv) “density” weight that canbe used to offset the high concentration of measurements near the center of the uv-plane, typically increasing
resolution and reducing the sidelobes caused by gaps in the uv-coverage.
There are two commonly used limiting forms of density weighting (Dk ):• Dk = 1 is called natural weighting, and is based primarily on the density of visibilities in the uv-plane.
Natural weighting yields maximum sensitivity and a relatively large synthesized beam.
• Dk = Ns1(k) is called uniform weighting, where Ns (k) is the number of visibilities in a region centeredon the k th visibility. It removes the dependence of spatial-scale sensitivity on the density of visibilities(samples) in the uv-plane. Uniform weighting allows the highest angular resolution at the expense of
sensitivity.
As will be discussed in Section 7.4, ALMA imaging typically uses a tunable, intermediate form of density
weighting called Robust or Briggs weighting.

87

88

CHAPTER 7. IMAGING WITH ALMA

Figure 7.1: This is one of the sharpest images ever taken by ALMA. It shows the protoplanetary disc surrounding
the young star HL Tauri. These new ALMA observations reveal substructures within the disc that have neverbeen seen before and even show the possible positions of planets forming in the dark patches within the system.
Credit: ALMA (ESO/NAOJ/NRAO)

7.2

Cycle 5 Configurations

In Cycle 5, depending on the range of angular scales required, an ALMA project will obtain data from one or
two 12-m Array configurations, and potentially also from the 7-m Array. If yet larger angular scale informationis required, single-dish data from the Total Power (TP) Array will be obtained as well when possible (forinstance, the TP Array does not currently support continuum science observing). Imaging consists of combining
the interferometric data together using an appropriate weighting function; de-convolving the interferometer
synthesized beam (the point spread function (PSF), or also called “dirty beam” ) which results from finite
sampling of the uv-plane; and, if TP Array data exist, gridding them into an image cube and combining it withthe de-convolved interferometer image cube using the feathering technique. We describe in this chapter someof the aspects of imaging that should be considered to obtain the best results from ALMA observations.
During Cycle 5, the 12-m Array - with (at least) 43 antennas - will be arranged in ten different configurations.
The maximum baselines achievable will be 16.2 km for Bands 3-6, 8.5 km for Band 7 and 3.6 km for Bands
8-10. The 7-m Array, with (at least) ten antennas, will be available in only one configuration. Four extended
configurations will be available in Cycle 5: C43-7, C43-8, C43-9, and C43-10. The most extended configuration- C43-10 - will be offered alone; it cannot be combined with other configurations. The other three extended
configurations - C43-7, C43-8 and C43-9 - are offered in combination with other configurations, as in previous
cycles. Tables 7.1 and 7.2 give the basic properties of the 12-m Array and 7-m Array configurations. In addition,
Figures 7.2, 7.3 and 7.4 show antenna locations for the configurations of the 12- and 7-m Arrays. The three TP
Array single-dish 12 m antennas will be in fixed positions. It should be noted that these configurations(especially for the 12-m Array configurations) and the corresponding resolutions/max angularscales are representative of the actual configurations that will be in use. A variety of factors including,but not limited to, the existence of hybrid configurations during antenna reconfiguration periods and the precise
antenna pad availability schedule will likely lead to deviations from the values shown here. From the user’s pointof view configurations are not directly selected, instead the required angular resolution (θres ) and the largest
angular scale (θLAS ) that need to be recovered are entered in the OT. Projects will then be observed usingarray configurations chosen to achieve the specified goals. More details about array combination are provided
in Section 7.8.

89

7.2. CYCLE 5 CONFIGURATIONS

Configuration
7-m
C43-1
C43-2
C43-3
C43-4
C43-5
C43-6
C43-7
C43-8
C43-9
C43-10Band
Frequency (GHz)

3
100

4
150

5[*]
185

6
230

7
345

8
460

9
650

10
870

θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)
θres (arcsec)
θM RS (arcsec)

12.5
66.7
3.38
28.5
2.3
22.6
1.42
16.2
0.918
11.2
0.545
6.7
0.306
4.11
0.211
2.58
0.096
1.42
0.057
0.814
0.042
0.496

8.35
44.5
2.25
19.0
1.53
15.0
0.943
10.8
0.612
7.5
0.363
4.47
0.204
2.74
0.141
1.72
0.064
0.947
0.038
0.543
0.028
0.331

6.77
36.1
1.83
15.4
1.24
12.2
0.765
8.73
0.496
6.08
0.295
3.62
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

5.45
29.0
1.47
12.4
0.999
9.81
0.615
7.02
0.399
4.89
0.237
2.91
0.133
1.78
0.09171.12
0.04170.618
0.02480.354
0.0183
0.216

3.63
19.3
0.98
8.25
0.666
6.54
0.41
4.68
0.266
3.26
0.158
1.94
0.08871.19
0.06120.749
0.0278
0.412
-

2.72
14.5
0.735
6.19
0.499
4.9
0.308
3.51
0.2
2.44
0.118
1.46
0.06650.892
0.0459
0.562
-

1.93
10.3
0.52
4.38
0.353
3.47
0.218
2.48
0.141
1.73
0.08381.03
0.0471
0.632
0.0325
0.398
-

1.44
7.67
0.389
3.27
0.264
2.59
0.163
1.86
0.106
1.29
0.06260.77
0.03520.472
0.0243
0.297-

Table 7.1: Resolution (θres ) and maximum recoverable scale (θM RS ) for the 7-m Array and 12-m Array configurations available during Cycle 5 as a function of a representative frequency in a band. The value of θM RS is
computed using L05 from Table 7.2 and Equation 7.7; the value of θres is the mean size of the interferometricbeam obtained through simulation with CASA, using Briggs uv-plane weighting with robust=0.5. (This valueof robust offers a compromise between natural and uniform.) The computations were done for a source atzenith; for sources transiting at lower elevations, the North-South angular measures will increase proportional
to 1/sin(ELEVATION). Note: Band 5 is planned to become available March 2018. Consequently, according to
the current planning the long baselines configuration C43-6 to C43-10 will not be available for Band 5 in Cycle
5.

Configuration
Minimum baseline (m)5th percentile or L05 (m)80th percentile or L80 (m)Maximum baseline (m)

7m
8.7
9.1
30.7
45.0

C43-1
14.6
21.4
107.1
160.7

C43-2
14.6
27.0
143.8
313.7

C43-3
14.6
37.6
235.4
500.2

C43-4
14.6
54.1
369.2
783.5

Configuration
Minimum baseline (m)5th percentile or L05 (m)80th percentile or L80 (m)Maximum baseline (m)

C43-6
14.6
148.6
1172.52516.9

C43-7
64.0
235.2
1673.13637.8

C43-8
110.4
427.3
3527.38547.7

C43-9
367.6
746.9
6482.613894.2

C43-10244.01228.18685.916194.0

C43-5
14.6
90.9
623.8
1397.9

Table 7.2: Basic parameters of the 7-m Array configuration and the ten 12-m Array configurations offeredduring Cycle 5. The baselines are projected for a transiting source (HA = ± 1h) at a declination of −23◦ . Notethat C43-8 will not be available for Bands 8-10, and C43-9 and C43-10 will not be available for Bands 7-10.

90

CHAPTER 7. IMAGING WITH ALMA

1000

C43-1

500

500

0

0
Y (meter)Y (meter)

1000

500
1000

1500
1000

500

0
X (meter)

500

1000

1500

1500

500

500

0

0

500

1000

1500

1500
1000

500

0
X (meter)

500

1000

1000

1500

1500

0
X (meter)

500

1000

0

0
Y (meter)

500

500
1000

1500

C43-4

1000

500

0
X (meter)

500

1000

1000

C43-5

500

1500

C43-6

500
1000

1500
1500

500

500

1000

1500

1000

1000

C43-3

Y (meter)Y (meter)

1000

Y (meter)

500
1000

1500
1500

C43-2

1500
1000

500

0
X (meter)

500

1000

1500

1500

1000

500

0
X (meter)

500

1000

Figure 7.2: Representative 12-m Array compact configurations for Cycle 5.

1500

91

7.3. SHADOWING

10000

10000

C43-7

5000
Y (meter)Y (meter)

5000

0

0

5000

5000

10000
10000 8000

6000

4000

2000 0X (meter)

2000

4000

10000

10000
10000 8000

6000

6000

4000

2000 0X (meter)

2000

4000

10000

C43-9

6000

C43-105000
Y (meter)5000
Y (meter)

C43-8

0

0

5000

5000

10000
10000 8000

6000

4000

2000 0X (meter)

2000

4000

10000
10000 8000

6000

6000

4000

2000 0X (meter)

2000

4000

6000

Figure 7.3: Representative 12-m Array extended configurations for Cycle 5.
20
7-m

15
10

Y (meter)

5
0
5
10
15
2020

15

10

5

0
X (meter)

5

10

15

20

Figure 7.4: Representative 7-m Array configuration for Cycle 5.

7.3

Shadowing

ALMA is located at latitude=-23.02917◦ , longitude=-67.754649◦ . During observations, particularly in very
compact configurations like those of the 7-m Array or C43-1, one antenna’s view of the source can be partially
blocked by another, making the data from that antenna unusable. This phenomenon is known as shadowing andcan be quite severe for sources that are observed at very low elevation. Targets as far North as declination +47◦ ,92

CHAPTER 7. IMAGING WITH ALMA

corresponding to a maximum source elevation at Chajnantor of ∼20◦ , can in principle be observed from the
ALMA site, but shadowing by adjacent antennas becomes an increasing problem at low elevations. For example,
Figure 7.5 shows the percentage of data that will be shadowed (the “shadowing fraction”) when sources of various
declinations are observed in the most compact ALMA configurations. As it can be seen, the shadowing fraction
can be as large as 55% for sources observed with the most compact 12-m Array configuration (C43-1). The
imaging capability, as well as the time on source, will necessarily be limited for such northern sources, especiallyat the higher frequencies. Shadowing depends on the antenna configuration. Given the short baselines in the
ACA configuration, sources with declinations less than −70◦ or greater than +25◦ are subject to significant
shadowing. For the 12-m Array, shadowing becomes significant (> 5 %) in the most compact configuration forsources with declination lower than −65◦ or higher than +20◦ .
Note that another issue with observations of sources at low elevations, whether there is shadowing or not,is that the uv coverage , and therefore the synthesized beam, will not be symmetric.

Figure 7.5: Shadowing fraction (%) for the most compact configurations as a function of declination (for a
1-hour observation at transit).

7.4

Resolution and Beam ShapeThe angular resolution θres of an array can be estimated roughly with the following equation:
θres =

kλ[radians]
Lmax

(7.3)

where k is a factor that depends on the uv-plane weighting function, λ is the observing wavelength inmeters, and Lmax is the longest baseline in meters. For the ALMA configurations, the following equation wasdetermined, which uses the 80th percentile of the uv-distance as a more robust proxy to the longest baselines.
θres ≈

0.574λ[radians]
L80

(7.4)

where λ is the observing wavelength in meters, and L80 is the 80th percentile of the uv-distance in meters.
An important consideration when imaging is the uv-plane weighting scheme (k) used when Fourier transforming the visibilities. Natural weighting gives the highest-sensitivity image as each visibility is assigned a7.4. RESOLUTION AND BEAM SHAPE

93

Figure 7.6: Angular resolution achieved using different values of the CASA robust parameter for a 1-hourobservation at 100 GHz and a declination of -23 deg in the C43-4 configuration. Note that robust = −2 is close
λto uniform weighting and robust = 2 is close to natural weighting. The dotted line corresponds to Lmax.
weight based on its intrinsic uncertainty. Uniform weighting, on the other hand, modifies the weights in sucha way that each part of the uv-plane contributes equally to the final image. If this were not done, the shorter
baselines would dominate as they have a higher density in the uv-plane. Therefore, uniform weighting degrades
the sensitivity (the intrinsic weights are no longer used) but increases the angular resolution as the longer
baselines have a higher weight.
To bridge the extremes of natural and uniform weighting, Briggs (1995) defined a continuous scheme thatuses a “robustness” parameter R (this parameter is called robust in CASA). In CASA, uniform weighting is close
to robust = −2 and natural weighting is close to robust = 2. Figure 7.6 shows the angular resolution achieved
for an observation with the C43-4 configuration at 100 GHz using robust values between −2 and 2. As canbe seen, the angular resolution varies from 0.700 (robust = −2) to 1.200 (robust = 2). The angular resolutions
presented here for ALMA were all computed using CASA simulations with Briggs weighting and robust = 0.5.
The synthesized beam shape, which is the Fourier transform of the uv-plane sampling during the observation(s), is a function of the source declination. In addition to shadowing, sources that must be observed at
low elevations also have shorter projected North-South baselines and thus the shape of the uv-plane sampling
distribution becomes more elongated and the beam shape more elliptical. For example, Figure 7.7 shows thedifferent beam shapes for sources observed at declinations of −70◦ (similar to the SMC and LMC) and −30◦ .
Also, Figure 7.8 shows the uv-coverage for these sources, revealing the elongation of the uv-plane sampling
distribution, together with the large fraction of shadowing, for the more southern sources. To mitigate thiseffect, one can convolve the resulting images to a more circular (albeit larger) beam after deconvolution.
Figure 7.9 shows the minor and major axes of the synthesized beam widths (θres ) for each array configuration
as a function of source declination for a 2-hour observation at 100 GHz. Figure 7.10 shows the geometrical meanof the major and minor axes of θres at the same frequency. The beam width scales with λ, but bear in mind
that not all configurations can be used with the higher-frequency bands, e.g., C43-8 is not available at Bands
8-10.
Note that in the OT, the angular resolution and sensitivity are now computed consistently, assuming Briggs
weighting with robust = 0.5. The most appropriate value of robust to use when imaging a dataset must be

94

CHAPTER 7. IMAGING WITH ALMA

Figure 7.7: Beam shape for configuration C43-1 with a 2-hour observation of a transiting source at a declinationof either −70◦ (left) or −30◦ (right).

Figure 7.8: uv-plane coverage for configuration C43-1 with a 1-hour observation of a transiting source at a
declination of either −70◦ (left) or −23◦ (right). For the source with a declination of −70◦ , the shadowing
fraction represents 25.7% of the total.

7.4. RESOLUTION AND BEAM SHAPE

95

Figure 7.9: Cycle 5 angular resolutions as a function of source declination. Each color shows, for a particularconfiguration, the range of the major and minor axes of the synthesized beams expected from a 2-hour observation at 100 GHz and at transit. 12-m Array configurations are arranged with C43-1 at the top and C43-10
at the bottom.

Figure 7.10: Geometrical mean of the major and minor axes of the synthesized beams as a function of source
declination. These correspond to a 2-hour observation at 100 GHz and at transit. 12-m Array configurations
are arranged with C43-1 at the top and C43-10 at the bottom. The 7-m Array is also shown.

96

CHAPTER 7. IMAGING WITH ALMA

determined based on the goals of the scientific case (required angular resolution, sensitivity, etc). In cases
where more precise information is required, CASA simulations using the representative configurations, actual
target declination, uv-coverage, and clean1 parameters can be used to predict the resolution and sensitivity fora specific science use case. One should clean the images carefully, and also add noise (and realistic systematic
errors, if possible) to simulations, to see what kind of residual sidelobes are expected. (Cleaning perfect data
does not show the limitations that one might obtain with real data.)
As will be discussed in Section 7.9, combining data from compact configurations with those from more
extended configurations primarily has the effect of compensating for negative sidelobes in the synthesized beamand thereby improving the interferometer’s response to larger angular structures on the sky. Such combination,
however, does also slightly degrade the resolution. This degradation can be mitigated by moving towards
uniform density weighting.

7.5

Response and Snapshot

The sampling function S of the visibility distribution is defined as:S(u, v) =

N
X

(7.5)

δ(u − uk , v − vk )k=1

If S were a continuous function, e.g., a Gaussian, the synthesized beam would also be a Gaussian i.e., acentral peak with a smoothly decreasing response away from the center. Given the finite number of baselines,
however, the sampling function is an ensemble of Dirac functions and the Fourier transform of this produces a
central peak surrounded by a complex pattern of sidelobes. This “dirty beam” response is a consequence of thegaps in the uv-plane, the sidelobes becoming increasingly prominent as the gaps increase (Gibbs phenomenon).
As the projected baselines (i.e., the baseline lengths and orientations as seen from the source) change as afunction of time as the Earth rotates, the longer a source is observed for, the greater the uv coverage and thesmaller the sidelobes. Short integrations are still valuable, particularly when using many of the fifty 12-m Arrayantennas, however, if angular structure and sensitivity are less important. Such integrations are sometimes
called snapshots , and they produce obvious sidelobes which can be mitigated by applying a uv-taper , a downweighting of the visibilities on longer baselines, during the Fourier transform. Table 7.3 gives the level ofsidelobes for each configuration, for a 1-hour observation of a source at Dec=−23◦ .
Configuration
naturalbriggs (R = 0.5)
uniform

7m
44.0%
42.2%
39.0%

C43-1
5.5%
7.8%
7.7%

C43-2
5.0%
6.6%
16.7%

C43-3
6.2%
6.7%
12.4%

C43-4
10.4%
7.3%
11.0%

Configuration
naturalbriggs (R = 0.5)
uniform

C43-6
4.6%
6.2%
11.3%

C43-7
9.6%
5.6%
11.2%

C43-8
7.8%
9.7%
10.1%

C43-9
11.1%
9.6%
8.5%

C43-10
13.0%
11.3%
12.0%

C43-5
6.3%
8.0%
13.1%

Table 7.3: Sidelobe levels for a 1-hour observation of an unresolved source at a declination of −23◦ with thedifferent array configurations. The levels are indicated with three different weighting schemes used for theimaging.
Figures 7.11 and 7.12 show examples of a uv-plane sampling distribution and cleaned image for a snapshot of
1-minute duration and a longer integration of 1-hour duration expected with the configuration C43-1. As shownin Figure 7.11, the uv-coverage in 1 minute is quite uniformly sampled, but much less dense than that of the
1-hour integration. In addition, the cleaned images of the snapshot and the longer integration (see Figure 7.12)
1 Or TCLEAN, an improved implementation of CLEAN. In a near future CASA release CLEAN and TCLEAN will be renamed
and the old implementation deprecated.

7.6. SPATIAL SCALE FILTERING

97

Figure 7.11: uv-plane sampling distributions of a model ALMA observation with 1-minute integration (left) and1-hour integration (right), using the C43-1 configuration to observe a source at a declination of −23◦ .
are similar in terms of angular resolution and the apparent differences are quite small. The main difference
between the two (besides sensitivity) is in the dirty beam: the sidelobe level for the snapshot will be muchhigher than for the 1-hour integration. The snapshot image will then require more careful cleaning in order toavoid introducing spurious sources from the strong sidelobes. Condon et al. (1998) gave a very comprehensive
description of how this issue impacted the 20-cm NRAO VLA Sky Survey (NVSS).
A useful practice to disentangle sidelobe effects from real point sources, especially with relatively strong
point sources, is to perform CASA simulations using a component list of the strongest sources together withthe actual array configuration. This test allows one to estimate the sidelobe fingerprint left by the strong point
sources after deconvolution (cleaning), although the residuals will likely be higher in practice due to imperfectcalibration. It is worthwhile to use the interactive mode during the deconvolution so that residuals can bemonitored.

7.6

Spatial Scale Filtering

As described in Chapter 3, an interferometer measures the Fourier components of the sky brightness distribution
in an area of the uv-plane defined by the array configuration used to observe the target. Since the uv-plane is a
representation of the power of the sky brightness distribution per angular scale, an interferometer observationacts like a passband filter in the spatial domain. An astronomical source is then filtered if its Fourier transform
has substantial power on angular scales outside the region of the uv-plane sampled by a given configuration.
To illustrate this concept, the annularly averaged amplitudes of the Fourier transforms of three uniform diskswith sizes of 500 , 1000 and 2000 are shown in Figure 7.13 for an observation at 100 GHz. The smallest uniform
disk is closest to a point source and so it has large amplitudes up to a baseline of 180 m. Meanwhile, the mostextended disk has large amplitudes only up to ∼40 m. Therefore, an array with baselines larger than 40 mwill not be sensitive to emission on angular scales larger than ∼2000 , and will filter out most of the emission
from such an extended disk. An important consequence of such filtering is that an interferometer only detects a
fraction of the total flux density for sources with emission on size scales larger than its shortest baseline. Indeed,
if the source only has structures on size scales larger than the shortest observed baselines, one can “resolve-out”
the source entirely. It is to ameliorate the effects of spatial filtering for extended sources that the 7-m and TP
Arrays are available in addition to the 12-m Array configurations.
The maximum recoverable scale (θM RS , see Equation 3.27) is the largest angular structure to which a given
array is sensitive. It is determined by the length Lmin of the shortest baseline in the array. In principle thisbaseline measures spatial scales with a period of λ/Lmin . In fact the sensitivity of this measurement to such large

98

CHAPTER 7. IMAGING WITH ALMA

Figure 7.12: Images obtained from a model ALMA observation with 1-minute integration (left) and 1-hour
integration (right), using the C43-1 configuration to observe a source at declination of −23◦ . Black contours at
100, 200, 300, 500, 700 and 900 mJy beam−1 are overlaid.
structures is not very good, so a smaller value of θM RS is typically adopted. Indeed, the exact filtering depends
on precisely how the structure of the large scale emission maps to the (lack-of) short-baseline uv-coverage andis best determined by simulations. ALMA has adopted a criterion of measuring 10% of the total flux density ofa uniform disk, which yields:
θM RS ≈

0.6 λ[radians]
Lmin

(7.6)

where λ is the observing wavelength in meters, and Lmin is the shortest baseline in meters. For the ALMA
configurations, the following equation was determined, which uses the 5th percentile of the uv-distance as amore robust proxy to the shortest baselines.
θM RS ≈

0.983 λ[radians]
L5

(7.7)

where λ is the observing wavelength in meters, and L5 is the 5th percentile of the uv-distance in meters.
Table 7.1 lists the θM RS for the various Cycle 5 array configurations. Note that these expressions assume
good uv-coverage. This situation is typically the norm for ALMA 12-m Array observations, but may not be forvery short 7-m Array observations due to the relatively small number of antennas.
The spatial filtering of an interferometer observation is a serious issue that must be considered carefully foreach science case. Ideally, the range of spatial frequencies over which the source has interesting structure will beknown a priori so that the appropriate configuration can be used during observations. Selecting a specific rangeof angular scales has the effect of discarding all emission from those angular scales outside that range. If verylarge spatial scales (relative to those measured by the 12-m and 7-m Arrays) are important, the combination of
the TP Array, 7-m Array, and 12-m Array should be used, as discussed in Section 7.8.
Figure 7.14 shows the annularly averaged visibility amplitudes vs. uv-distance of an example astronomicalsource, M51. This example is taken from an H-α image, but it is used to indicate the flux expected at 100 GHz.
The amplitudes of the visibilities can be approximated as a power law of uv-distance with a negative index. This

99

7.7. MOSAICING

5 arcsec
10 arcsec
20 arcsec
0.8

V

0.6

0.4

0.2

0.0

0.20

50

100
UV radius (meter)

150

200

Figure 7.13: Annularly averaged amplitudes of the expected visibilities of three model uniform disks (annularaverages) at 100 GHz as a function of uv-distance.
indicates that most of the power is located in larger scale structures and that power decreases rapidly at smallerscales. This result shows that the flux that would be received by the 7-m Array would be much higher than thatreceived by the 12-m Array with extended configurations (e.g., C43-6). The only case where flux is independentof the sampling in the uv-plane is for point sources, which have the same amplitude for all visibilities (i.e., theFourier transform of a Dirac function). In our M51 example, the visibility amplitude detected by the 7-m Array(at kuv ≈ 5kλ) is ∼23 Jy, whereas that detected by the configuration C43-6 (kuv ≈ 200kλ) is only ∼0.9 Jy.
Ideally, ALMA users should use simulations to estimate the distribution of power at different length scales fortargets they wish to observe.

7.7

Mosaicing

The field of view of a single interferometer pointing is determined by the antenna primary beam. A uniformly
λilluminated, circular aperture will have a beam width at half power (F W HM ) of 1.02 D. It will also havevery high side lobes due to the abrupt truncation of the antenna illumination pattern; indeed, these side lobes
would be particularly problematic for single-dish observations. Most radio and millimeter receivers illuminate
their antennas with approximately Gaussian illumination patterns that smoothly go down to -10 dB to -15 dB
response at the edges of the dish. The ALMA feedhorns were designed to illuminate the dish with a -12 dB edge
taper to provide a nearly Gaussian primary beam with low sidelobes while preserving as much of the resolution
and sensitivity as possible. This tradeoff is a fundamental aspect of radio telescope design. The resulting
λ= 5800 at 100 GHz, and it varies
F W HM of the ALMA 12 m antennas is measured to be F W HM = 1.13 D
inversely with frequency. For example, Figure 7.15 shows a Gaussian profile that approximates the shape of the
primary beam at 112 GHz with F W HM = 5200 . As described in Chapter 3, the primary beam attenuation canbe corrected as the last step of imaging. In addition to correcting the sky distribution of the signal to its correct
value, this correction, however, also increases the noise (i.e., the signal-to-noise is unchanged). For example atthe radius of the FWHM, the noise will be increased by a factor of two compared to that at the phase center.
Moreover, beyond a certain map size, the antenna is not sensitive and it is necessary to observe several adjacentpointings, i.e., a mosaic, to recover the sky emission.
Observing a mosaic with ALMA is needed if a map size larger than approximately the F W HM of the

100

CHAPTER 7. IMAGING WITH ALMA

Figure 7.14: Image of Hα emission from M51 used as a model of emission at 100 GHz (left) and the expectedvisibility amplitudes with uv-distance (right).
primary beam is required. The default mosaic pointing pattern used by ALMA is a “fully sampled” hexagonal
grid with equilateral triangles whose vertices are separated by θhex = Dλ√3 = 0.511 × F W HM . With thisspacing, the mosaic will sample the emission at the Nyquist
spatial frequency. Note that a hexagonal mosaic√
has spacing θhex along a row (e.g., in right ascension) and 23 θhex between rows (e.g., in declination). Figure 7.16
gives an example of such a mosaic. To estimate the number of pointings (Np ) necessary to cover an area of
LX × LY using this hexagonal pattern, the following expressions can be used:
LX
NX = (int) 0.511F
W HM + 1.
Y√ + 1.
NY = (int) 0.511F2×L
W HM 3Np≈ (2NX − 1.) × N2.Y

For an observation at 100 GHz with LX = LY = 4 arcmin, 85 pointings are defined, similar to that obtainedby the above formulae. In the case of an odd number of rows, Np may differ slightly from the value returnedby the OT. Note that mosaicing with the 7-m Array is more efficient because with the smaller diameter of its
λalso holds for the 7-m antennas).
antennas, the FWHMs are commensurately larger (F W HM = 1.13 D
Like a single pointing, a mosaic has an analogous “mosaic primary beam response pattern” that is the
convolution of the individual F W HM s of the different pointings. Near the mosaic center, a Nyquist sampled
hexagonal mosaic pattern has a sensitivity about 1.58 times that of a single pointing, with the sensitivity
decreasing with the fall off of the mosaic primarybeam response pattern. Another frequently used mosaic√
pattern has pointings separated by F W HM/ 2 (see for example the NVSS survey); this pattern covers area
more efficiently but with little gain in sensitivity over a single pointing. Generally the Nyquist sampled hexagonal
pattern (default on ALMA) is a good choice for smaller mosaics and the constant noise hexagonal pattern ismost often used for larger mosaics. The ALMA Observing Tool (OT) can be used easily to set up a mosaic ofadjacent pointings with a user-defined√spacing, though it is not recommended to exceed spacings greater thanthe constant noise pattern (F W HM/ 2) if a well-sampled mosaic image is desired.

7.8

Multi-array and Multi-configuration Observations

As shown in Table 7.1, different 12-m Array configurations provide different angular resolutions, θres , which
are a function of the longest baselines of the configuration. Similarly, the maximum recoverable scales , θM RS ,of each configuration depend on the shortest baselines present. To achieve the requirements entered by the PI
in the OT, θres and θLAS , multiple configurations may be needed. Note that θLAS is a property of the science7.8. MULTI-ARRAY AND MULTI-CONFIGURATION OBSERVATIONS

101

Figure 7.15: Approximation of the primary beam profile of an ALMA 12 m antenna at 112 GHz with FWHM
= 5200 .

Figure 7.16: An example of mosaicing with a field of 2 arcmin extent at 100 GHz using a hexagonal patternwith Nyquist sampling (white crosses).

102

CHAPTER 7. IMAGING WITH ALMA

target, while θM RS is a property of an array configuration. In particular, the most compact configuration for a
project must ensure that θM RS is larger than or equal to the θLAS of the science target.
Based on the user-entered values of θres and θLAS , the OT will automatically attempt to choose configurations that will produce a final image with the requested scientific goals. Note, however, that there are
significant restrictions in this process. For example, at most two 12-m Array configurations are allowed andthe most extended configurations (C43-10) cannot be combined with any more compact configurations. If such
restrictions result in the requested θLAS not being achievable, the OT will return a validation error and θLAS
must be modified. In contrast, a new possibility for Cycle 5 is “stand-alone ACA”, i.e. observations that use the
7-m Array, with the TP Array added if required, but without 12-m Array observations. It is not possible torequest observations that only require the TP array.
In detail, the process of selecting the various array configurations required to satisfy the entered constraints
is the following:
1. An interferometric array configuration (12 or 7 m) is selected that comes closest to achieving the enteredvalue of θres .
2. If the θM RS of this array configuration is less than the requested θLAS , the largest structures in the source
will not be well imaged and more compact array configurations must be added, if possible.
3. If the initial array configuration was a medium-sized 12 m configuration, a more compact 12 m configuration can be added. If this array configuration also has θM RS < θLAS , the 7-m Array will then be added.
If the initial array configuration was one of the more compact 12 m configurations, it will only be possible
to add the 7-m Array.
4. If, after adding additional interferometric array configurations the requested θLAS has still not beenachieved, the TP array will be added. Note that this is not possible for continuum observations and forBands 9 and 10, so there is a fundamental limit to how large a source can be reliably imaged in thesesituations.
This procedure is carried out automatically by the OT and is entirely dependent on the values of θres and θLAS
that are entered by the user. A detailed list of the allowed combinations is given in Table 7.4.
Table 7.4 also shows the relative integration times that will be used by each array. Broadly speaking, becauseof their smaller collecting areas, the TP and 7-m Arrays require more on-source integration time than the 12-m
Array. The needed time ratios have been calculated by requiring similar sensitivity in the region of the uv planewhere configurations or arrays provide overlapping baselines; details of this calculation are in Mason & Brogan(2013). The actual time ratios adopted for ALMA observations are guided by the calculations outlined in thismemo, but are subject to further operational constraints. Cycle 5 implements again configuration-dependent
time ratios. That is, the time multiplier for, e.g., the 7-m Array depends on the 12 m configuration with which it
is being combined. A trend can be seen whereby the more compact the 12-m Array configuration, the more 7-m
Array time is required. Increasingly compact 12-m Array configurations contain more sensitivity on baselines
similar to those provided by the 7-m Array, which must in turn observe for longer to contribute significantly tothe final image. The TP Array’s time multiplier is fixed at 1.7 times the 7-m Array integration time.
As the compact configurations or arrays do require extra observing time, it is important to consider andjustify the requested value of θLAS . An additional consideration when requiring the 7-m Array (with only 10
antennas) is that it provides limited uv coverage for snapshot observations. For Cycle 5, at least one hourof unique 7-m Array hour-angle coverage is recommended to provide sufficient uv-coverage for good image
combination with data from the 12-m Array, and snapshot observations are therefore strongly discouraged. A
comprehensive plot about the array combination is shown in Fig. 15 of the ALMA Primer for Cycle 5.
The process whereby the OT chooses 12-m Array configurations is done assuming the exact antenna positions that make up the ten representative configurations that have been selected for Cycle 5. In reality, theconfiguration available to the scheduling software at the time of Scheduling Block (SB) execution rarely conforms to this ideal, due to the fact that the array is often being reconfigured, i.e., antennas are being moved
from one pad to another, a process that takes some time. Therefore, it is usually the case that the available

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7.8. MULTI-ARRAY AND MULTI-CONFIGURATION OBSERVATIONS

θres (arcsec)
0.042
0.042
0.057
0.057
0.057
0.096
0.096
0.096
0.211
0.211
0.211
0.306
0.306
0.306
0.306
0.545
0.545
0.545
0.545
0.918
0.918
0.918
0.918
1.42
1.42
1.42
2.3
2.3
2.3
3.38
3.38
3.38
12.5
12.5

θLAS (arcsec)< 0.496> 0.496< 0.8140.814-4.11> 4.11< 1.42
1.42-6.7> 6.7< 2.58
2.58-11.2> 11.2< 4.11
4.11-16.2
16.2-66.7> 66.7< 6.7
6.7-22.6
22.6-66.7> 66.7< 11.2
11.2-28.5
28.5-66.7> 66.7< 16.2
16.2-66.7> 66.7< 22.6
22.6-66.7> 66.7< 28.528.5-66.7> 66.7< 66.7> 66.7

Array combination
C43-10
C43-9
C43-9 + C43-6
C43-8
C43-8 + C43-5
C43-7
C43-7 + C43-4
C43-6
C43-6 + C43-3
C43-6 + C43-3 + 7-m
C43-6 + C43-3 + 7-m + TP
C43-5
C43-5 + C43-2
C43-5 + C43-2 + 7-m
C43-5 + C43-2 + 7-m + TP
C43-4
C43-4 + C43-1
C43-4 + C43-1 + 7-m
C43-4 + C43-1 + 7-m + TP
C43-3
C43-3 + 7-m
C43-3 + 7-m + TP
C43-2
C43-2 + 7-m
C43-2 + 7-m + TP
C43-1
C43-1 + 7-m
C43-1 + 7-m + TP
7-m
7-m + TPTime ratios
1
1
1 : 0.5
1
1 : 0.5
1
1 : 0.4
1
1 : 0.4
1 : 0.4 : 2.3
1 : 0.4 : 2.3 : 3.9
1
1 : 0.5
1 : 0.5 : 4.6
1 : 0.5 : 4.6 : 7.8
1
1 : 0.4
1 : 0.4 : 5
1 : 0.4 : 5 : 8.5
1
1: 5
1 : 5 : 8.5
1
1: 5
1 : 5 : 8.5
1
1: 5
1 : 5 : 8.5
1
1 : 1.7

Total Time
1.0 × ∆extended
1.0 × ∆extended
1.5 × ∆extended
1.0 × ∆extended
1.5 × ∆extended
1.0 × ∆extended
1.4 × ∆extended
1.0 × ∆extended
1.4 × ∆extended
3.7 × ∆extended
5.3 × ∆extended
1.0 × ∆extended
1.5 × ∆extended
6.1 × ∆extended
9.3 × ∆extended
1.0 × ∆extended
1.4 × ∆extended
6.4 × ∆extended
9.9 × ∆extended
1.0 × ∆extended
6 × ∆extended
9.5 × ∆extended
1.0 × ∆extended
6.0 × ∆extended
9.5 × ∆extended
1.0 × ∆extended
6.0 × ∆extended
9.5 × ∆extended
1.0 × ∆extended
1.7 × ∆extended

Table 7.4: Configuration or Array combinations with the corresponding {θres , θLAS } conditions for an observation at 100 GHz. As in the OT, the angular resolution is computed from the most extended configuration.
The actual resolution obtained with combined configurations can be 50% lower due to different weighting (seetext). NOTES: a) for the full array combination, the total time is not equal to the sum of the individual times
because TP and 7-m Array observations are run in parallel; b) for intermediate values of θres , please see text.

configuration’s properties, θM RS and θres , do not exactly conform to those assumed by the OT. Given that theavailable configuration provides a similar range of spatial scales to that which was assumed, SB execution may
still be possible provided that the other parameters (weather, project rank, LST range and executive balance)
are also appropriate. This flexibility in scheduling is vital to the efficient execution of SBs and is built into
the second stage of ALMA’s Quality Assurance process (QA2) such that all observed projects should meet theuser’s imaging requirements, within some tolerances. Note that some additional flexibility is provided by theassumption of Briggs’ weighting during the imaging stage, a scheme which allows a tradeoff between angularresolution and sensitivity.

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CHAPTER 7. IMAGING WITH ALMA

Multi-array and Multi-configuration Imaging

If a project requires observations with different arrays or configurations, the data from each will be processedindividually and delivered if they pass quality assurance. When all observations are complete, they will also—
on a best-efforts basis— be combined to make and deliver a final image, again if it passes quality assurance.
The combination procedure comprises either one or two steps, depending on whether total power data
are collected. First, the interferometric data will be imaged together in a single, “joint” deconvolution. Thiscan be done in CASA by passing all interferometric measurement sets— 7-m and one or more 12-m Arrayconfigurations— directly to the CLEAN task2 . All 7 m and 12 m data delivered during Cycle 5 will be directly
combinable. Manually calibrated data deliveries from earlier ALMA cycles that were calibrated using CASA
versions earlier than 4.3 require an additional step to put the 7-m and 12-m Array data weights on an equalbasis. All ALMA data calibrated by the ALMA pipeline, however, have correct weights, irrespective of Cycle
number and CASA version. The steps to correct data weight issues for manually calibrated data from earlier
Cycles are described in the “Data Weights and Combination” CASA guide3 . Using the STATWT method is
another easy and reliable approach assuming sufficient line-free spectrum can be identified.
If total power data are part of a project, then there is a second step to the combination procedure, whichis to combine the deconvolved interferometric (7-m+12-m) image cube with the total power image cube. In
Cycle 5 this combination will be done by “feathering” them together. Feathering is a commonly used techniquein radio imaging for combining two images together by forming a weighted sum of their Fourier transforms. The
steps are as follows:
1. The total power and interferometer images are Fourier transformed.
2. The beam from the total power image is Fourier transformed (F T SDB(u, v)), to be used as a weighting function. Alternatively one can specify some smaller portion of the total power antenna aperture,corresponding to a wider (single-dish) beam.
3. The Fourier transform of the interferometer image is multiplied by (1 – F T SDB(u, v)). This step downweights the large spatial scale components of the interferometer map which are poorly measured, if measured at all.
4. The Fourier transform of the total power image is multiplied by the ratio of the volumes of the interferometer restoring beam to the single-dish beam, thereby putting the maps in the same units.
5. The results from 3 and 4 are added and Fourier transformed back to the image plane.
The resulting cube provides high angular resolution due to the interferometric data, but will have moreaccurate large-scale features and total flux densities because the single dish data are present as well. An excellent
discussion of feathering and comparison to other techniques for combining single dish and interferometer data
is given in Stanimirovic (2002).
As an example, the uv-coverages and uv-plane sampling distributions for a 1-hour observation with the C43-1
configuration and 5-hour observation with the 7-m Array are shown in Figure 7.17 and Figure 7.18, respectively.
The Cycle 5 7-m Array configuration with ten 7 m antennas provides uv measurements in the range 8-32 m andtakes over the 12-m Array configurations in the range R(u,v) < 15 m. Using the Hα emission in M51 as a model,
and given the spread of its emission over different length scales (see Figure 7.14), Figure 7.19 shows the images
resulting from observing with a C43-compact configuration (C43-3), a compact and extended configuration(C43-3 + C43-6), and adding the 7-m Array. Natural weighting was used and deconvolution was performed
using the CLEAN algorithm. The recovery of larger scales is quite noticeable with the inclusion of the 7-m
Array data. Using only the C43-6 configuration at 100 GHz provides an angular resolution of 0.2700 . Combinedwith the C43-3 configuration, the angular resolution is lowered to 0.3100 . Finally, the angular resolution with thefull combination (C43-3 + C43-6 + 7-m) is 0.3200 , very similar to that of only the two 12-m Array configuration
2 Or TCLEAN, an improved implementation of CLEAN. In a near future CASA release CLEAN and TCLEAN will be renamed
and the old implementation deprecated.
3 https://casaguides.nrao.edu/index.php/DataWeightsAndCombination

7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

105

Figure 7.17: Expected uv-coverage for C43-1 (1 hour) and 7-m observations (5 hours)

Figure 7.18: Radial density of uv-coverage with uv-distance using C43-1 (1 hour) and 7 m observations (5 hours)

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data but 17% larger than the angular resolution obtained with the extended 12-m Array data alone. Thatdifference is due to the respective uv-coverage and weight of the array configurations in the combined dataset.

Figure 7.19: Images obtained using C43-3 (top left; 1 hour), C43-3 + C43-6 (top right; 1 + 3.3 hours) and C43-3+ C43-6 + 7-m (bottom left; 1 + 3.3 + 1.3 hours) Array combinations, and the image model itself (bottom
right).
These simulations illustrate two general features of multi-configuration/array observations. First, they are
effective in retrieving a wider range of spatial scales than are accessible to a single configuration or array.
Second, the addition of more compact configurations or arrays does tend to broaden the synthesized beam(PSF) slightly. This broadening can be mitigated by changing the uv weighting, e.g., via the robust parameter,at the expense of sensitivity.
References[1] Briggs, D. S. 1995, High Fidelity Deconvolution of Moderately Resolved Sources Ph.D. thesis, New Mexico
Institute of Mining and Technology

7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

107[2] Briggs, D. S., Schwab, F.R., Sramek, R. A. 1999, Synthesis Imaging in Radio Astronomy II, ASP Conference
Series, 180, 127[3] Condon, J. J., R, W. D., Greisen, E. W., Yin, Q. F., Perley, R. A., Taylor, G. B., Broderick, J. J. 1998, AJ,
115, 1693[4] Mason, B. & Brogan, C., 2013, Relative Integration Times for the ALMA Cycle 1 12-m, 7-m, and Total
Power Arrays, ALMA memo 598[5] Moriarty-Schieven, G. ed., 2013, Observing with ALMA: A Primer for Early Science, ALMA Doc. 2.1, ver.
1
[6] Stanimirovic, S. 2002, in Single-Dish Radio Astronomy: Techniques and Applications, edited by S. Stanimirovic, D. Altschuler, P. Goldsmith, & C. Salter, vol. 278 of Astronomical Society of the Pacific Conference
Series, 375. astro-ph/0205329

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Chapter 8

Observing Modes
The ALMA Observing modes are the set of capabilities that ALMA offers each cycle to its base community. In
order to execute an approved ALMA project, the particular observing mode needs to be implemented in the
ALMA online software package and verified using the required hardware. Here the software implementation is
described along with a description of particular observing modes.
An observing proposal submitted to the ALMA archive will have an associated structure called the Observing Project that will accompany it along the whole length of its lifecycle. This structure is defined in the
ALMA Project Data Model (APDM), which specifies all the relevant components and their contents needed forsuccessful completion of a project. A summary view of the constituents of an Observing Project is shown in
Figure 8.1.

8.1

Observing Project Structure

The organization of each science project is subdivided into a well-defined structure with clear hierarchicallevels. At the bottom of this structure are the Scheduling Blocks (hereafter SB). An SB is the minimum setof instructions describing an ALMA observation that can be fully calibrated. The SBs to be executed during
the observations are produced automatically by the ALMA Observing Tool (hereafter OT) during the Phase 21
stage of the project life cycle. The SB may be edited, using the OT, in Phase 2 after the proposal has been
accepted for observation and also during the proposal execution if necessary2 . Projects are broken down into a
set of these fundamental units for flexibility, given the properties of the ALMA site and the continuously-varying
status of the Observatory as a whole (including the weather), and to encapsulate the scientific objectives of the
proposal into single entities.
An SB contains a large amount of information about what should be observed, the positions and velocities ofthe science targets, details of the correlator setup, the integration and cycle times of the different calibrations,etc. However, the SB itself does not control the observations as it is just a single set of XML instructions.
Instead, the ALMA online software reads the SB and executes the observing script appropriate to the type ofobservation required e.g., single-dish, single field interferometry, etc. The SB has relatively little influence over
the order in which the various sources are observed and does not describe all of the calibrations that should be
performed (a prime example being the measurements of the system temperatures).
Each SB typically executes set-ups, calibrations, and target observations within 1.5 hours. The end of an SB
may be specified in terms of a maximum amount of time or when certain well-defined science goals have beenreached as specified in the Science Parameters section of the SB. An SB is atomic in the sense that it cannot
be stopped and re-started. Therefore, an SB runs to completion, fails, or is terminated by the Astronomer on
Duty (or AoD). Given the limited length of the SBs, it is often necessary to observe it several times to achieve
1 For a description of Phase 1 and Phase 2 see the Cycle 5 Proposer’s Guide
2 SBs can also be created in an ad-hoc manner for commissioning purposes

109

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Figure 8.1: Block diagram of an Observing Project from the point of view of the observation preparation(top) and internal hierarchical structure of the SB in actual executions (bottom). All projects have the same
ObsUnitSet (OUS) levels, the Science Goal OUS level, the Group OUS level and the Member OUS level.
Scheduling blocks are attached to the Member OUS. Each time a Scheduling Block is executed, Control createsa new ExecBlock structure (see text).

8.2. PROGRAM EXECUTION

111

the required sensitivity. The current maximum time (or end execution) for a particular SB, has been chosen
based on statistical measurements about the stability of the system. A system failure will prevent the online
software from flushing the data into the archive losing the observed project data. Thus, executing SBs formore than two hours becomes unsafe from the operational perspective. To optimize this scheme, a session was
implemented, which is the continuous execution of a single SB until a certain goal has been reached (see detailed
description later on). Sessions have the added benefit that some of the calibrations can be shared among thedifferent elections, which increases the overall observing efficiency. For this cycle, sessions are primarily used
for polarization observations.
If the SB is the smallest entity used for observing, the Observing Unit Set (hereafter OUS) is the smallest
unit for data processing3 . The SB/Member OUS/Group OUS are the smallest structures that hold scienceobservations that need to be observed/processed/combined together. These data hierarchies therefore maximize
observing flexibility and ensure that data gets processed as early and as fast as possible. In the OT, observations
are divided into different Science Goals (see the ALMA Proposer’s Guide). In order to follow this structure,each Group OUS is attached to a Science Goal OUS.
All SBs have to be processed together to produce calibrated science products (e.g. images or data cubes). In
most cases, there will be exactly one SB in each Member OUS, but the latter may hold multiple executions of
this SB. For polarization observations, all the SBs that belong to the same session should be grouped together
for data processing. Unfortunately, this is not explicitly described in the SB.
If the calibrated science observations of a Member OUS have to be combined with science observations ofanother Member OUS, then these are grouped together into one Group OUS. Otherwise, they will be placed into
different Group OUSs. A typical case of Member OUSs that belong to the same Group OUS are observationsof the 12-m Array, the 7-m Array and the TP array. According to the method above, these observations would
be in three separate Member OUSs, but in the same Group OUS.
Pipeline processing happens at the Member OUS level, as soon as all observations of a Member OUS arecompleted (see Chapter 13 for more details). It is expected that in future cycles, processing will also happen at
the Group OUS level, in case the Group OUS contains several Member OUSs which have already been processed.
The only other event that triggers data reduction is the end of an observing season, when all the Member OUSs
and potentially Group OUSs are reduced, irrespective of their degree of completion. As polarization observations
do not currently fit this scheme, the data reduction will be done manually by the ALMA staff.

8.2

Program Execution

Once a given SB has been selected for execution (by the Scheduler subsystem or by the Astronomer on Duty), it isread into the online Control software, particularly by the Science Software Requirements subsystem (hereafter
SSR). The SSR subsystem commands the lower level Control software to create an Execution Block (EB)structure that is attached to the SB. As many SBs will be executed several times, a number of EBs may exist
for a given SB. Each EB contains a record of the parameters and conditions under which the SB was executedalong with references to the acquired data. The internal hierarchical structure of the EB is also shown in
Figure 8.1. The SSR subsystem constructs a sequential series of scans for each of the required calibrations andcommand Control to execute them. Each scan4 execution is in fact carried out by breaking it down into a seriesof subscans, each of which is itself broken into a series of integrations (the correlator software only understands
subscan sequences). Although commands are issued at the scan/subscan level, the correlator output corresponds
to a particular integration. In general, each calibration observation consists of a scan containing several subscans(e.g. the 5 points of pointing calibration constitutes a scan with five subscans). Similarly, the integration time
3 There are two types of OUS, the Member OUS and the Group OUS. Member OUS is the set of all SBs needed to achieve (partof) a Science Goal, and usually it is associated to a specific array configuration. Group OUS contain all Member OUS neededto achieve the science goals of a complete science proposal, and it can include Member OUS corresponding to different ALMA
configurations and/or arrays.
4 A scan is a period of data acquisition that achieves a particular declare OBSERVER INTENT (e.g., TSYS measurement,
pointing determination, science target observations, etc). A subscan is a distinct period of data acquisition collected in support ofa scan (e.g., one pointing offset measurement in a pointing scan; one mosaic pointing of a mosaic scan, etc). Finally, an integrationis the shortest period of data recorded in the data sets.

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CHAPTER 8. OBSERVING MODES

on a single science source between phase calibrations can consist of one scan comprised of a number of subscans.
To optimize the execution, scans may be organized in scan sequences which are passed to Control for execution.
Scans and scan sequences can be of arbitrary length, depending on the characteristics of a given observation.
But subscans are recommended to be 30 seconds or less. Integrations tend to be on the order of 1 to 10 seconds
where the final value has to be an integer multiple of the correlator dump time. These values can be specified
during Phase 2 SBs construction, particularly in the SB target parameters section. Calibration results from theTelescope Calibration subsystem (TelCal) and QuickLook (QL) pipeline are usually attached to a scan where
one example is an antenna pointing result. The SSR and the Control subsystem are responsible for the creationof all the metadata needed downstream for data processing.

8.3

The Observing Process

For a given project, a set of targets are specified in the SB (for more details, see the Cycle 5 OT User Manual).
These targets can correspond to either calibration or science executions. Targets are organized in observing
groups where the first group (group 1) is always the initial calibration group, with subsequent groups detailingthe science observations5 All Science targets and relevant calibrators within a group are observed before thenext group is started. An SB can have multiple groups.
All groups other than group 1 are considered complete when all Science targets in the group have been
observed for the requested time or have set below the elevation limit. After all groups are completed or the SB
execution limit is reached, the primary Phase calibrator for the group which triggered the SB execution time
limit as well as any deferred calibrators from group 1 are observed.
Most observing modes, including single field interferometry, grouped source executions, pointed mosaics,
and polarization use the same ALMA observing script, called the standard interferometry script. The set ofnecessary calibration measurements (e.g. flux, bandpass, etc) usually specified in group 1 are performed at the
beginning of the observation sequence if appropriate sources are available. The sources are selected at run-timeby the SSR query algorithm using the parameters defined in the SB as input. If sources of sufficient quality forcalibration are found the SB will execute.
Pointing, Atmospheric, and Sideband-Ratio calibrations are associated to the main (Bandpass, Amplitude,
Polarization, and Phase) calibrations on an as-needed basis which is determined by the SSR at run-time.
However, pointing is usually verified before the amplitude and bandpass calibrators are observed, and again
before the main observations of the science target and phase calibrator cycle. Within a group, the Sciencetargets are each observed in turn until observation of the primary phase calibrator (the calibrator with shortest
cycle time in the group) is required. A typical cycle time for the phase calibrator may be 7-10 minutes forstandard observations, and 1-2 minutes for long-baseline observations (see Chapter 10). This process is repeateduntil the observing requirements are met, or the SB reaches its time limit. Any additional (secondary) phasecalibrators are observed as specified in the scheduling block. For a description of what each calibration entails,
see Chapter 10.
The user has several options to select optimal calibrators. He/she can let the OT set up default queries
to the Calibrator Database in the ALMA Archive which will be used to select appropriate calibrators at run
time (system-defined calibration in the OT). This is the recommended mode. He/she can also enter specificcalibration sources or set up the queries using alternative values for the parameters, but this carries some risk(for example, calibrators will not be observed during the execution of a group if they are not visible at the timeof the observation), and thus must be fully justified in the Technical Justification of the proposal (user-definedcalibration in the OT).
5 However, this is not strictly correct. Additional calibrations can be added into subsequent groups and they will be interleaved
according to their cycle times. One example is the polarization calibration.

8.4. SINGLE FIELD INTERFEROMETRY

8.3.1

113

The Source Selection Algorithm

The ALMA system calibration for a given scheduling block is done using astronomical sources selected atruntime. To correctly select the appropriate calibration sources, selection criteria were implemented in the SSR
using the following steps:• A list of sources is retrieved from the ALMA catalog based on the query center and the search radiusdefined in the SB.
• For each source in the list there is a check whether there are flux measurements at the SB representative
frequency. If no flux measurement is present, the flux is extrapolated using a spectral index of -0.7 to the
SB representative frequency.
• The flux is weighted based on proximity to the representative frequency, target and time since the lastmeasurement present in the source catalog.
• The returned list of sources that passed the signal to noise criteria are ranked based on source strengthand separation with respect to the query center and flux error.
• The final list is sorted based on ranking.
Using these rules the criteria for all the ALMA calibrations were implemented adding specific requirements
based on the nature of the target, such as:• Bandpass calibrator. The bandpass calibrator integration time defined in the SB (typically 5-15 minutes,
depending on e.g. band and spectral setup) and a number of dynamically determined parameters (e.g.
the number of antennas in the array and the estimated system temperature) are used to determine aflux density threshold for the catalog search that would correspond to a minimum SNR per antenna of
50. If no suitable sources are found, the SNR limit is lowered. Other factors that are taken into accountare elevation and shadowing. The search radius is typically 45 degrees from the query center, but if nosuitable calibrator is found the search radius is increased.
• Phase calibrator. A signal to noise of 15 given is used in the flux estimation. The required integration
time is derived either using the widest spectral window bandwidth (usually 2 GHz), or the integrated
bandwidth when only narrower spectral set-ups are used. A 15 degrees from the query center searchradius is used as default (smaller cycle times and radii are used for the highest frequencies and longest
baselines, as described in Chapter 10. However, the value is taken from the SB and the closest source tothe target, from the selected list, is returned.
• Flux calibrator. A solar system object is searched for first, then the grid cal sources are searched. The
first observable grid source is picked up. A detailed list of the Solar System objects and grid sources used
for flux calibration is available in Chapter 10.

8.4

Single Field Interferometry

Single field interferometry is the most basic form of observation that ALMA supports. It consists of standard
calibration scans associated with the constituent targets, and science observations of a single field (primarybeam). A typical observation will start with a bandpass calibration. The bandpass observation is executed tomeasure the spectral response of the system, and thus should be done on a bright source with simple spectral
properties, such as a bright quasar with no emission or absorption lines and a reasonably flat spectrum.
The flux scale calibration will be taken next, which is intended to obtain the observed flux of a well known
source, such as a solar system object. The observed flux will be used to compare with the established model
fluxes of these objects to obtain the scaling factor to be applied to all other sources in the SB. Ideally theseflux scale calibrator sources should be small with respect to the synthesized beam so as not to resolve the114

CHAPTER 8. OBSERVING MODES

source structure and create uncertainties in the flux calibration. In practice many solar system objects may bemoderately resolved. In such cases only a subset of the antennas may be used to estimate the flux based on
accurate models of the objects available in the analysis software. From this result, a scaling factor is derived
which can then be applied to the data at the data reduction stage. If no solar system object is observable, theSSR will pick the first available grid source.
The interferometer is a device for measuring the spatial coherence function (Clark 1999), the phase information of the sources must be preserved and discerned from phase variations at the individual antenna elements.
This is achieved with the phase calibration during the course of an observation. Since the phase is expected tochange much more rapidly in time than the amplitude, these sources will be observed more frequently than theother calibrators. Because the phase varies on small scales on the sky, the calibrator must be quite close to thescience target. The phase calibration observations are taken before and after observations of the science target,
and the phase correction will be interpolated in time when applying to the science target. As the atmospherefluctuates rapidly (especially at higher frequencies), radiometric observations of atmospheric water lines aredone to correct for these additional phase variations. These corrections can be applied online and offline (seeSection 10.4.2 for further details).

8.5

Pointed Mosaic Observations

Pointed mosaic observations are also offered for this Cycle. This mode enables a single Science Goal to cover a
field of view larger than the primary beam by making observations of multiple single fields that overlap by anamount specified in the proposal. Up to 150 pointings are possible in a single SB. This limitation is set by the
maximum execution time for a single SB and the necessity to finish all fields at least once within an execution.
In pointed mosaic observations, each of the fields will be assigned different field IDs in the data, but the same
source ID. Thus all fields will share their bandpass, amplitude and phase calibrations which are done as single
fields. For larger fields that cannot be covered by 150 pointings, multiple SBs may need to be defined. The
mosaic is arranged as a single scan composed by a number of subscans corresponding to the individual rows in
the mosaic (see Section 5.5). Both the Science target specific last mosaic pointing position and index within
the Science target list are handled by the SSR to ensure the next scan begins on the proper Science target andproper offset position. The mosaic observations can be set up by specifying a Rectangular Field in the OT.
If the user wishes to execute several small mosaics within an SB, the custom-mosaic under Multiple Pointings
should be selected.

8.6

Single Dish (Total Power) Observations

The purpose of adding data from single-dish observations using autocorrelations is to recover large scale emission
from the science target that may have been spatially filtered-out by even the shortest baselines of the 7-m Array.
For this reason, these observations are referred to as zero spacing. For convenience, these observations are also
sometimes referred to as total power (hereafter TP), although in practice they are taken in autocorrelation mode
rather than using a total power (square law) detector. Four 12 m antennas connected to the ACA Correlator
are available for this purpose. For this cycle, only spectral-line observations are offered in this mode.
The observing script that executes this mode is called standard single-dish script. As with standard interferometry, this script uses the SSR capabilities to perform some of the calibrations observations (e.g. pointing)interferometrically. The SB of a TP observation consists of a group of calibrations followed by an On-The-Fly(OTF) observation of a rectangular area on the science target for line mapping with periodic offsets to reference
position for calibration observations. For the OTF and reference position integrations, only the autocorrelation
data will be written to the ASDM to minimize data rate and size, whereas calibrations use cross-correlation
information for analysis.
Most of the calibration scans are executed in group 2. Group 2 can contain pointing observations (if acalibrator is attached to that group and none have been carried out in group 1), and the atmospheric calibrationsat regular intervals, another round of pointing calibration, then a sideband ratio measurement. For the higher

115

8.7. POLARIZATION

frequency bands, a focus calibration is executed next. Then another atmospheric calibration is taken at thereference position of the science target, then the actual OTF map of the science target.
The OTF map is observed as a series of raster rows, scanning in the coordinate system specified in the SB.
In Cycle 5, scans are taken either in longitudinal or latitudinal directions as specified in the OT6 . In later cycles,
scans may be taken in the two perpendicular directions in turn, to minimize scanning effects. The reference
positions, assumed to be positions which are free of emission, are specified either in absolute coordinates oras offsets from the map center. By default, the OTF map will cover an area one half of the full beam larger
than the interferometric observation on all sides. This will ensure that undersampling at the map edges does
not affect the data combination process with the interferometric data. A raster row in these observations isdefined as a subscan, with a maximum length of a scan (consisting of some number of subscans) of 600 seconds.
The reference position is observed as specified by its cycle time during the science target scans. Pointing iscalibrated on a bright calibrator near the Science target with a frequency indicated in the SB, and atmosphericcalibrations are taken every 10 minutes at the reference position to measure the system temperature.
The calibrated TP map of the science target will be in units of Kelvin, on the antenna temperature (T∗a )scale. Since all TP observations are expected to be combined with 12-m and 7-m Array data which come incalibrated units of Jy/beam, the TP data must also be converted into these units. This conversion from Kelvin
to Jy/beam requires knowledge of the main beam efficiency ηmb and the beam size θ. These are measured
separately for each project by obtaining a continuum map of a bright quasar or a planet with known flux7 .
These “amplitude calibration” maps are reduced in the same way as the science observations, then the emission
will be compared with their model or observed flux (taken from the most recent calibrator survey measurementsin the case of quasars) to calculate the Kelvin to Jansky/beam conversion factor, which will then be applied tothe science observations.

8.7

Polarization

The ALMA antennas have receivers with linearly polarized feeds followed by a waveguide with a polarization
splitter8
In this way, the incoming radiation is separated into two orthogonal components (X and Y) which are
down-converted and digitized independently. For each baseline, the digital signals are cross-correlated at thecorrelator where the outputs are the four cross-correlations XX, YY, XY, and YX (or Vxx , Vyy , Vxy , and Vyx ).
These four cross-correlations, as a function of the Stokes parameters, are ideally given by

Vxx = I + Q(8.1)

Vxy = U + iV

(8.2)

Vyx = U − iV

(8.3)

Vyy = I − Q(8.4)

where I, Q, U , and V are the Stokes parameters. In an ideal world, one would be able to combine the crosscorrelated visibilities and recover the Stokes parameters as,
6 The minimum time per row in a map is 3 sec, and maximum speed at which data can be taken is usually limited by thecorrelator.
7 It is expected that during Cycle 5, these measurements will only be needed for the high-frequency ALMA bands, while forbands up to Band 7, the values will be automatically derived from fits to the aperture efficiency of each antenna as a function oftime, elevation, outside temperature, surface accuracy, etc., which will be regularly monitored by the observatory.
8 For the ALMA receiver bands offered in polarization mode in Cycle 5, Bands 3, 4, 5 and 6 the polarization splitter is an
Ortho-Mode-Transducer (OMT), and for Band 7 it is a polarized grid.

116

CHAPTER 8. OBSERVING MODES

Vxx + Vyy
2
Vxx − Vyy
Q=
2
Vxy + Vyx
U=2
Vxy − Vyx
V =
2i
I=

(8.5)
(8.6)
(8.7)
(8.8)

From here, it is easy to see that the total intensity is in Stokes I (function of the parallel hands XX andYY), and the linear polarization is described by Stokes Q and U ; while circular polarization is described by
Stokes V . However, there are a number of issues that prevent directly using the measured cross-correlation inthis simple way.
1. The splitting of the incoming radiation into orthogonal components is not perfect and small projectionsof one component into the other are produced. This is called the instrumental polarization or D − terms.
The instrumental polarization is an antenna based quantity which also depends on the frequency andthe band (cartridge design and external optics). Additionally, this quantity is measured in the frame of
the antenna which is an elevation and azimuth frame (Alt/Az) and thus, it rotates with respect to theframe of the sky. This rotation introduces an angular dependance into the visibilities as a function of theparallactic angle (ψ). By design, the instrumental polarization is small (a few percent), but not negligible.
2. The signal path followed by each of the individual X and Y polarizations is slightly different, which
introduces a small delay in the signal that needs to be accounted for. It has also been observed that theusage of the different local oscillators also introduces an offset in the XY-Phase.
3. The usual off-line calibration procedure arbitrarily sets the phase of a reference antenna to zero; thisresults in the inverse of its X-Y offset being imprinted on the cross-hand phases of the other antennas.
4. Other effects, such as position within the primary beam (off-axis polarization), are still under commissioning. Thus, only on-axis polarization is offered for Cycle 5 (see below for a detailed explanation.)
By taking into consideration the instrumental polarization and the parallactic angle dependence, the equations for the visibilities can be re-written as

VXX = (I + Qψ ) + (Uψ + iV )d∗Xj + dXi (Uψ − iV ) + dXi (I − Qψ )d∗Xj(8.9)

VXY = (I + Qψ )d∗Yj + (Uψ + iV ) + dXi (Uψ − iV )d∗Yj + dXi (I − Qψ )VY X = dYi (I + Qψ ) + dYi (Uψ + iV )d∗Xj + (Uψ − iV ) + (I − Qψ )d∗Xj
VY Y = dYi (I + Qψ )d∗Yj + dYi (Uψ + iV ) + (Uψ − iV )d∗Yj + (I − Qψ )(8.10)(8.11)(8.12)

where dXj are the D −terms as a function of polarization and antenna, the asterisk denotes complex conjugates,
and Uψ and Qψ are the Stokes parameters as a function of the parallactic angle. Figure 8.2 shows an example
of D − terms at Band 3. The D − term level is typically a few percent at Bands 3, 4, 5, 6, and 7 on axis TBC
with some variations over frequency9 . Without any D − term calibration, an unpolarized source may appear
to be polarized at the 1% level. The most straightforward way to calibrate the D − terms is to observe an
unpolarized source. The cross-hands output will be purely D − terms since Stokes Q, U, and V will have nosignal. However, bright unpolarized sources are rarely found.
ALMA therefore normally uses an unresolved quasar as a polarization calibration source. These are monitored to ensure they are bright enough, and the exact polarization is determined during data reduction provided
9 A resonance has been documented for Band 6 between the feed and the OMT. This resonance introduces a small ripple in the
D-term solution which increases the leakage amplitude by a small amount, but still only a few percent.

8.7. POLARIZATION

117

Figure 8.2: The D − term plots of DA42 (top), DV03 (middle), and PM01 (bottom). The vertical axis is thefraction of the input signal voltage in one polarization that leaks into the output of the other polarization involtage units and the horizontal axis is the frequency in MHz. The blue and red symbols represent DX (thefraction of Y polarization signal that leaks into the X polarization) and DY (the fraction of X polarization signalthat leaks into the Y polarization), respectively.

that the source is observed over a wide enough range (> 60◦ ) of parallactic angles to separate the effects of thesource polarization, the D − terms and the cross-hands phase spectra and delay. Fig 8.3 shows that the rateof change of parallactic angle is fastest near transit and slowest for low elevation sources. The D − terms may
have a slight elevation dependence, and therefore it is favorable for the polarization calibrator to be close to
the science target. The ALMA Observatory will choose appropriate calibrators, but the users must take into
account these limitations when planning the observation.
With the current calibration scheme, linear polarization imaging of a compact source on-axis, at the level of
0.1% in fractional polarization is feasible. The accuracy of absolute polarization position angle will be nominally
6 degrees (based on initial polarization mode verification results), with a contribution of 2 degrees coming fromthe specification on the orientation of the receiver feeds, and an additional scaling of the error with the numberof antennas in the final image. Of course, these levels of accuracy will only be reached if there is sufficient signalto-noise in the polarised emission. Although a Stokes V (circular polarization) image can be produced with
reduction and analysis software (CASA), this capability is still under commissioning. The ALMA Observatory
cannot guarantee the accuracy of Stokes V images at the current cycle. Thus, the users may investigate the
Stokes V emission at their own risk.
As the D − term component also arises from the off-axis geometry of feed horn, antenna illumination, andthe alignment of optics, it will also vary across the primary beam pattern. Generally, the D−term level becomeslarger when increasing the offset from the beam center. This is so-called off-axis instrumental polarization. In
Cycle 5, the off-axis instrumental polarization calibration will not be employed. In Cycle 5, polarization imaging
with accuracy better than 0.3% can be achieved within the inner 1/3 of the primary beam FWHM and thisdetermines the largest acceptable angular size of sources which can be observed in full polarization. Users mustjustify that their science goals can be met by sources exceeding these lower limits (of 0.1% polarization for apoint source in the center of the field or 0.3% within up to the inner 1/3 of the FWHM).
For this cycle, polarization observations have been extended to FDM correlation mode at arbitrary frequencies and frequency resolutions within three of offered Bands (3, 6, and 7). For the two bands for which weoffer polarization observations for the first time in this Cycle, i.e. Bands 4 and 5, the observations will only
be possible at the following frequencies: Band 4: 127, 129, 139 and 141 GHz, and Band 5: 196, 198, 208, 210
GHz, respectively. Figure 8.4 shows the D-term solutions of a representative antenna (DV22) obtained duringcommissioning. Figure 8.5 shows a zoomed-in view in frequency of the D-term solutions shown in Figure 8.4.
These figures show that the spectral shape of the D-term solutions is smooth and no spur like structure is seen

118

CHAPTER 8. OBSERVING MODES

100
80

parallactic angle [deg]

60
40
20
0
-20
-40
DEC=30 deg
DEC=10 deg
DEC=-10 deg
DEC=-30 deg
DEC=-50 deg

-60
-80
-100
-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

source hour angle [hr]Figure 8.3: Parallactic angle (ψ) plot as a function of hour angle for the declination of 30, 10, -10, -30, and -50
degrees.

even in highest frequency resolution mode (30.5 kHz at the right bottom panel of Figure 8.5). Figures 8.4 and
8.5 clearly demonstrate that the instrumental polarization is mostly spectral resolution independent for thesedatasets. No mosaic, ACA, circular polarization and TP Array observations are offered. Further, a minimum
execution time of 3 hours will be imposed to ensure sufficient parallactic angle coverage for calibration.

8.7.1

Sessions

Though not directly related to polarization iteself, sessions are the observing scheme designed to observe polarization projects with ALMA. In order to allow the execution of long programs and to avoid the execution oflong scheduling blocks (more than 1.5 hours), the concept of a session was implemented into the SSR. Given thecurrent stability of the system, it was considered an unnecessary risk to have more than 1.5 hours scheduling
blocks, because in the event of a crash all data are lost. Thus, a session scheme was designed as an alternative.
A session is defined as the continuous execution of the same SB until the scientific criteria are met. A session
will manage the cycle time of each of the calibrators from the starting point of the session, i.e. the first executionof the SB. In this way, calibrations are only executed when needed avoiding unnecessary observations giving an
additional level of optimization for ALMA. By default, calibrations such as flux calibration will be done once
per project and bandpass every hour saving observing time. Also, the phase calibration science target loop
will be interrupted (preserving phase calibration) when an additional calibration is-needed (e.g. polarization)10
The current mode for sessions in ALMA is the observation of polarization projects. Because for an Alt/Az
antenna the frame of the sky rotates, the calibration of the instrumental polarization requires sampling a strong
compact source as a function of parallactic angle approximately every 30 minutes. The session will remember
the last time the polarization calibrator was observed and interleave the calibration when needed. In general,
one can achieve the parallactic angle coverage by running the polarization SB 2 or 3 times, which will give
between 3 to 4 hours of observation, which is a perfect example of the session scheme. Other cases in which
the session scheme might be useful are large mosaics, surveys (multi-target), and large single dish raster maps,
but those cases are not offered in session mode for Cycle 5. The implementation of sessions is done by keeping
information in memory about the previous execution of the SB. This is done through an interface provided byControl software to access a persistent component which is used to store and retrieve this information.
10 The cycle time parameters are user controlled and can be explicitly specified in the OT target parameters section.

8.8. MULTIPLE REGION MODES

119

Figure 8.4: A frequency vs real part of the D-terms plot for an antenna (DV22) obtained towards J0522-364.
Blue circles and red crosses are showing the D-term obtained using a setup of FDM with 2 GHz bandwidth andusing a setup with higher spectral resolutions (FDM 500 and 62.5 MHz bandwidth respectively). Four panels
show the D-terms obtained from the SPW 0, 1, 3, 2 (from top left, clockwise).

8.8

Multiple Region Modes

In the frequency division modes (FDM) of the correlator (see Sectionr̃effdm-mode), the final spectrum is synthesized using individual filters 62.5 MHz wide. In multiple region modes, when the total bandwidth is between
125 MHz and 1 GHz, it is possible to move these individual filter positions to create spectral windows covering
a number of disjointed spectral regions. This is called the Multiple Region Modes. The constraints are:
• The spectral window width must be a multiple of 62.5 MHz.
• The aggregate width of these spectral windows must be equal to that of the original bandwidth selected.
• The spectral windows must all fit within the 2 GHz baseband used.
• The other parameters (resolution, polarization and sensitivity options) must be the same for all spectral
windows.
This mode is useful when a number of line features which require high spectral resolution are spread acrossthe IF bandwidth. Since the filters have a unit width of 62.5 MHz, if the user chooses a mode with 250 MHz
total bandwidth, it is possible to place four separate windows, each with 62.5 MHz width, anywhere within the
2 GHz baseband. In Cycle 5, a maximum of four spectral windows per baseband will be offered.

8.9

Observation of Ephemeris Objects

Observation of solar system objects (with the exception of the Sun) is supported as in previous cycles. Several
well known solar system objects including planets, satellites and asteroids can be selected from a pulldown
menu in the Observing Tool. For other sources including non-sidereal objects, an external ephemeris file can besupplied as an input. The ephemeris file must be in JPL Horizons format. A typical ephemeris file may consistof the date (time), Right Ascension, Declination, range and range rate, for example:

120

CHAPTER 8. OBSERVING MODES

Figure 8.5: A close-up view in frequency space of the real part of D-term shown in Figure 8.4. Blue circles andred crosses are showing the D-terms obtained from setup #1 (FDM, 2 GHz bandwidth) and setup #2 (FDM,
500 and 62.5 MHz bandwidth respectively).
*******************************************************************************
Date__(UT)__HR:MN
R.A._(ICRF/J2000.0)_DECdelta
deldot***************************************************************************
2012-Jun-26 13:00
06 22 57.33 +23 16 11.23 1.01653182506561 -0.2593303
2012-Jun-26 13:01
06 22 57.49 +23 16 11.14 1.01653170585632 -0.2583150
2012-Jun-26 13:02
06 22 57.66 +23 16 11.05 1.01653158664703 -0.2572937
2012-Jun-26 13:03
06 22 57.82 +23 16 10.96 1.01653146743774 -0.2562665
2012-Jun-26 13:04
06 22 57.98 +23 16 10.84 1.01653134822845 -0.2552333
2012-Jun-26 13:05
06 22 58.14 +23 16 10.74 1.01653122901917 -0.2541942
2012-Jun-26 13:06
06 22 58.30 +23 16 10.66 1.01653122901917 -0.2531491
More information on the format and precision needed is available in the ALMA Observing Tool documentation.

8.10

Solar Observations

Solar observing was part of the original science case for ALMA. It has recently been thoroughly tested andverified and released for PI science observations. In Cycle 5, solar observing with ALMA will be supported,albeit with limitations. In particular, the following conditions apply to solar observing in Cycle 5:• Only Band 3 and Band 6 continuum observations using the following default frequencies are offered*******************************************************************************
LSB
USB
Band
LO Freq.
BB1
BB2
BB3
BB4
*******************************************************************************
3
100 GHz
92-94 GHz
94-96 GHz
104-106 GHz
106-108 GHz
6239 GHz
229-231 GHz 231-233 GHz 245-247 GHz 247-249 GHz• Interferometric observations must be done using the TDM mode (see section 5.1.1); frequencies are fixed
to 2 GHz-wide spectral windows centered on the frequencies shown in the table above. The spectral-line
FDM observing mode is not offered for solar observations (Section 5.1.2).
• Simultaneous observations with Bands 3 and 6 are not offered: each execution block can only include one
band.
• Observations will be carried out while the array is in a compact configuration corresponding to C43-1, 2,
or 3.

8.10. SOLAR OBSERVATIONS

121• Because the WVR receivers are saturated when dishes point at the Sun, on-line WVR phase correction
will not be applied and off-line WVR correction for on-source (solar) data is not possible.
• Interferometric observations will use a combined array comprising both 12 m and 7 m dishes and will beprocessed with the baseline correlator (Section 5.1).
• To minimize shadowing of 7 m antennas, observations will be carried out between 13:00 UT and 20:00
UT.
• Mosaicing of larger FOVs can be carried out with up to 150 different pointing offsets relative to the phasecenter specified in the ephemeris, typically in a rectangular pattern.
• One target (one ephemeris file) is allowed for each science goal.
• A single observation (an execution block) cannot exceed 2 hours, which will include the time overheads
for bandpass and flux calibration. These calibration overheads amount to about 25 mins.
• The integration time of interferometric observations is fixed to 1 seconds.
• Observations may be performed using dual linear polarization (XX, YY) or single polarization (XX)correlations; full polarization measurements are not currently offered for solar observations.
• Total-power full-Sun fast-scanning single-dish observations are offered as context and to recover the largest
angular scales for interferometric observations; proposals requesting only total-power single-dish observations will not be accepted in Cycle 5.
• Single-dish total-power mapping will be “monomode” (double-circle scan pattern) with a 2400 arcsecdiameter circular FOV centered on the solar disk (see below).
• Single-dish full-Sun will not be executed when the Sun is at elevations above 70o because the required
fast-scan azimuth slew speeds are too high.
• The time cadence of full-sun images obtained from total power observations is fixed to about 7 minutes
for Band 3 and 10 minutes for Band 6.

8.10.1

Solar Observing Modes

Solar observations with ALMA are possible because the surface of the antennas are designed to scatter the
optical and IR radiation to an extent that the subreflector and other elements in the optical path are notdamaged or degraded. However, additional steps must be taken to allow useful observations of the Sun to be
made. ALMA receivers are designed for a maximum RF signal corresponding to an effective brightness of about
800 K at the receiver input. Since the quiet Sun has a temperature of ∼5000-7000 K at ALMA frequencies, thesolar signal must be attenuated or the receiver gain must be reduced to ensure that receivers remain linear, or
nearly so.
The initial solution adopted by ALMA was the use of a “solar filter” (SF) that is mounted on the Amplitude
Calibration Device (ACD) of each antenna (Section A.5). When placed in the optical path the solar filter isrequired to attenuate the signal by 4+2λmm dB with a return loss of -25 dB (-20 dB for ν > 400 GHz) and across polarization induced by the filter of -15 dB, or less. While the use of solar filters has been demonstrated
to work, their use introduces several disadvantages, not least of which are cumbersome calibration procedures.
Yagoubov (2013b, 2014) pointed out that the ALMA SIS mixers could be de-biased to reduce the mixer gainand effectively increase the saturation level to a degree that allows solar observations without the use of thesolar filters, at least for non-flaring conditions on the Sun. These produce lower conversion gain and since thedynamic range scales roughly inversely with gain, these settings can handle larger signal levels before saturating.
In addition to the SIS bias voltage, the local oscillator (LO) power can be altered in order to further modify
the receiver performance. However, LO power settings have not yet been fully optimized for solar observing.
Two so-called “mixer de-tuned” or “mixer de-biased” settings have been adopted for solar observations inBand 3 and Band 6 for Cycle 5. These are referred to as solar observing modes MD1 and MD2.

122

CHAPTER 8. OBSERVING MODES• Band 3: MD1 mode uses a bias voltage that sets the SIS mixer to the 2nd photonic step below thevoltage gap whereas MD2 mode employs a bias voltage corresponding to the 2nd photonic step above thegap. For MD1 mode, the Band 3 receiver temperature suffers a modest increase, to ∼50 K, and receivercompression is limited to ∼10%. For MD2 mode, however, the Band 3 receiver temperature increases
significantly, to 800 K, but receiver performance is believed to be essentially linear.
• Band 6: MD1 mode settings are nominal for ALMA; i.e., the bias voltage is that used under normal
observing conditions. Receiver compression is again on the order of ∼10%. MD2 mode employs a bias
voltage corresponding to the 1st photonic step above the voltage gap. Again, the receiver temperature issignificantly higher, 800 K, but the receiver is essentially linear.
The MD1 mode is considered to be a “quiet Sun” mode (coronal holes, the solar limb, quiescent filaments, prominences, quiet areas outside of active regions) whereas the MD2 mode isrecommended for the “active Sun” (active regions, active filaments, science objectives that require
accurate photometry).

8.10.2

Array Observations

The Sun is an extremely large source compared with the primary beam of either the 7 m or 12 m antennas.
The primary beam of both antennas is filled with complex emission when pointing at the Sun, as are the beamsidelobes. The ALMA array ultimately measures the brightness temperature contrast relative to the background
Sun, which is resolved out by the array. As noted earlier, in order to recover the absolute brightness temperatureof solar targets, it is necessary to include not only interferometric observations (by the 7 m and 12 m antennas),
but also total power measurements made with a single dish. Single dish fast-scan mapping of the Sun in total
power mode is addressed in the next subsection.
An advantage to using MD mode observing is that the water vapor radiometers (WVRs), which are used tocorrect differential phase errors introduced by precipitable water vapor over the array, are not blocked by the
ACD. They can therefore be used, in principle, to make such corrections to solar data. Unfortunately, unlessthe optical depth of the sky is ∼2.5 or more, which would represent highly non-optimum observing conditions,
the WVRs saturate on the Sun. Until the WVRs are modified or replaced to increase their dynamic range
to accommodate the Sun, phase corrections based on WVR measurements will not generally be possible whenpointed at the Sun. For this reason, solar observations are currently restricted to compact array configurations
to minimize such phase errors.
Another consideration, again regardless of whether SFs or the MD modes are used, is the system IF attenuatorsettings. The input power changes significantly as the antennas move from the (solar) source to a calibrator andback. The IF chain has two variable attenuators (in steps of 0.5 dB) to ensure that signal levels remain within
nominal limits: one in the IF Switch and one in the IF Processor. A concern is whether the variable attenuatorsthemselves introduce unacceptable (differential) phase variation between source and calibrator settings, thereby
corrupting phase calibration referenced against suitable sidereal calibrators; and whether there are differences
between the spectral window bandpass response between source and calibrator scans as a result of attenuatorsettings. Careful testing has shown that this should not be a significant concern. While these tests show thatphase shifts caused by the attenuation level changes do in practice difference out, verification that this is the casecannot be checked from observing data obtained using the solar scheduling block. As a check, the observatory
will carry out a test observation of a calibrator source using normal and MD attenuation levels before solar
observations begin on a given day or at least once before a campaign program.
Bandpass calibration is carried out in the usual manner using MD modes: i.e., a strong calibrator is observedin an MD mode and the bandpass solution is obtained. Bandpass shape and stability were checked for MD
modes and attenuator states in Bands 3 and 6. It was found that perturbations to bandpass amplitudes andphases were small. For the IF switch and IF processor settings adopted for MD mode observing it was foundthat the rms difference between bandpass phases for an MD attenuator state and the nominal attenuator state
was generally a fraction of a degree for both Band 3 and Band 6, the maximum being 1.2 deg. Similarly, thenormalized amplitude difference was typically a fraction of 1%. No explicit correction for differential bandpass
is needed.

123

8.11. VLBI OBSERVING MODE

In the non-solar case, the antenna temperature (Tant ) is small compared to the system temperature, andTant can therefore be neglected for amplitude calibration. In contrast, unlike most cosmic sources, the antenna
temperature of the Sun is large (∼7000 K at 100 GHz). It is therefore necessary to measure both the systemtemperature and the antenna temperature when pointing at the Sun in order to compute the System Equivalent
Flux Density (SEFD) to correctly scale visibility amplitudes.
To estimate the antenna temperature Ta∗ on the Sun, “single-dish” measurements must be performed using
all antennas of the array. Specifically, the standard observing sequence for solar interferometric observations
will include the following measurements:• a “sky” observation Psky , offset from (by typically 2o ) and at the same elevation as, the target (Sun)• a “cold” load observation Pcold (also known as the “ambient” load), in which an absorber at the temperatureof the thermally-controlled receiver cabin (nominally 20 o C) fills the beam path
• a “hot” load observation Phot , in which an absorber heated to ∼70 o C fills the beam path
• a “zero” level measurement Pzero , which reports the levels in the detectors when no power is being supplied
Then the telescope moves to the target (Sun) where the IF attenuation levels are set appropriate to the input
power. After the target scan, the telescope again moves to the “sky” position and takes another measurement,
called the “off” measurement Pof f , without changing the IF attenuation.
The antenna temperature of the science target is then given by:Ta∗ = (Psun − Pof f )(Psky − Pzero )(Thot − Tcold )(Pof f − Pzero )(Phot − Pcold )The autocorrelation data output from the baseline correlator cannot be used for this measurement because
it has insufficient dynamic range to measure Pzero . Instead, the necessary measurements rely on total power
data obtained by the baseband detectors.

8.10.3Single Dish Mapping

Fast scanning observations are ideal for recovering the flux or brightness distribution on angular scales ranging
from the ALMA primary beam width to the scale of the target in question (typically a few arcminutes), or up to
the full disk of the Sun. Briefly, fast-scan mapping entails making total power (and more recently, autocorrelation
measurements) as the telescope pointing is driven continuously and smoothly through a sampling pattern on
the target that avoids sudden acceleration or deceleration of the antenna drive motors. A major advantage offast scanning is that it minimizes the impact of atmospheric variation, and the full solar disk can be mappedin as little as 7 minutes.
While various types of scan patterns have been developed and tested for ALMA dishes, Cycle 5 supports
the use of a “double circle” pattern, which maps a circular region on the sky. The double-circle pattern isparticularly well suited for full-disk mapping because its coverage matches the shape of the solar disk and it
repeatedly revisits the region of the center of the disk, allowing atmospheric opacity variations to be corrected.
Standard observing procedures include focus and pointing checks on suitable sources prior to the fast-scan
mapping.

8.11

VLBI Observing Mode

The Very Long Baseline Interferometry (VLBI) Observing Mode (VOM) is a variant of the standard interferometry mode with some additional capabilities to allow ALMA to participate in global VLBI networks operating
at millimeter and submillimeter wavelengths. Since Cycle 5, ALMA VLBI mode observing will be offered

124

CHAPTER 8. OBSERVING MODES

Figure 8.6: Left: Schematic illustration of a double-circle scan pattern used to map the full disk of the Sun.
Actual patterns sample the source more densely to ensure that it is no less dilute than Nyquist sampling.
Right: Example of a fast-scan map of the Sun obtained in Band 6.
in Band 3 in conjunction with the the Global Millimeter VLBI Array (GMVA)11 and in Band 6 in conjunction with the Event Horizon Telescope (EHT) network12 . For details about proposing for these opportunities,
see the ALMA Cycle 5 Call for Proposals See https://science.nrao.edu/observing/call-for-proposals/
1mm-vlbi-cycle5/ .
For all VOM observations in Cycle 5, ALMA will be operated as a phased array of 12 m antennas (mostlikely containing between 35 and 43 phased antennas). For example, with 37 12 m antennas, this is an equivalentdiameter of 73 m. From Section 9.2.1, Table 9.3 the aperture efficiencies in Band 3 and Band 6 are 0.71 and
0.68, and Tsys is 70 K and 100 K, respectively. Since Gain ≡ Aeff /(2kB ) and SEFD ≡ Tsys /Gain,
Gain
SEFD
Gain
SEFD

= 0.71π(36.52 ) × 10−26 = 1.08 K/Jy
= 65 Jy= 0.68π(36.52 ) × 10−26 = 1.03 K/Jy
= 97 Jy(Band 3)
(Band 6)Note that the VOM is not compatible with the use of subarrays.
When ALMA is operated as a VLBI station, all standard interferometry data products are also output by the
ALMA correlator. Therefore during any VOM execution, an observer simultaneously obtains data equivalent
to a standard ALMA interferometric observation of the science target, in addition to the VLBI data products.
The latter are recorded independently on Mark 6 VLBI recording systems and will be shipped to common sites(MIT Haystack Observatory and MPIfR Bonn) for correlation with the other VLBI site data before delivery to
the PI (see below). Some important details of the VOM are elaborated in the next subsections.

8.11.1

General VLBI Considerations

The supporting VLBI networks (i.e., the GMVA for Band 3 and the EHT for Band 6), together with ALMA,
place certain restrictions on the observing process; these are largely driven by the complexity of orchestrating thesimultaneous, reliable execution of a common VLBI schedule, as well as seeing to the calibration requirementsof the individual telescopes that comprise the global array. In practice, for the ALMA VLBI observer there will
11 See http://www3.mpifr-bonn.mpg.de/div/vlbi/globalmm/
12 See http://www.eventhorizontelescope.org/

8.11. VLBI OBSERVING MODE

125

be very little difference between planning an observation in the two observing bands, aside from a few minor
details (i.e. differing bandwidths and frequencies).
Successful proposals will be passed to a network Scheduler who builds the common VLBI schedules (encoded
in a so-called VLBI EXperiment, or VEX file built with SCHED13 ) for a particular observing campaign. In theseschedules, some number of contiguous hours will be devoted to each set of science targets and necessary VLBI
calibrators.
The schedule will be worked out between the Scheduler and the PI well in advance of the observation. Mostsites participating in the VLBI network also have a “friend” of VLBI who assists the Scheduler in working out
details specific to that site. Schedules from previous campaigns are available from the aforementioned GMVA
website and it is expected that schedules for Cycle 5 with ALMA with either the GMVA or the EHTC will besimilar.
In general, the required time on the VLBI science target(s) and VLBI calibrators will be broken into a
number of VLBI scans of several minutes duration, separated by gaps on order of several minutes to allow
time for local calibrations (pointing, system temperature measurements, etc.) and antenna slew time sufficient
to meet the needs of each observatory. VLBI observations that include ALMA will require that the gaps
between VLBI scans are of sufficient length to allow for the performance of the calibrations normally required
for standard interferometric observing, including flux, gain, bandpass, and polarimetric calibrators (see below).
Since all VLBI science targets for Cycle 5 are required to be sufficiently bright to allow phase self-calibration(≥500 mJy), observations of a gain calibrator will be required only every 20-30 minutes to allow calibration of
the amplitudes.
It is important to recognize that most VLBI stations currently record circular polarization (either left,right or dual), in contrast to ALMA which records dual linear polarizations. Consequently, every VLBI mode
observation with ALMA must treated as a polarization observation in order that a transformation from linear
to circular polarization can be made correctly during post-correlation processing. A special tool, PolConvert
has been written to be used with the standard VLBI correlation software, DiFX14 , which converts ALMA data
to a circular basis, greatly simplifying the analysis. In particular, this requires a minimum session duration of
3 hours (session length, not time on science target) in order to achieve adequate parallactic angle coverage on
the polarization calibrator sources for the computation of polarimetric “leakage” or D terms.
Aside from differences in polarization, other VLBI observatories all have receiver capabilities that differ
substantially from ALMA, especially with regard to bandwidth. In particular, none of the GMVA and EHT
sites are currently able to match ALMA’s full recording bandwidth. An additional complication is that the
sample rate used at ALMA is non-traditional for VLBI, so some care must be taken in the experiment set-up
to ensure that the VLBI data can be correlated with the other stations. The VOM spectral set-ups chosen foreach band in Cycle 5 were selected to address these constraints and are therefore fixed. For Band 3 (at 3mm)
there are 4 1.875 GHz bands centered at 86.124, 88.124, 98.124 and 100.124 GHz, respectively. The GMVA sites
will be tuned to a 256 MHz band centered on 86.124, so only the first band is available for VLBI. In Band 6(at 1mm) the bands are centered at 213.1, 215.1, 227.1 and 229.1 GHz, respectively. For Cycle 5, the EHTC isplanning to offer 64 Gbps recording at all sites and will therefore be able to record all four bands and matchfor the first time ALMA’s full frequency coverage and bandwidth.
Calibration of VLBI data generally requires observations of VLBI calibration targets interleaved with themain science target. At ALMA, these VLBI calibration measurements will be carried out in a manner analogous
to the observations of the science targets (i.e., using the VOM and active phasing of the ALMA array). The VLBI
calibrators are generally chosen for their utility across the entire global array to meet a particular calibrationneed (e.g., fringe-finding, bandpass calibration, polarization calibration) and need not be the same calibrators
as observed for calibration of the (ALMA-only) standard interferometry data.
In a VLBI observation, the observatories are usually not connected by any network, so recordings (ontodisk modules) of the antenna baseband signals are forwarded to common correlation facilities (managed by theappropriate network, i.e. MPIfR Bonn and MIT Haystack Observatory under arrangements with ALMA) whichtake responsibility for the correlation of the VLBI data. Correlated VLBI data products will then be made13 http://www.aoc.nrao.edu/software/sched
14 http://www.atnf.csiro.au/vlbi/dokuwiki/doku.php/difx/start

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available to the observer (and uploaded to the ALMA Archive), as discussed in Section 8.11.2.

8.11.2

ALMA Considerations for VLBIAs mentioned in the previous section, all VOM observations should be viewed as polarimetric observations. The
reader is referred to Section 8.7 for guidance on this.
In order to participate in a VLBI observation, there are two special requirements at ALMA. The first isthat the ALMA control system must tune receivers appropriately and point to the targets specified in the VEX
schedule at the appropriate times. The second is that the signals from the ALMA antennas must be coherently
summed, decimated, and recorded on media suitable for delivery to the common VLBI correlator. In order toform this coherent sum, the (arbitrary) phases of the signals at the antennas need to be adjusted during theobservation so that they can be added “in phase”. The necessary signal processing for this takes place within
special cards and circuitry within the ALMA correlator as well as with special software within the ALMA
control system which were developed by the ALMA Phasing Project (APP)15 Details of this are presented in
the following sections, with particular emphasis on those aspects which are essential either for the proposer
or data analyst to be aware of. It begins with a discussion of the VOM Scheduling block in the next section,
followed by information about the scan sequences used by the VOM. That is followed by a section with some
important details about how the ALMA Phasing System (APS) works (Section 8.11.2). Finally Section 8.11.2
makes a few comments about the analsys of VLBI data (a full discussion would be considerably outside thescope of this document).
VLBI Observing Mode Schedule Block and Execution
As with other modes, VOM observations are executed with a scheduling block which provides observationspecific details to an SSR observing script. In the case of the VOM, the script is called StandardVLBI.py,
although, as noted elsewhere, VLBI is a non-standard observing mode in Cycle 5.
The scheduling block is created from the observing project and the VEX file using a special tool called
VEX2VOM. This tool reconciles the Phase II schedule block with the schedule and targets specified in the VEX
file and thus provides the detailed operating instructions for the SSR observing script. The preparation of the
final schedule block with VEX2VOM is done by the Friend of VLBI or the AoD prior to execution when all thenecessary details of the observing array are known.
Like the StandardInterferometry.py script, the StandardVLBI.py ensures that the necessary calibrations
as specified by the OT are performed with the desired repetition rate. Unlike the StandardInterferometry.py
script, it must give precedence to the scheduled VLBI scans which need to occur at the appointed times. As
mentioned above in Section 8.11.1, the VEX file will have provided gaps of various durations which are in fact
created to allow the observing script to make these ALMA-specific calibration observations. Thus the scriptorganizes its work by first noting when the next VLBI scan will occur and then noting which calibrations might
fit into the time until the VLBI scan and finally executing those that fit. The VLBI scans in the VEX fileinclude a start time specified in so-called VEX time format, YYYYyDOYdHHhMMmSSs, so the next result
from an execution perspective is something similar to:
perform initial ALMA calibrations
VLBI Scan 2016y089d07h00m00s on Target-X for 300s
perform some ALMA calibration
VLBI Scan 2016y089d07h10m00s on Target-X for 300s
perform some ALMA calibration
VLBI Scan 2016y089d07h20m00s on Target-X for 300s
perform some ALMA calibration
VLBI Scan 2016y089d07h30m00s on Target-X for 300s
perform some ALMA longer calibrations
15 An NSF MRI/ALMA development fund project.

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8.11. VLBI OBSERVING MODE

VLBI Scan 2016y089d07h50m00s on Target-X for 300s
perform some ALMA calibration
VLBI Scan 2016y089d08h00m00s on Target-X for 300s
. . .
perform final ALMA calibrations
VLBI Scan Sequence
The VEX file specifies the observations in terms of VLBI scans which begin and end at some appointed times.
The VOM translates this request into a sequence of (ALMA) correlator scans which typically start prior to thespecified time in order to allow the phasing system to stabilize on a good solution. Each of these correlatorscans appears in the ALMA meta-data, and is processed by the telescope calibration system (TelCal) according
to the specified intents. The relevant ones for this discussion are intents for phasing and for WVR correction.
The phasing intents direct TelCal to calculate the phases of the signals (i.e.effective area of the signals ofeach polarization in each band of each antenna) relative to those of a designated “reference” antenna. These
phases are calculated from “channel average” data products calculated within the correlator. Typically there
are several channel averages calculated during one of these correlator subscans; see below. With those phases
known, commands are issued to the tunable filter banks (TFBs) within the station cards in the correlator toadjust the antenna phases by exactly the computed values so as to bring all signals into phase with those of thereference antenna. Once these adjustments have been made, a “residual” phase correction typically needs to bemade on the following correlator scan, and indeed, such corrections continue to be made every scan until theend of the recording. The phasing loop is closed in the sense that small errors in the phase adjustments may becorrected on subsequent scans. This is the so-called “slow” loop which is illustrated schematically in Figure 8.7.
VLBI Scan

Record On...

Correlator Scan Sequence...
TelCal Solving...
TFB Commands...
WVR Data...
Unphased∆

Phased∆Phased∆PhasedTime

Figure 8.7: VLBI Scans in the Phasing System. Each VLBI scan is partitioned into “subscans” for correlation
and “slow” timescale processing (seconds)in TelCal. WVR adjustments are made in the CDP on a “fast” timescale(every second). See text for full discussion and explanation.
While the correlator scans are shown as time-contiguous in Figure 8.7 (green bar), there are in fact small gaps
to allow the data to be dumped out for subsequent correlator processing. Even so, the solutions from TelCal(purple) do not arrive at the TFBs (red) until after the correlator scan has started—the time of application
is noted and the early part of the scan is excluded from the subsequent phase calculation. Usually one phaseapplication is needed to get an acceptable solution, so the recording should start no sooner than the start of
the third correlator subscan. These parameters are all programmable, and judicious choices for them are madewhen the schedule block is created. For Cycle 5, the subscans are likely to be 16 s long with 4 s (channel
average) integrations; there are then about 30 s of observations prior to the start of the recording. Note that

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CHAPTER 8. OBSERVING MODES

the ALMA correlator does its processing by subscans—each subscan must be dumped and processed by thecorrelator and ultimately archived—with a gap of several seconds between subscans. On the other hand, thesignals from the antennas flow continuously to the summation logic and recorders, so there are no comparable
gaps in the VLBI data.
In addition to the slow loop, there is also a “fast” loop that may be enabled and which uses the WVR datafrom each antenna to correct the antenna phases in response to the wet component of the atmosphere. These
corrections are performed at a frequency of ∼1 Hz (blue in Figure 8.7). This loop is open (corrections arecontinuously made, but feedback is only achieved through the slow loop). Note also that all WVR corrections
are made online in the ALMA correlator, but obviously after the WVR data was collected, so the phasingcorrections are at their best in stable atmospheres, and deteriorate with increasing atmospheric instability.
There is no limit to the duration on the operation of these loops (other than general ALMA ones with regard
to total data collected).
VLBI Phasing System
Moving beyond the timing of the phasing system, there are several other aspects of the system that an ALMAVLBI observer should be familiar with. All ALMA observations operate with an array of antennas (i.e. thoseavailable to a scheduled observation). Of these, a portion are controlled by the phasing system to form thecoherent sum signal which is used for the VLBI recordings. The previously mentioned reference antenna ismerely a designated member of this “phased array”. At least two antennas from the active array (designated“comparison antennas”) are held outside the phased array. These comparison antennas are thus available fordiagnosing the performance and efficiency of the phased array system. Finally, after construction the summed
signal is decimated to two bits per sample (as is the case with all of the ALMA signals in the VOM), so it
is possible to have the ALMA correlator correlate the sum signal during online processing. This is done byco-opting some antenna that is not used by the VOM and placing the sum signals into the correlator as if it
had come from this “sum antenna”. The sum signal therefore appears as antenna “APP001” in any ASDM filecontaining ALMA data acquired with the VOM. There are a few things to note about the data and metadata
for this antenna:• it has no useful metadata, as it is not a physical antenna• it has no WVR data, for the same reason• it is highly correlated with other antennas in the phased array since the non-phsyical receiver noise ispresent in both
The selections of antennas for the phased array and comparison array are made when the scheduling blockis created, although these may be adjusted if necessary during the observation. Normally, the antennas to bephased are all chosen to lie within a certain radius from the array center. The efficiency of the phasing systemdecreases on longer baselines, so in practice, maximum baseline lengths in the phased array will typically be<∼1 km. The reference antenna is in general selected to be centrally located, and typically at least one of thecomparison antennas is chosen to be within the radius of the phased array. An additional detail is that becauseof the decimation to two-bits, the number of phased antennas must always be odd.
A final important note concerns delays between antennas. The ALMA control system estimates the total
delays between all antennas and adjusts the signals through a variety of techniques (in hardware and software)so that the visibilities found in the data set have essentially zero delay on each baseline, (i.e. there is no slope ina plot of visibility phase as a function of frequency on any baseline.) Unfortunately, a (significant) component of
the delay is removed with a frequency dependent phase rotation in the online correlation processing, not in the
hardware, so there is some significant delay present in the signals at the TFBs where the phase corrections are
made and correspondingly in the logic which creates the “sum antenna” signal. Thus in order for the phasingsystem to work properly, it is necessary to turn off this component of software delay correction and to insteadcorrect it in the phasing calculations. To do this, the observing band is subdivided into a relatively large numberof channel averages (at least 8) and the normal phase-solving procedure produces different, independent phases

8.12. HIGH FREQUENCY OBSERVING

129

that can be applied to the TFBs corresponding to each channel average. This does remove most of the delay,
but it does leave a small residual of phase-slope within each channel average. The only restriction is that thesource needs to be bright enough in each of the channels so that a usable phase solution can be found. The flux
limit if 0.5 Jy in Cycle 5 ensures that this is the case.
The activities of the phasing loop are recorded in an ASDM table as described above.
VLBI Observing Mode Analysis
As pointed out in Section 8.11, any VOM observation actually involves two concurrent interferometric observations: one on the ALMA scale that results in correlated data products between all participating ALMA
antennas and one on a global scale, where ALMA serves as a station in a global VLBI array. A description of
the reduction and analysis of ALMA VLBI data is largely beyond the scope of this document16 . This process
is, however, informed by the analysis of the ALMA-scale observation with regard to observatory performance(SEFD, system temperature, etc.), which for the most part may be obtained in the usual way. However, since
the VLBI signal that is recorded is that of the “sum” antenna whose properties in turn depend on the phasing
performance, a few details should be pointed out. The most significant point is that the effective area of the“ALMA dish” is roughly proportional to the square root of the number of phased antennas. (In Cycle 5 only
12 m dishes are to be used, and they have similar effective areas. If the 7 m dishes were to be included therelation is more complicated.) In practice, a number of effects conspire to lower performance from this ideal
relation17 to about 90% of what would be expected in a perfect system. A second point here is that the sum
antenna signal is decimated to two bits from the individual antenna signals which were also decimated to two
bits. Thus there is an additional reduction in sensitivity by 0.88 that must be taken into account in the VLBI
analysis. In any case, the net effective area of the ALMA “sum” dish may be calculated from the ASDM on a
per-scan basis.
The performance of the phasing system is captured in the metadata in ASDM CalAppPhase tables. Thereis one table entry per scan per baseband.
In each table, there are temporal bounds on validity (i.e. the range of time within the scan of stable phase)and entries to list the disposition of the antennas amongst the various categories (i.e. phased antennas, reference
antenna, and comparison antennas) and whether this represents a change from the previous scan. The tableprimarily reports a number of phase values, Nv , which is dependent on the “packing mode”. In Cycle 5, there
is one value per channel average per polarization per antenna. Additionally, the CalAppPhase table reports
lower-level details of the phasing system, including online per-antenna assessments from TelCal of the antennas
drawn from the quality of the phasing solution. This table may be used in conjunction with the ALMA data for
a particular scan to calculate the phasing efficiency and thus to make an appropriate correction for the absolute
VLBI correlation amplitudes.
As indicated in Section 8.11.1, the correlation products are delivered to the PI for analysis. Traditionallyfor the GMVA this has been in the form of FITS-IDI files. A complication for work with ALMA data is thatthe polarization conversion is performed with a tool (PolConvert) that requires input from the CASA analysisof the ALMA dataset. This conversion can be performed on the FITS-IDI file or at the correlator using theraw correlator output if the the CASA analysis is available. Arrangements for doing this will be worked out
between the PI of each project and the supporting observatory collaborations (GMVA and EHTC) following
the observation.

8.12

High Frequency Observing

High-Frequency Observations (specifically Bands 8, 9, and 10) require some special observing techniques, mostly
because of the combined ill effects of lower atmospheric transmission and fainter and more widely spaced
calibrators. These techniques, which are just addenda to standard observing modes, will be progressively
16 A VLBI analysis handbook is in preparation.
17 ALMA-05.11.63.03-0001-A-REP.pdf

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CHAPTER 8. OBSERVING MODES

implemented in the ALMA observations for Cycles 4 and beyond, after some extensive testing is carried out.
It is expected that all of them will improve not only the quality of the final data products, but also the overall
observing efficiency at high frequencies. For reference, a brief description of the nomenclature that would be usedby Contact Scientists and the ALMA project in general whenever they are discussed, reported or communicatedto PIs is added:• High Frequency Cone Searches and Calibrator Surveys: Observations with the high frequency
ALMA bands require that the availability of calibrators near the target source are checked near the timeof the planned observations. Searches for phase calibrators and check sources (see Chapter 10. details)
within 10 degrees of the science targets (i.e., the so-called “Cone Searches”) in each SB will be carried out
by ALMA staff within 90 days of the high frequency observations. The results of those measurements will
be immediately ingested into the ALMA Calibrator Catalogue, so that they are available for queries at
the time of the actual observations.
• Bandwidth Switching (BWSW): For high frequency observations (Bands 8, 9, 10) with spectral setups including only narrow band spectral windows, the PI will be asked to add an additional wide band
spectral window. This approach increases the accuracy of the gain calibration, allowing a solution acrossthe combined spectral windows and/or transferring of the wide-window solutions to the narrow spectral
windows.Whenever adding a spectral window is not possible (i.e., projects that have occupied all the
spectral windows with narrow-band set-ups), it is possible to use bandwidth switching, in which the phasecalibrator is observed with wider spectral windows for increased signal to noise. The wide-to-narrowspectral window complex gain offsets are measured by observations of the bandpass calibrator, allowing
the phase cal solutions to be transferred. For more details, please read Chapter 10.
• Sideband separation by 90 degree Walsh phase switching (Bands 9 and 10): The Band 9 and
10 receivers are of DSB design, i.e. do not separate or supress either sideband, and signals from bothsidebands are superposed on a single IF output per polarization. Prior to Cycle 5 the only option available
for interferometric observing has been to use orthogonal LO frequency switching sequences to suppress
the contributions of one sideband to the visibilities. From Cycle 5 a means of sideband separation is alsooffered, resulting in twice the output bandwidth and number of channels. The separation uses orthogonalsequences of 90 degree phase shifts applied at the first LO in each antenna, combined with synchronised
accumulation over the sequence duration of the three phase combination states of the cross-correlations ofeach baseline by the correlators, and subsequent combination to produce the two sideband spectra in thecorrelator data processing software. The sequences are of length 128, with switching on 16 ms ticks, andtherefore total length of 2048 ms. This mode therefore adds a constraint that the dump and integration
durations must be a multiple of 2048 ms. Due to an unrelated requirement that subscans must start andend on 48 ms Timing Event (TE) boundaries, and 2048 ms not being a multiple of 48 ms, the allowed
values of subscan durations are somewhat limited, as will be seen when adjusting times in the OT. In
Cycle 5 only a single pair of spectral windows (LSB+USB) in each baseband is offered, and either theTDM (2 GHz, 256/Npol channels) or widest bandwidth FDM (1.875 GHz, 7680/Npol channels) modes
must be used (additionally for FDM, the spw should not be moved from the center of the baseband). The
modes in the four basebands remain independent, e.g. one baseband can use FDM to observe a spectral
line, while the other basebands use TDM to detect continuum.

Chapter 9

ALMA Sensitivity Calculator
The main tool for calculating the sensitivity of ALMA is the ALMA Sensitivity Calculator (ASC). This is anapplication contained within the ALMA Observing Tool (OT) that allows a user (via a GUI) to experiment withvarious sensitivity options using the same methods that the OT employs internally to calculate time estimates
based on parameters entered into a project’s Science Goals.
Although the user may experiment with various sensitivity options (PWV octile, number of antennas, etc.)
in the ASC, the final time estimate for a project calculated by the OT is not influenced by user-supplied entries
in the ASC. For instance, the OT will always assume a fixed number of antennas for the particular Cycle, andwill always use the standard precipitable water vapor (PWV) octile that is appropriate to the frequency ofobservation.
The ASC is also available as a web page that is linked on the ALMA Science Portal1 . This stand-alone ASC
differs from the GUI version incorporated in the OT in that it is possible to enter some parameters that areoutside the ranges that are applicable to the current observing cycle.

9.1

Calculating the System Temperature

When determining the time required to achieve a particular sensitivity, the system temperature, Tsys , is afundamental parameter as it takes into account various sources of noise that make it difficult to detect the very
weak astronomical signals that ALMA is trying to detect. The most prominent sources of noise are from thereceivers and from the atmosphere. The latter is highly variable, both in time and frequency, and thus dynamicscheduling and careful placement of spectral windows are crucial.

9.1.1

Sky Temperature

The OT’s estimate of both the atmospheric zenith opacity, τ0 , and the sky temperature, Tsky , are calculatedusing the Atmospheric Transmission at Microwaves (ATM) code2 . This provides values of the opacity and theatmospheric “output radiance”, in steps of 100 MHz, for the seven different octiles of PWV. The sky temperature
is converted from the radiance using the Planck function and includes the contribution due to the CMB.
The ATM code only provides measurements of the sky temperature at the zenith, Tsky (z = 0), and therefore
the OT must account for the greater atmospheric emission at lower elevations. It does this by assuming that
1 http://almascience.org/
2 See Pardo, J. R., Cernicharo, J., Serabyn, E., 2001, ITAP, 49, 1683. This calculates the sky temperature by integrating theatmospheric temperature profile, this having been formed from the average of 28 radiosonde measurements taken at the ALMA
site during November 1999.

131

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CHAPTER 9. ALMA SENSITIVITY CALCULATOR

Octile
1
2
3
4
5
6
7

PWV (mm)
0.472
0.658
0.913
1.262
1.796
2.748
5.186

Table 9.1: Octiles of PWV measured at the ALMA site from years of monitoring data and used in the ASC.
The first octile corresponds to the best weather conditions and shows that 12.5% of the time, PWV values atleast as good as 0.472 mm can be expected. Subsequent octiles give the corresponding value for 25%, 37.5%.
etc.
the emission from the atmosphere can be approximated asTsky = Tatm (1 − e−τ0 sec z ).

(9.1)

Inserting the ATM values of Tsky (z = 0) and τ0 into Equation 9.1 allows the mean physical temperature of theatmosphere, Tatm , to be measured i.e.
Tsky (z = 0).
(9.2)
Tatm =(1 − e−τ0 )This can be reinserted into Equation 9.1 to calculate the sky temperature at any zenith angle asTsky (z) = Tsky (z = 0)

(1 − e−τ0 sec z )(1 − e−τ0 )(9.3)

Tsky (z) is then corrected for the fact that the required noise temperatures (Tn ) are defined assuming Pν = kT
and thus a correction for the Planck law is required, i.e.

Tn = T ×

hν/kT
hν/kT
e
−1



(9.4)

The octiles characterize the amount of PWV that can be expected at the ALMA site, i.e. a value of PWVat least as good as the first octile value can be expected 12.5 per cent of the time, a value at least as good as
the second octile 25 per cent of the time, and so on. The octiles corresponding to the ALMA site (determinedfrom many years of monitoring) are shown in Table 9.1.
When estimating the time for a project, the OT will always select a PWV octile that is appropriate to thefrequency being observed. It does this by calculating the time required for each octile and then choosing (andreporting) the highest (worst) octile for which the increase in time relative to the first is less than 100 per cent. A
consequence of this definition is that the octile also depends on source declination, i.e. sources at low elevations
will require better weather conditions. The resulting curve of octile versus frequency is shown in Figure 9.1,
for a source declination of zero degrees. A user can override this choice in the GUI version of the ASC, but
submitted projects will always use an automatic choice.

9.1.2

CMB Temperature

The temperature of the Cosmic Microwave Background is included in Tsky and thus does not feature further inthis document.

9.1. CALCULATING THE SYSTEM TEMPERATURE

133

Figure 9.1: Plot of PWV octile assumed by the ASC as a function of frequency, for a source declination of zero
degrees. The vertical lines separate different bands, the numbers of which are shown at the top of the plot. The
water line at 183 GHz (Band 5) is particularly prominent. In general, higher frequencies require drier observing
conditions.

9.1.3

Receiver Temperatures

For ALMA Bands 4 and 10, the calculator currently only uses the specifications for the receiver temperatures(required over 80% of the receiver bandwidth) and not the actual measured values. For ALMA Bands 3, 5, 6,
7, 8 and 9, however, typical values measured in the laboratory are used as these are usually significantly better
than the specifications. The measured values are somewhat conservative and so are in between what might be
expected at the middle and edges of the bands. The values used in the ASC are given in Table 9.2.
Note that single sideband noise temperatures are reported for Bands 1-8 and double sideband temperatures
for Bands 9 and 10.
At the moment, no attempt is made to incorporate the frequency dependence of the receiver temperature,i.e. only a single value is used per band. Ultimately, it is the intention to use the actual measured values for all
receivers and to incorporate the frequency response across the band.
Note that the calculator doesn’t concern itself with the so-called “zero-point fluctuations” as the requisite
half photon of noise (hν/2k) has already been included in the noise measurements provided by the various
receiver groups (A. Kerr, private communication).
The receiver temperatures are already expressed in terms of the Planck expression and thus do not require
the correction given in Equation 9.4.

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CHAPTER 9. ALMA SENSITIVITY CALCULATOR

ALMA Band
1
2
3
4
5
6
7
8
9
10

Receiver Type
SSB
SSB
2SB
2SB
2SB
2SB
2SB
2SB
DSB
DSB

Trx,spec (K)
17
30
37
51
65
83
147
196
175
230

Trx,ASC (K)
17
30
45
51
55
55
75
150
110
230

Table 9.2: Receiver temperatures (and their specifications) assumed in the ASC as a function of ALMA band.
For most of the bands it is currently assumed the ALMA specification for the receiver temperature that shouldbe achieved across 80% of the band, Trx,spec . In practice, the receivers actually outperform the specificationand for Bands 3, 6, 7, 8 and 9 the ASC uses “typical temperatures measured in the laboratory” (highlighted inbold text).

9.1.4

Ambient Temperature

Ambient temperature is essentially spillover from the sidelobes of the antenna beam corresponding to emission
from the ground and the telescope itself. This is held constant at 270 K (median value as measured from many
years of monitoring data at the ALMA site). However, the value used by the ASC is converted to a noise
temperature according to Equation 9.4 and thus its total contribution is frequency dependent and can vary
between the different sidebands.

9.1.5

DSB Receivers

Due to the way that the astronomical signals are down-converted to an intermediate frequency, every heterodyne
radio receiver simultaneously detects radiation from two sidebands. This means that, if nothing were done toprevent it, a spectral window processed by the correlator would contain two sets of astronomical signals mixed
in with one another, one from the “signal” sideband and an undesirable one from the “image” sideband. In
the case of 2SB receivers , the contribution from the image sideband (emission from the source and noise) is
suppressed to a very high degree. However, for DSB receivers (Bands 9 and 10) it is only possible to remove thesource contribution (either by LO offsetting or 90-degree Walsh switching) and so the noise cannot be neglected.
One important consequence of this is that, if a spectral window has its image counterpart in an area of very
poor atmospheric transmission, it can greatly increase the system temperature and lead to very long on-source
times. Therefore, it is important to avoid areas of bad atmospheric opacity in the image spectral windows andthe OT therefore shows the location of these in the spectral visual editor (Figure 9.2).
One subtlety is that the tuning software will always place spectral windows in the upper sideband if possible.
Therefore, to take a simple case, a single spectral window centered at 637 GHz will find its image equivalent
in the middle of the zero transmission feature at ∼621 GHz. Where possible, this situation can be avoided bydefining dummy spectral windows such that the line of interest is forced into the other sideband (Figure 9.2).

9.1. CALCULATING THE SYSTEM TEMPERATURE

135

Figure 9.2: A Band 9 spectral setup as displayed in the spectral visual editor in the OT. The top figure shows
an example of how the image equivalent of a single spectral window can fall into an area of poor atmospherictransmission, leading to much higher Tsys than necessary. Placing a dummy spectral window at a higher
frequency can remedy the situation (bottom).

9.1.6

System Temperature (OT version)

The OT version uses two distinct formulas depending on whether a double sideband receiver is being used, ornot. The DSB equation is the following:
1
Tsys,dsb =
2
×
T
+
η
(T
+
T
)
+
(1
−
η
)
×
(T
+
T
)
(9.5)
rx
eff
sky,s
sky,i
eff
amb,s
amb,i
ηeff e−τ0 sec z
where• Trx – receiver temperature• Tsky,s – sky temperature at the requested frequency in the signal sideband• Tsky,i – sky temperature in the image sideband• Tamb,s – ambient temperature in the signal sideband• Tamb,i – ambient temperature in the image sideband• ηeff – the coupling factor, or forward efficiency. This is equal to the fraction of the antenna power patternthat is contained within the main beam and is currently fixed at 0.95
• e−τ0 sec z – the fractional transmission of the atmosphere, where τ0 is equal to the zenith atmosphericopacity and sec z is the airmass at transit (the ASC always assumes that the source is being observed attransit).
The terms ηeff and e−τ0 sec z both attenuate the source signal and thus divide through by them in order to obtaina measure of the system noise that is relative to the unattenuated source. Note that this is always done at thesignal frequency.
For SSB and 2SB receivers, the equation is the following:


1
T
+
η
T
+
(1
−
η
)
×
T
Tsys,ndsb =
rx
eff
sky,s
eff
amb,s
ηeff e−τ0 sec z

(9.6)

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CHAPTER 9. ALMA SENSITIVITY CALCULATOR

where the terms are all the same as in Equation 9.5.

9.1.7

System Temperature (Stand-alone ASC and GUI (OT) version)

The equations to calculate the system temperature, used by the stand-alone ASC and the GUI within the OT,
are similar. Both are unaware of the details of the tuning setup and so do not know the location of the image
sideband and cannot perform a rigorous calculation of its contribution to the system temperature. In this case,the same equation is used for all receiver types and the DSB noise contribution is simply double the single
sideband case. This is controlled via the sideband gain ratio, g:


1+g
T
+
η
T
+
(1
−
η
)
×
T
.
(9.7)
Tsys =
rx
eff
sky,s
eff
amb,s
ηeff e−τ0 sec z
For Bands 1 and 2 (Single Sideband; SSB) and 3-8 (Sideband Separating; 2SB), g = 0. For DSB receivers,g = 1.

9.2

The Sensitivity Calculation

Once Tsys has been determined it is possible to calculate the point-source sensitivity given a requested amountof on-source observing time or vice versa. At no point is any account made for the expected level of loss insensitivity due to problems with the telescopes such as residual pointing and focus error.
Under certain circumstances it will not be possible to achieve the theoretical sensitivity, particularly if thesource being observed is very bright and/or the u, v coverage relatively sparse. In these situations the image
can be dynamic-range limited due to residual source flux scattered across the map as a result of calibration
errors and imperfect source deconvolution.

9.2.1

12-m and 7-m Arrays

When dealing with the 12-m and 7-m Arrays, the point-source sensitivity, σS , is given by the standard equation:
σS =wr 2 k Tsysp.
ηq ηc Aeff (1 − fs ) N (N − 1) np ∆ν tint

(9.8)

The various parameters are:• wr – robust weighting factor. Pipeline imaging and subsequent QA2 assessment is performed assumingthat the visibilities are weighted using robust weighting, specifically a Briggs robustness factor of 0.5.
Simulations have shown that this factor is equal to 1.1.
• Aeff – effective area. This is equal to the geometrical area of the antenna multiplied by the aperture
efficiency where ηap = R0 exp (−16 π 2 σ 2 /λ2 ) and σ is the rms surface accuracy of the antenna. The latteris set to the design goal of 25 µm and 20 µm for the 12 and 7 m antennas respectively3 . Ro is the productof a number of different efficiencies and is equal to 0.72. See Table 9.2 for values of antenna efficiencies
and effective areas in various ALMA bands.
• fs – shadowing fraction. For the more compact 12 m configurations and the ACA 7-m Array, antennas
can block the field-of-view of other antennas in the array and thus reduce the total collecting area. The
shadowing fraction is a function of source declination as shown in Fig. 7.5.
• ηq – quantization efficiency. A fundamental limit on the achievable sensitivity is set by the initial 3-bit
digitization of the baseband signals. This is equal to 0.96.
3 Note that not all antennas might achieve this specification. The performance of a given antenna will also vary with the thermal
conditions and the length of time between surface realignments.

137

9.2. THE SENSITIVITY CALCULATION

Band
3
4
6
7
8
9
10

Frequency (GHz)
100
145
230
345
405
690
870

ηap,12 m (%)
71
70
68
63
60
43
31

ηap,7 m (%)
71
71
69
66
64
52
42

Table 9.3: Aperture efficiencies at typical continuum frequencies for both the 12 and 7 m antennas. The effective
area, Aeff , is equal to ηap multiplied by the physical area of the dish i.e. 113.1 m2 and 38.5 m2 for the 12 and 7
m antennas respectively.
• ηc – correlator efficiency. This depends on the correlator (64-input or ACA) and correlator mode, although
the efficiency of all 64-input Correlator modes is equal to 0.88. The ACA efficiencies do depend on themode, but this is only taken into account in the OT, not by the stand-alone ASC (see below) which
therefore also assumes a value of 0.88.
• N – number of antennas. This defaults to 43 for the 12-m Array and 10 for the 7-m Array.
• np – number of polarizations. np = 1 for single polarization and np = 2 for dual and full polarization
observations.
• ∆ν – resolution element width. As already mentioned, this should be equal to 7.5 GHz for continuum
observations. This is due to the maximum usable bandwidth of a spectral window being limited to1.875 GHz by the anti-aliasing filter through which the baseband signal passes. np ∆ν is often referred toas the effective bandwidth.
• tint – total on-source integration time.
The associated surface brightness sensitivity (K) is related to the point-source sensitivity (Jy) by
σT =

σS λ2
2k Ω

(9.9)

where Ω is the beam solid angle. This is related to the user-entered spatial resolution, θ, by
Ω=

πθ2
.
4 ln 2(9.10)

This assumes that the telescope beam is a circular Gaussian with a half power beamwidth of θ.

9.2.2

Total Power Array

In the case of the TP Array, a different equation is used
2 k Tsysp.
(9.11)ηq ηc Aeff N np ∆ν tint√
This is similar to Equation 9.8, but there is only a factor of N in the denominator and there is no need totake shadowing into account.
σTP =Particularly for continuum observations, the above equation is likely to be too optimistic due to rapid
fluctuations of the receiver gain and atmospheric opacity. These require extremely demanding calibration
strategies and, as these have not yet been commissioned, only spectral line total power projects are currently
possible.

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CHAPTER 9. ALMA SENSITIVITY CALCULATOR

Figure 9.3: Screenshot of the GUI version of the ALMA Sensitivity Calculator as implemented in the ALMA
Observing Tool. The white area at the bottom is for displaying error messages i.e. parameters out of bounds.
The example here shows the achievable sensitivity for all three arrays for an on-source time of 10 minutes.

9.3

User Interface

The main way that a user interacts with the Calculator is through a GUI in the OT or via the stand-alone ACA
in the ALMA Science Portal – both are essentially identical. By entering various parameters, the time required
to achieve a particular sensitivity (in either Jy or K) can be calculated, or vice versa. The inputs that affectthe sensitivity or time are given below; a screenshot of the OT’s GUI version is shown in Figure 9.3.
• Source declination – this is used to calculate the maximum elevation of the observation and thus theminimum airmass i.e. the ASC assumes that the source is transiting. It is also used to calculate theamount of shadowing that is likely to affect the ACA 7 m and the smaller 12 m configurations.
• Observing frequency – this sets the receiver temperature, antenna efficiency and the PWV octile.
• Bandwidth per polarization – this otherwise straightforward parameter should be set to 7.5 GHz forcontinuum observations (see Section 9.2.1). For spectral line observations, it is usually set to the frequency/velocity resolution that one requires in one’s spectrum.
• Water column density (PWV). The user is able to enter one of the seven octile values, or the calculator
will set this automatically depending on the frequency entered.
• Number of antennas – the ASC currently defaults to the values for Early Science, namely 43 from the
12-m Array, 10 from the 7-m Array and 3 from the TP Array.

9.4. TOTAL TIME ESTIMATES

139• Angular resolution – this affects the time estimates when sensitivities are specified in temperature units.
The calculator will not perform any calculations when Kelvins have been specified, unless a non-zero value
for angular resolution has been entered. The calculator will also issue a warning if the angular resolution
falls outside of the range corresponding to 125 m and 1 km baselines.
The calculator reports the values of τ0 , Tsky (including the correction for the source elevation) and Tsys that
correspond to the entered frequency and PWV.

9.4

Total Time Estimates

Note that the time calculated by the ALMA Sensitivity Calculator does not account for telescope overheads(calibration, software and hardware latencies, etc.) and therefore the time is always assumed to be the true
on-source time. Chapter 5 of the OT User Manual should be consulted for details on how the total time required
to observe and calibrate an ALMA project is calculated.

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CHAPTER 9. ALMA SENSITIVITY CALCULATOR

Chapter 10

Calibration and Calibration Strategies
10.1

The True and Observed Visibility Function

10.1.1

The Data Format and the Correlator Model

The fundamental output of the ALMA correlator is a complex quantity, called the observed complex visibility
function, V o . Its amplitude measures the fractional correlation of the radio signals between any two antennas,
and its phase measures the phase difference between the signals. These data, together with meta-data that
describe relevant parameters associated with the observations, are stored in the ALMA archive and are in theform of the ALMA Science Data Model (ASDM). The hardware associated with the flow of the astronomical
data from the antennas through the correlator to the archive is described in Chapter 14.
The true complex visibility function, V t , is related to the celestial radio emission angular and spectral
distribution, and the relationship, an approximate Fourier transform, is described in the Chapter 7. The goalof the present chapter is to describe methods to retrieve the true complex visibility function from the observed
complex visibility function.
The fastest time dependence of the observed visibility function is produced by the diurnal motion of the radiosource which changes the phase difference of the signals in each antenna pair. This response is quasi-sinusoidal
and is called the natural fringe, often with a rate of several kilohertz. This fast response can be approximatedby assuming a position in the sky, σ0 , called the phase center, the positions of the appropriate antenna-pairand the observing frequency, and of course the earth rotation rate. This algorithm is called the correlator delay
model and is described in more detail in Chapter 5. Other, smaller contributions to the visibility phases; suchas the atmosphere delay over each antenna and phase or delay changes in the antenna electronic system, can bealso included, if well-known. After this correlator model is subtracted from the natural fringes, the (residual)
visibility function is a much slower function of time and can then be averaged over many seconds, with no loss of
information about the angular distribution of the observed celestial object. The resultant image position of thecelestial object will then be obtained with respect to the assumed phase center position. The most convenient
location of the phase center is antenna pointing and delay center positions used for the observation.

10.1.2The Visibility Function Dependence

The observed visibility function, V o , associated with each baseline pair (i,j), with each scan (see Section 8.2)
and set of band frequencies is
V o (σ, νb )i,j [tk , νs,c , pq ](10.1)
where:
i, j is baseline pair between antenna i and j,

141

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

tk is each time-stamp in the scan,νs,c is the frequency sampling within the band,
where s is a spectral window (spw),
and c is the channel index within each spw (from 1 to a maximum of 4096),
pq represents up to a maximum of the four linear polarizations products (XX,XY,YX,YY).
The complex visibility function is often described by its amplitude, Ao , and its phase (φ0 ) components sincevirtually all of the calibrations change its amplitude and phase somewhat independently, rather than real andimaginary parts independently.
The autocorrelation data, for the case where i = j is also contained in the data set. The calibration and useof this data are given in Section 8.6 and Chapter 13.

10.2

Main Interferometric Calibration Strategies

10.2.1

Phase Referencing

Most ALMA interferometric observations use phase referencing as the major calibration method. This methodinterleaves scans between the science target and a nearby calibrator source that has an accurately known
position, spectrum and flux density, and is sufficiently small in angular diameter. Since the true visibility ofthe quasar can be modelled, its observed visibility indicates the entire changes induced by the ALMA system,
including that of the atmosphere. If the calibrator and target are only several degrees apart and a typicalswitching time between them is several minutes, then the measured induced changes from the calibrator data
will be approximately that for the target, hence its true visibility can be estimated.

10.2.2

Antenna-based Calibrations

Nearly all of the changes from the true visibility function to the observed visibility function are associated withchanges in the signal flow in each antenna, from the radio wave path in the troposphere above that antenna,
through all of the antenna electronic processing, then into the correlator that combines each antenna-pair of
signals to obtain the visibility function for each baseline. Hence, the calibration equation that describes thesechanges to each baseline visibility function can be written solely in terms of the changes in the two antennas
associated with the baseline pair1 :otV(i,j)(tk , νc ) = Gi (tk , νc ) ∗ G̃j (tk , νc ) V(i,j)(tk , νc )t+noise + g(i,j) (tk , νc ) V(i,j)(tk , νc )(10.2)

where Gi (tk , νc ) is the antenna-based complex gain calibration as a function of time and frequency. This is thenormal antenna-based calibration equation. The second line in equation 10.2 contains the effect of noise andany additional baseline-dependent calibrations, and these will be ignored for the most part. The polarization
dependence (the calibration relationship between the X- and Y-polarization) is discussed in Section 10.5.
The complex antenna gain can be separated into the antenna-based amplitude gain, G and the antenna-based
phase, ψ component,
Gi (tk , ν) = ai (tk , νc ) ejψ(tk ,νc )(10.3)
where ai (tk , νc ) is the antenna-based amplitude correction and ψ[tk , ν) is the antenna-based phase corrections,both as a function of time tk and frequency νc for each polarization. The symbol j is the imaginary unit. The
antenna-based gains and phases are the major calibration quantities that are described in this chapter.
1 The radio emission has two polarizations which are can be detected in ALMA into two linear parts, X and Y. The equations
are for either polarization. For polarization interferometry, additional terms between the X and Y polarizations are discussed later.

10.2. MAIN INTERFEROMETRIC CALIBRATION STRATEGIES

10.2.3143

Major Calibrations Affecting Interferometric Data

The modifications of the information in the radio waves from a celestial source occur at many locations along
the path from the source to the data archive. A list of components associated with signal changes, based on G.
Moellenbrock’s 2014 Socorro Summer School Lecture2 is:I = Ionosphere: Opposite rotation of linear polarization position angle caused by propagation through theionosphere—not significant at frequencies above 70 GHz.
T = Troposphere: Absorption of signal and delay of signal caused by several atmospheric components.
P = Antenna Voltage pattern: The relative response across the reception area of the antenna beam which canbe lightly modified because of pointing and focus errors, and by the quality of the antenna surface.
p = Parallactic angle: The rotation of the antenna feed orientation with respect to the sky (alt-azimuth
mounts).
X = Linear polarization angle: The orientation of the feed with respect to the antenna structure.
d = Polarization leakage: The non-orthogonality and small mis-alignments of the two orthogonal polarized
feeds causing slight mixing of polarizations.
T = System Temperature: A measure of the noise fluctuations from the entire system, dominated by thereceiver system at low frequencies, and the atmosphere noise at high frequencies.
M = Delay model used in the correlator to compensate for the best-estimate temporal delay changes at eachantenna.
D = Instrumental delay offset of the signals between antennas.
B = Bandpass response: The relative amplitude and phase of an antenna response as a function of frequency.
G = Temporal gain: The relative amplitude and phase of an antenna response as a function of time.
F = Flagging: Editing of data found during the calibration process.
Do not be intimidated by the above list. The most important ALMA calibrations deal with the temporalgain G and the bandpass response B. The calibration process is significantly simplified because the temporaldependence (GT ) and frequency dependence (BF ) for nearly all instrumental changes are only lightly coupled,so the variations in time, tk and frequency νk can be determined independently to first order:
Gi (tk , νc ) ≈ GT (tk ) ∗ BF (νc )10.2.4(10.4)The Organization of the Calibrations

There are three major stages of calibrations in ALMA.
A-priori Calibrations. These are calibrations that are associated with relatively fixed properties of thearray; for example the antenna positions, pointing, focus and delay models, and calibration parametersof various devices throughout the system. These are measured periodically by the ALMA staff using
methodologies briefly outlined below.
2 https://science.nrao.edu/science/meetings/2014/14th-synthesis-imaging-workshop/lectures-files/
nbsp;nbsp;nbsp;MoellenbrockCalibration2014_FINAL.pdf

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

Online parameters and calibrations. Various calibrations and corrections are performed during observations. Some happen completely transparently, such as regulating the fiber path length from antenna tocorrelator by the Line Length Correctors (LLCs), and small pointing corrections by metrology systems ineach antenna to compensate structural deformation by uneven temperatures, wind loading etc.
Some explicit calibration scans are included in the observing sequence, which are clearly visible in the
ASDM and can be re-processed offline if needed. Most observations include pointing calibration scans,after which the measured pointing offsets (only collimation terms) are applied as an increment to theantenna pointing models. Some observations similarly contain focus calibration scans, although in mostcases focus is calibrated in separate observations throughout the day to allow more flexible schedulingof these calibrations. Atmosphere calibration scans are included, from which Tsys spectra are computed
online and provided in the ASDM for application in data reduction offline. Auxiliary calibration results
are also computed online from various scans primarily for quality assurance purposes, for example phasevariability statistics from scans on bright calibrators. When online WVR correction is used, parameters
to facilitate the simple linear approximation of path length with WVR channel temperatures are also
computed from many scans and updated in the correlator software.
Offline calibrations. The offline calibrations are those determined after the completion of an observation.
These calibrations are associated with special-purpose calibrator scans that are embedded within thesequence of scans. The three major types are: (1) the removal of the frequency dependence across themeasured bandwidth, B, using a strong calibrator with no spectral features, known as the bandpass
calibrator; (2) the removal of remaining amplitude and phase temporal changes during the experiment, G,
using the phase referencing technique; (3) the conversion of the measured visibility amplitude to Jansky
flux density units, best accomplished by a short observation of a source of known flux density.
A detailed description of each one of these major stages are given in Sections 10.3 to 10.5. Special calibration
techniques are outlined in Section 10.6. Following each calibration item, its corresponding category according
to the classification in Section 10.2.3 is given in parenthesis.

10.3

ALMA-Supplied a-priori Calibrations

The ALMA staff will provide calibrations that are long-term and/or require specialized observations and monitoring. These are outlined below.

10.3.1

Antenna Beam/Surface Characteristics (P)The relative sensitivity of each antenna as a function of azimuth and elevation from the pointing direction
is called primary beam pattern, which is described in Section 3.2. This sensitivity correction is needed forlarge angular source emission, and for multi-pointings observations (mosaicing) with overlapping fields. The
measurements of the pattern are made by mapping the antenna beam using a bright radio source, either using
single dish scanning around a strong source or with interferometric observations at many points over an areathat extends well outside of the main primary beam area. The measurements are processed in special-purpose
software that estimates the accurate antenna surface topology, and adjustments of the antenna panel supports
can be made if the surface is not within specifications. The measured primary beam patterns for each antennatype are available in the imaging software packages and applied when producing the sky-corrected images (seeChapters 3 and 7 for more details).

10.3.2

Antenna Pointing Models (P)All-sky pointing of the array elements at a nominal accuracy of 200 RMS is achieved by a combination of metrology
systems inside the antennas themselves to account for variable deformations, and static models maintained by
the observatory. The static models are dominated by six terms: azimuth encoder/pad offset (“IA” term, of10.3. ALMA-SUPPLIED A-PRIORI CALIBRATIONS

145

order 100000 ), elevation encoder/collimation offset (“IE” term, order of few hundred arcsec), azimuth collimation
offset (“CA”, order few tens of arcsec), tilt in North-South and East-West directions “AN” and “AW” terms,
order of ten arcsec), and elevation sag (“HECE”) term, order of ten arcsec). The full pointing model has 17 to
19 terms, most of which are at the arc-second level. The pointing differences between receiver bands require
only a collimation offset (CA, IE terms) with respect to a reference band (currently Band 3).
The complete pointing models are checked and adjusted on weekly timescales, primarily by making “all-sky
pointing runs”. These observations carry out a series of around 50 pointing calibration scans in Band 3 onbright quasars of accurately known position, well distributed over the sky. The total observing time is about
one hour and each pointing measurement scan consists of a measurement of the quasar visibility amplitude atfive subscans at different antenna pointing offsets (depending on frequency and antenna diameter) from theassumed pointing direction. From these data, the pointing offset for each quasar scan for each antenna can be
determined to an accuracy of around 0.300 . The fit of these offsets to the full pointing model has a typical rms
error over the sky of < 200 . Results from pointing calibration scans in science and other observations are also
used to supplement dedicated measurements for maintaining the pointing models.
The pointing models are stored in the Telescope Monitor and Configuration Data Base (TMCDB) which
includes a history of all changes. Currently only night time pointing measurements are considered in these static
models. During daytime observations, the pointing changes with time due to differential antenna heating, andthe modeling of the pointing is not yet well-characterized.
After each antenna relocation, the pointing changes are primarily confined to the azimuth offset and tilt
terms (IA, AN, AW). The tilt is measured after the relocation by spinning the antenna in azimuth and fitting
sinusoids to the two axes outputs of inclinometers located above the azimuth bearing. This gravitational tilt isconverted to an astronomical tilt by adding a local gravity vector (which varies over a 5-km distance across thearray due to the effect of the nearby mountains). With the tilt updated in the pointing models, the azimuth
offset is determined by fitting total power data recorded while the antenna performs azimuth strokes across aplanet or bright quasar. After this the all-sky pointing is typically accurate to within a few arcseconds, and it
is later refined as described previously.
In all science executions, additional short pointing measurements are made as needed using a bright quasar
near each of the science targets and calibrators. The pointing observations are currently made in the target
observing band up to Band 8, but in Band 7 for Bands 9 and 10 due to insufficient sensitivity to quasars. Up to
Cycle 4, pointing scans were made at a fixed tuning for each band, but from Cycle 5 it is hoped to use the samefirst LO frequency as the science tuning in order to reduce re-tuning overheads where atmospheric transmission
makes this optimization feasible. The criteria for whether to do pointing calibration scans are more strict at
higher frequencies. These additional pointing offsets are at the arcsecond level, and are applied in a temporary
auxiliary pointing model, which is added to the master static TMCDB pointing model for each antenna. With
these residual offsets included, the pointing accuracy for all scans is intended to be within 0.600 RMS. The total
pointing model used for any scan (sum of primary and auxiliary models) is stored in a PointingModel table in
the ASDM datasets.

10.3.3Focus Models (P)As for pointing, static models for antenna focus (subreflector position) are stored in the TMCDB, and offsets
applied while observing as needed. Unlike for pointing, we do not use active metrology systems in the antennas
themselves to correct the focus due to unpredictable path length changes that may result.
The focus models only require six main terms, plus offsets for each receiver band. The models contain
an offset for each axis which describes the optimum subreflector position for Band 73 at elevation 50◦ andtemperature 0◦ C (“XR”, “YR”, “ZR”, typically a few mm in size). In the axial (Z) and elevation-oriented
direction (Y) there is a coefficient of sag with elevation (“ZS”, “YS”, up to a few mm in size and depending on
antenna type). For the Z axis there is a temperature coefficient (“ZT”), which well tracks the night time (thermal
3 Band 7 is used as focus reference for three reasons: it typically gives the smallest measurement uncertainty in an individual
focus scan, Band 7 is located with the high frequency receivers near the optical axis, and Band 9 and 10 observations tend todepend on focus scans in Band 7 to guarantee good S/N. The bottom of Band 7, around 290 GHz is used to optimize measurement
accuracy for a wide range of observing conditions.

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

equilibrium) variation of the focus. The band offsets are mostly small, around 0.1 mm, with the exception of theaxial focus of Band 4 which differs by around 1 mm from the other bands as a compromise to avoid having touse a lens on the feed horn as has to be done for Band 3 and below to save space. These models are maintainedby long- term compilation of focus measurements in all receiver bands for the antennas, with care taken withregard to hardware changes which may change the focus characteristics.
Focus measurements are traditionally made in a way similar to those described for pointing measurements,
except the subreflector is offset (in one axis per scan) relative to the nominal model position. The subreflector
position in the axis being offset which yields maximum gain is solved for each antenna from the cross-correlation
data. A holographic technique using interferometric beam maps which simultaneously derives the three axis
offsets in addition to pointing and illumination offsets, which does not require the subreflector to move, isalso available, but is not commonly used yet due to concerns over dependence on atmospheric path lengthstability which the traditional technique is largely immune to, and requirements on calibrator fluxes for higher
frequencies. These measurements are made by the observatory as needed to maintain the models, and routinely
while observing to track non-equilibrium focus variation during daytime and sunrise/sunset and to correct forany errors in the TMCDB model. Most focus measurement observations only perform a scan for the axial (Z)axis, as the antenna gains are much more affected by the Z-axis variations than variations in the lateral axes
(usually the measurement uncertainty from a single measurement scan in the lateral axes is at the same level
as the error by just using the TMCDB model).
The focus model used during an observation is stored in a FocusModel table in the ASDM datasets.
Further improvements to focus calibration are desirable. As for pointing, performance in daytime and aroundsunrise/sunset is problematic and relies on frequent measurement and correction. Correlations between focus
changes and temperature sensors at various locations in the antenna structures are being studied in the hopeof improving the daytime modelling, which would improve daytime high frequency performance and improve
daytime observing efficiency. In addition to the translational axes, the subreflectors can also be tilted, which
will give a small reduction in spillover for the low frequency bands that are far from the optical axis (Bands
1–6). This capability may be implemented in future Cycles.

10.3.4

Antenna Delay Offsets (D)As for pointing and focus, models for the antenna delays are stored in the TMCDB. These include an overall pad
delay of up to tens of microsec for the most remote stations, plus delays for each signal path combination, eachvalue typically up to a few hundred picosec. When an antenna is integrated after relocation to a different pad,the delay is obtained a-priori to within a few tens of nanosec using a hardware timing mechanism of the digitaltransmission system (DTS), and after that the remaining delay error is found by interferometric observation ofa very bright continuum source in Band 3 with a medium spectral resolution FDM mode, which can reliably
measure delay errors up to a few hundred nanoseconds. The signal path delays are obtained by low spectral
resolution observation of a continuum source in a variety of tunings to cover all the signal path combinations.
Checks of the delays are usually performed at the start of an observing session, probing all of the backend
signal paths using four scans in Band 3 (an “IF Delay” observation), and for the frontend bands that are to be
used by making a scan in that band.
The typical spread of delay errors in science observations is around 50 ps, corresponding to 36◦ of phase slope
over a 2 GHz baseband. This is what you should expect to see in the phase component of bandpass calibration
solutions, as described below. The primary reason for maintaining such low errors is to allow spectral-averaged
data to be used for processing calibration scans online (pointing, focus, phase statistics etc.). Repeatabilityof delay measurements with ALMA is actually at the 1 ps level, even over multiple days. However, in reality
the “delay” measurements include a component which is just the phase vs. frequency response of the receiversystems, which differs from tuning to tuning, and results in a spread of some tens of picoseconds even if delays
are set to 1ps accuracy at a nominal tuning. The receiver phase response spectra also mean that the delay
measurement errors derived from residual phases after the fit are typically around 20 ps, and far greater than
the repeatability.

10.4. ON-LINE CALIBRATIONS

10.3.5147

Antenna Positions (M)The relative positions among the ALMA antennas must be known to a small fraction of a wavelength in orderfor the delay model M (see Section 10.3.4) to be accurately calculated during an observation4 . This corresponds
to an accuracy of about 0.1 mm.
The antenna positions are determined in a two-step procedure. The first step is made within a day or twoof the antenna relocation to a new pad. Since the a-priori value of an antenna position error after the move canbe as large as 10 mm, its position must be updated to about 1 mm accuracy so it can be used for the additional
calibrations to incorporate the antenna into the array. One of the initial calibrations, that of determining theantenna pointing parameters over the sky, can also be used to determine the antenna positions. The positions
are stored in the TMCDB and are the most critical part of the delay model that determines the observed
visibility phases for all observations. The antenna positions are the (x,y,z) distance of the intersection of thetwo axes of the antenna from the Earth geocentric position.
When all of the antenna relocations to an array configuration have been completed, the second step is todetermine accurate antenna positions of about 0.1 mm accuracy. This is done with a one-hour all-sky-delay
observation at 88 to 100 GHz of about 50 quasars distributed over the sky, and when the atmospheric phasestability is excellent.
For observations that are made before the most accurate antenna positions have been determined, there areoffline procedures using the Pipeline or Manual reductions that compare the antenna values in the TMCDB
used for the observation with values from the best all-sky delay observation, which are stored in an accessible
computer file, to correct for the known antenna position offset during the observations.
The repeatability of antenna position measurements in long baseline configurations is under active investigation. Position variations of over a millimeter are often seen on a variety of timescales for the most distantantennas, which is thought to primarily be due to variation in zenith path delay through the troposphere above
each antenna. When analyzing observations made in the longest baseline configurations, it is quite possible you
will see effects of position errors at around 1 mm level for the most distant antennas (i.e. phase slope in phasecalibrator scans after bandpass calibration).

10.4

On-Line Calibrations

10.4.1

Water Vapor Radiometer Measurements (M)Fluctuations in the line-of-sight precipitible water vapor (PWV) of an antenna cause significant delay corrections,
up to 0.3 mm/sec, corresponding to 30◦ of phase/sec at 90 GHz, and scales in phase linearly with frequency.
The changes are driven by wind, and cover a large range of spatial scales from 5 m to many km. All 12 m
ALMA antennas are equipped with a Water Vapor Radiometer (Dicke-type) that measures the emission of theatmospheric water line along the same path of the other ALMA bands, in four spectral frequencies near 183
GHz with a sampling of about 1 Hz. These radiometers are described in Nikolic, B., et al., 2013, A&A, 552, 104.
The CM antennas do not have WVR receivers. Tests to using interpolated WVR data from the PM antennas
that surround the CM array suggested any corrections on these short baselines are insignificant.
The conversion of the water vapor emission into appropriate delay changes (M) depends on the atmospherictemperature and pressure and is measured using two systems that are discussed in the following section.

10.4.2

System and Receiver Temperature(T)At millimeter and submillimeter wavelengths, the additional random noise associated with a measurement has
two major causes: the noise associated with the receiving system, TRX , and the noise associated with the
4 To reiterate, the observed visibility phase is the difference between the observed quasi-sinuoisoid correlated signal between any
two antennas with that of the correlator delay model. The difference should be small (< 60◦ ) and not too variable (< 10◦ per
minute) for accurate calibration and imaging of celestial sources

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atmosphere Tsky , which acts like a black body emitter, and attenuates the astronomical signals. This sky noise
is a strong function of frequency, elevation, the column of wet and dry constituents of the atmosphere, and thetemperature of the atmosphere. The noise from the receivers can also vary for a given tuning with factors suchas cryostat temperature and pointing direction with respect to the local magnetic field.
To measure these effective temperatures, the ALMA and ACA front ends are equipped with an Amplitude
Calibration Device (ACD) that moves a hot and an ambient blackbody load in front of each receiver feed. The
description of the system temperature electronics is given in Chapter 9, equation 1.7. The noise measurementfrom these two loads give the total system temperature, Tsys , and the receiver temperature, TRX for each spectral
channel, and significantly effect the observation sensitivity, given in Chapter 9, equation 1.7. The accuracy ofthese measurements depends on the linearity of the autocorrelation data with input power, which currently
limits these observations to the lower spectral resolution TDM mode (256 total channels, divided amongst 1, 2
or 4 polarization) of the baseline correlator5 .
Every scan could have a system temperature measurement, but at frequencies below about 400 GHz, where
the system temperatures are relatively constant over 10 min or over 10◦ in the sky, measurements can be limited
in time and among sources. At higher frequencies, each of the sources should have a measurement to remove
amplitude offsets between them. The specifications for Tsys calibrations are to reach 1% correction accuracy.
The on-line measurements of Tsys and TRX are stored in the CalAtmosphere table in the ASDM datasets, andare displayed in real-time at the telescope to show measurement problems immediately. The system temperature
measurements can also be re-derived off-line from the original hot and cold load data if there were on-line
conversion problems or if a modified processing algorithm is used. The Tsys spectra, suitably interpolated
between time and sources, is then applied off-line to the correlation data. Assuming that the correlated data isin units of percentage correlation, multiplication by the Tsys will change the correlated data units to Kelvin.
The temperature measurements give the receiver-weighted contributions from both sidebands, whereas the
cross-correlation data is measured for each sideband by using LO switching sequences to suppress the image
sideband cross-correlation. Thus, the measured Tsys and TRX must be scaled by a sideband gain factor to
produce a single sideband temperature which can be directly applied to the visibility data to put them intemperature units. In prior cycles, strong sources were included in every science execution to measure basebandaveraged sideband gains to correct the system temperatures, but these measurements are not accurate except
under very ideal observing conditions. Since Cycle 4, nominal values of 0.99 for single side-band frequency
bands and 0.5 for double side-band frequency bands are used to convert the system temperature.

10.4.3

Additional Antenna Pointing Checks (P)As discussed in Section 10.3, corrections are determined for the antenna pointing after each antenna moveand approximately once per week. The nominal all-sky pointing accuracy is about 2.0 arcsec. In order toobtain ALMA’s 0.600 RMS pointing accuracy specification, additional pointing observations may be made before
each scan. To some extent these additional pointing calibrations compensate for shortcomings in the antenna
metrology systems, and errors in the static models. These pointing measurements are automatically includedin the observation schedules, with no PI input. At present a pointing calibration is triggered when moving toa target more than 25 degrees from the previous pointing calibration.
The results of the pointing measurements in each execution are stored in the CalPointing table in the ASDM
datasets, and are displayed as they are produced during the observations to allow problems to be immediately
seen on-line. These results can be used for off-line data flagging of antennas: if a correction is deemed too large;
the measurement uncertainty is too high; or the pointing result is missing.
5 In TDM mode the autocorrelation zero lags can be used to fully compensate for quantization effects on the autocorrelations.
However, in FDM mode an extra filter bank is inserted before the correlations so an external measure of the total digitized power
is needed. The current plan is to use the baseband square-law detector data to provide this extra input for Cycle 5.

10.5. OFF-LINE CALIBRATIONS

10.5

149

Off-Line Calibrations

Off-line calibrations, those made after completion of an observation, are described in other chapters (QA0,
QA2, Pipeline, Manual Reductions). The data format conversion of the ASDM to the measurement set, andits archive are also given in other chapters. In this chapter an overview of the calibrations and editing aredescribed.
The compilation of the radio sources that are used for many of the off-line calibrations are found in the
ALMA catalog that contains over 15,000 objects, south of δ = 45◦ , nearly all of them small-diameter quasars.
Information on calibrators near a specified target can be selected, plotted and downloaded to aid in the selectionof the best calibrator(s) for any target6 .
The ALMA catalog is compiled from many major catalogs, mostly at frequencies between 1.4 and 23 GHz,
over the last 30 years. The catalogs include VLA calibrator catalog, at20g catalog, vlbi (Petrov) catalog,
CRATES 8.4 GHz compilation and the SMA catalog. Nearly all of the brightest 2000 sources in the ALMA
catalog have been observed with VLBI techniques and thus have positions that are accurate to < 0.00200 , allmeasured on the ICRF2 7 coordinate frame. It is recommended that all objects observed with ALMA use their
ICRF positions.

10.5.1

On-Line Flagging (F)The on-line calibration system uses the results of many monitoring devices to indicate periods when data should
be flagged; for example, when an antenna pointing or focus settings are offset more than a specified amount fromthe calculated settings, or when relevant local oscillators are not locked. These flags are stored in the archive
data base in two ways, xml and binary flags. When converting from the ASDM format to the MS format, thetwo sets of flags (applyflags = T and bdfflags = T) can be inserted into the data or stored in a separate flag
table for later use.

10.5.2

Calibration-based Flagging (F)During most of the off-line calibrations, described below, additional time periods and antennas that require
flagging are often found. Examples are: noisy edge channels in the spectral windows, low relative signal in one
antenna compared with the others, and phase jumps in time. In most cases, these bad data periods can only beseen in the calibrator observations; hence, most flags associated with a calibration scan should be appropriately
extended to other source scans, spws and baselines.

10.5.3

Bandpass Calibration (B)The correction of the frequency response from flatness across each spw and polarization is the purpose of the
bandpass calibration. First, there is a residual amplitude and phase variation with a characteristic length oftens of MHz of about 10% and 5 deg. These remain stable over many hours, and are nearly independent of thesky position of the radio source8 . However, within about 5% of the band edge, larger changes occur and theappropriate channels should be flagged out. Second, an additional phase slope in the bandpass is produced bya offset delay from that assumed9 .
The residual bandpass for each spw and pol is determined from a 5 to 30 min scan of a bright calibrator
source with a known radio spectral index and no spectral features. From the CASA task bandpass the relative
amplitude and phase for each antenna/spw/pol as a function of frequency is determined. The nominal bandpass
accuracy is < 0.2% and < 0.5◦ over the spectral resolution requested. If an observation contains several tunings
or a large Doppler change, the bandpass for each setting must be obtained.
6 https://almascience.eso.org/sc/
7 /www.iers.org/IERS/EN/DataProducts/ICRF/ICRF2/icrf2.html
8 http://almascience.org/documents-and-tools/alma-technical-notes/ALMATechnicalNotes15_FINAL.pdf
9 The major delay offset is corrected on-line once a day so that the residual phase delay slope is generally small

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

Lines at known frequencies from components in the atmosphere will produce apparent bandpass amplitudechanges that are similar for all spw’s and pols. These lines will also produce system temperature increases.
These data can be used but caution is necessary, since the line amplitude does depend on the source elevation,
so it may differ between the bandpass, calibrator and the target sources. Generally, the bandpass phase is notaffected by atmospheric lines.
In Cycle 5, the bandpass calibrator is chosen from a set of 35 bright quasars, called grid sources and the list
is given in Table 10.1
Grid Sources Used for Bandpass
J0006−0623
J0237+2848 J0238+1636
J0319+4130
J0423−0120
J0510+1800 J0519−4546
J0522−3627L
J0635−7516L J0750+1231 J0854+2006
J1037−2934
J1107−4449
J1146+3958 J1229+0203L J1256−0547
J1427−4206
J1517−2422 J1550+0527
J1617−5848
J1733−1304
J1751+0939 J1924−2914
J2025+3343
J2148+0657
J2232+1143 J2253+1608
J2258−2758
L = large scale emission

J0334−4008
J0538−4405
J1058+0133
J1337−1257
J1642+3948
J2056−4714
J2357−5311

Table 10.1: The 35 Grid Sources Used by ALMA

10.5.4Gain Calibration (G)Nearly all ALMA observations use the phase referencing technique to measure the residual antenna-based temporal amplitude and phase variations. The weather conditions (transparency of the atmosphere and magnitudeof the phase fluctuations) are monitored continuously so that the chosen PI observation can be successfully
phase-referenced. The effectiveness of the on-line WVR-corrections is critical, often removing up to 75% of theshort term phase changes. See Chapter 11 for more descriptions of the on-line observational checks.
The choice of calibrator is critical to the success of the reduction and imaging. Generally, the best calibrator
is that closest to the target that can determine the antenna-based solutions with an SNR> 15. The calibrator
parameters needed for the optimum phase reference choice are given in Table 10.2. For many targets thecalibrator choice can be automatically selected from the ALMA catalog and is described in Section 8.1. However,for long baseline and high frequency targets, the availability of a suitable calibrator is checked by the JAO-staff
months ahead of the proposed observation. These additional observational checks are described in Section 10.6.
The CASA task gaincal is used to determine the antenna-based amplitude and phase gains from each phasecalibrator scan. Several recommendations are: (1) Pick a reference antenna near the center of the array thathas not been recently moved10 . (2) If the calibrator is a relatively strong quasar, antenna-based solutions canbe generated accurately for each spw and polarization. (3) For a weak phase calibrator for which more than
5% of the data are flagged using each spw solution separately, use the bandpass observation to align the phasesof the eight data streams (4 spw, 2 pol’s) which can then be added (combine=’spw’; gaintype = ’T’ to give an
SNR increase of 2.8) before determining a solution. This will enable the use of calibrators that are significantly
closer to the target.
After using gaincal in a manual or pipeline script, the plots from CASA tasks plotcal or plotms should be
inspected. The ALMA pipeline can generate appropriate flags from anomalous calibrator values but the PI
should inspect the flags since not all problems are found by the pipeline. Some guidelines in the interpretationof the calibration plots are:(1) The antenna-based amplitudes should not vary by more than about 10% over the observation period,and not differ by more than about 20% among the antennas. For antennas with low gain values or obvious
drop-outs, check on possible reasons: for example, is the Tsys for the antenna large? Are there comments in theobserving logs about pointing errors, local-oscillator drop-outs?
10 CASA helper task of es.getReference does this10.5. OFF-LINE CALIBRATIONS

151

Flux Limit-Avg Separation for Phase Calibrators
BAND Frequency Tsys PWV
Flux
AvgSep(GHz)(K) (mm) (mJy)
(deg)
3
86.2
83
5.186
4.6
1.0
3
115.3
173
5.186
9.7
1.4
4
147.0
86
1.796
4.9
1.2
5
192.0
100
1.500
5.3
1.3
6
230.5
102
1.262
6.0
1.4
7
345.8
151
0.658
9.5
1.6
8
461.0
431
0.472
30.0
1.9
8
492.2
638
0.472
46.0
2.2
9
624.2
4302 0.472 364.4
8.0
9
658.0
1721 0.472 152.9
4.6
9
691.5
1231 0.472 114.9
4.3
10
806.7
2405 0.472 271.3
7.1
Table 10.2: The minimum phase calibrator flux density in mJy needed for an antenna-based amplitude accuracy
of 7% and a phase accuracy of 4 deg rms (15 SNR) with 120 seconds integration time, forty-three 12 m antennas,
an elevation of 50 degrees, and no coherence loss. The total bandwidth, νBW in both polarizations of 7.5 GHz
is assumed.

(2) The antenna-based phase difference between adjacent calibration scans should be relatively small. For
example, if the antenna-based phase change between scans exceeds about 60◦ , interpolation to the intervening
target scan becomes uncertain. This often occurs at longer baselines and high frequencies, and flagging of thetarget data during these intervals may be useful to improve the image quality. This is the criterion used by the
Go-noGo system at the telescope to decide if observations are feasible for a project.

10.5.5Flux Density Calibration (T)The gain calibration determines the relative amplitude between the phase calibrator to an accuracy of < 6% perantenna solution per scan. This accuracy depends on the strength of the calibrator and other array parameters.
However, the amplitude accuracy of the image will be significantly better since it is based on many antenna/scansolutions, so that a 1% accuracy of the target, relative to the assumed flux density of the phase cal, is typical.
In order to determine the absolute flux density scale of an observation, the observing schedule should containeither a solar system object and/or a bandpass calibrator with a recently measured flux density from the ‘Grid’source monitoring. The present list of solar system objects used as primary flux density references are: Uranus(standard, but large in angular size); Neptune, Mars (Large), Ganymede, and Callisto. Ceres, Titan, Juno,
Vesta and Pallas are also used, but may be too weak at Bands 3 and 4. The flux density model accuracy of thesolar system objects is 3% at Band 3, rising to 15% at Band 9.
Once the Tsys corrections are applied to all scans, the known flux density of the grid source and/or solar
system object can then be transferred to the phase calibrator to an accuracy of a few percent since the ALMA
antenna gains do not vary by more than this level. If more accurate relative and/or absolute flux density
precision is needed for a source observed over time or over frequency, contact your local arc for additional
calibrations that may be necessary.
Because of the excellent stability of the antenna gains and the number and quality of the antennas, thea-priori calibration from Kelvin to Jansky is possible. Tests are not underway to determine the conversion
accuracy and stability.

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10.5.6

CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESPolarization Calibration (p,X)

The XY and YX (crossed-hand) true visibility functions, in addition to the XX and YY, are needed to determine
the linear and circular polarization images of a source. However, these two cross-hand terms are contaminatedby three effects that must be calibrated: 1) The delay and phase difference between the X and Y total intensity calibrations to remove the global delay and delay difference after the total intensity calibration; 2) the
non-orthogonality for each antenna-spw of the X and Y feeds, and 3) the slight rotation of the antenna-feedorientation from that assumed. The last two effects are parameterized by D-terms, two complex values as afunction of frequency for each antenna-spw.
The present ALMA linear polarization calibration method requires the addition of observations of a bright,
polarized source during a science experiment. The accurate linear polarization of the quasar need not be known,
only that it is more than about 2.0% polarized in order to have its true polarization signal dominate over thatof the polarization error terms. In order to separate the quasar true polarization XY and YX from that causedby the three contaminants listed above, the polarization calibrator must be observed over a period of threehours (depends on declination) for its parallactic angle to rotate at least 60◦ . This means that the polarization
calibration of a science target requires at least a three hour observation, even for target observation lengths that
may require only a few minutes. Other polarization methods that require a shorter period of time are currently
under investigation.
The D-terms vary considerably over the primary beam so that at present only sources with a limited angularextent can be accurately imaged. In Cycle 5 this size limit will remain limited to the 70% power point of theantenna primary beam. Both 12-m and 7-m Arrays can be used for polarization observations, but are limited
to Bands 3, 4, 5, 6 and 7. Investigations are in progress to open up the area of polarization imaging, withmosaicing in all Stokes parameters an ultimate goal.
Circular polarization information can be determined from the four Stokes parameters (I,Q,U,V) that aremeasured. However, the calibration accuracy of V remains uncertain, especially at a location more than a few
percent of the primary beam size from the beam center, and thus circular polarization is not currently supported.
Please contact the ALMA helpdesk of your local arc for more information about any circular polarization resultsfrom your data before their publication.

10.6

Additional Calibration Concerns

10.6.1

Observations at Frequencies > 400 GHz

At high frequencies the number density of detectable quasar calibrators drops significantly because of thedecrease in ALMA sensitivity and the negative spectral index of quasars. Thus, it is difficult to find a calibrator
that is closer than 3◦ to a target needed for accurate phase referencing. In Cycle 4 and continuing at least into
Cycle 5, JAO and ALEGRO (EU ARC Node in Leiden, Netherlands) plan and carry out short observations withpart of the ALMA array in order to determine which of the 15,000 sources in the ALMA catalog are sufficiently
strong to be used as a nearby calibrator for each PI target. These observations are called Cone Searches. Withan observation of a few minutes, the suitability of a candidate calibrator can be ascertained (see Section 8.12)

10.6.2

Observations with Baselines > 3 km

The calibration of long baseline observations (> 3 km) is similar to those at shorter spacings, with the maindifferences being that the phase calibrator is visited more often, and should be as close to the science target as
possible. Starting with Cycle 4, cone searches, that were described above for the high frequency targets, havebeen used to find the closest detectable calibrator for a long baseline observation.
Do not propose for the longer baselines unless there is sufficient information about the smallscale structure in the target. Otherwise, you may have to smooth the data to detect the source at a lower
resolution—which essentially removes the longer baseline data from the image.

10.6. ADDITIONAL CALIBRATION CONCERNS

153

Continuum Observations: Does the source have sufficiently small-scale structure in order to benefit from long
baseline observations? For example, at 350 GHz with a 5 km array with 40 12 m antennas, the resolution
is 0.0600 and the rms image noise in a 600-sec integration over a bandwidth of 7.6 GHz is 0.1 mJy. Hence,unless there is sufficient substructure in the target at this angular size, the long baseline will dilute theextended source emission.
Narrow line emission at high resolution: The imaging of line emission with the longest baselines is challenging.
For example, at 89 GHz with 0.25 km/s channels, 40 antennas, 3.5 hours on-source, and an angularresolution of 70 mas, the expected spectral rms noise per channel is 2.0 mJy/beam but only 63K insurface brightness sensitivity. Hence, a brightness of emission of at least 300K is needed for a solid
detection.

10.6.3Phase Calibration with Narrow Bandwidths

When observing a target within narrow spw bandwidths (typically < 250 MHz), a suitable phase calibrator,
especially at the highest frequencies, may not be detectable with a one to two minute calibrator scan. Two
methods of calibrating these narrow bandwidths are available:
One wide spw: Low-SNR calibration. If the aggregate bandwidth in the combined spw’s in the experimenthas a bandwidth > 1 GHz (usually because one of the spws is wide band), then there will be sufficientsensitivity to determine the antenna-based gains using the low SNR calibration. This method, which uses
the bandpass scan to determine the spw phase differences, is described in Section 5, Gain Calibration.
Band-Width-Switching. If all of the spw’s are narrow bandwidth, it is likely that a suitably nearby phasecalibrator cannot be detected within scan, even after phasing up all of the spw’s. In this case, the strategy
for phase calibration is to observe the phase calibrator with wide-band spectral windows and the target
in the desired narrow bandwidths by switching the spectral setup between the relevant scans.
The antenna-based amplitude ratio and phase difference between the wide-band spw’s and the narrow band
spw’s is measured by observing a strong calibrator, also called a Differential Gain Calibrator (DGC), withboth spw setups. In order to remove short-term phase changes, the measurement of the DGC is made inthree consecutive scans with: wide band, narrow band, wide band. The temporal variation between thetwo wide band scans is used to remove the temporal variations in the intervening narrow band observation.
The advantage of the second strategy is that all of the target spw’s can be used for narrow-band spectroscopy, whereas the first strategy uses one wide band spw for calibration purposes. But, the first is
simpler to schedule, somewhat more efficient, and easier to calibrate.

10.6.4Band-to-Band Calibration

For phase referencing at frequencies above 400 GHz, finding a calibrator closer than 5◦ to the target is rare(even after using cone-searches), whereas a closer calibrator at lower frequencies is often available. The goal of
band-to-band phase transfer is to use observations of a phase calibrator at a lower ALMA Band, scale theseantenna-based phase solutions (G) to the higher frequency band, and then apply this calibration to the target
source, observed only at the higher frequency.
This method is being tested and may be available for Cycle 6. The main experimental problem is that thephase difference between the low and high frequencies must be determined at one specific time. Since ALMA
cannot observe at two frequencies simultaneously, the phase difference measurement is contaminated by theatmospheric phase fluctuations between the high and low frequency observation. The minimum switching time
is now about 70 sec, but could be decreased to 20 sec in the next year, permitting a much more accurate
measurement of the instrumental phase difference between frequencies.

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10.6.5Check Source

Some observations (those at high frequency or long baselines) contain short observations of a weak calibrator
source, called a check source, in order to provide an estimate of the quality of the observational calibration
based on the check source image purity and position). For Cycle 5, a check source is included in all observations
with angular resolution < 0.2500 and for all observations at a frequency greater than 400 GHz. All potential
check sources are in the ALMA catalog; a typical choice is weaker than the phase cal but at a similar distancefrom the target. It is typically observed every third phase-target cycle with less integration time than the phasecalibrator scan. After normal calibration of the data, an image of the check source provides a good indicationof the image quality (its dynamic range) and positional accuracy (offset from the phase center) since the checksource position is usually known to 2 mas.

10.6.6

Astrometric Observations

ALMA Nominal Positional Accuracy
The absolute positional accuracy of an ALMA image, made with normal phase referencing depends, on thetarget signal to noise and the array resolution, but also on the quality of the phase calibration that depends on
the atmosphere delay fluctuations and the proximity of the phase calibrator to the target.
First, the signal-to-noise of the source image and the resolution of the observations provide a minimum
obtainable astrometric precision. The relationship is given by∆p = 60 mas ∗ (100GHz/F REQ) ∗ (10km/BSL)/SN R(10.5)

where∆p = Theoretical accuracy limit by SNR only,
BSL = Maximum baseline length in km,
F REQ = The observing frequency in GHz,SN R = The signal to noise at the source peak.
For example, at Band 7 (350 GHz), for the 1-km BSL configuration (C40-5), and for SN R = 40, the theoreticalastrometric accuracy is 4.2 mas.
However, for a reasonably bright and compact source, the astrometric accuracy is often limited by the size
and nature of the phase variations with time and over the array, rather than that from the SNR limit and array
resolution. An estimate to the best positional accuracy of an ALMA observation with normal calibrations are:1) from the SNR estimate given above; 2) 5% of the resolution; 3) or a limit of 3 mas, whichever is the largest.
This limit is frequency independent.
Optimum Choice of Frequency and Configuration
The choice of configuration and observing frequency is important to the success of an astrometric observation,and depends on the spectral and angular properties of the radio source. Since virtually all astrometric phaseerrors are delay-like and scale with frequency, simply changing an observation from a low frequency to a higher
frequency, other things being equal, will not produce better astrometric accuracy even with the higher resolution.
Of course, for thermal objects, the increase in flux density with increasing frequency does increase the SNR witha probable gain in precision. On the other hand for a non-thermal source a lower frequency may give better
positional accuracy.
The larger the configuration, the more accurate will be the astrometric results. But, the positional accuracy
tends to increase only with the square-root of the maximum baseline length of the array for two reasons: (1)Most of the phase/delay errors also increase somewhat with baseline length, so the gain in astrometric accuracy
varies less than linear with the configuration size: (2) If the object is not a point source, then its peak brightness

10.6. ADDITIONAL CALIBRATION CONCERNS

155

will decrease with the increased resolution, limiting the astrometric accuracy from SNR considerations and withthe possible change of the maximum brightness position as a function of resolution. Hence, choose the frequency
and configuration that best suits the celestial object—where it is strong but not too resolved.
More Sophisticated Astrometric Calibrations
When the SNR of the object is sufficiently large (> 20) and point-like, increased astrometric precision to < 1
mas can be obtained with ALMA with somewhat more complicated calibration strategies. Some suggestions
are given below, but please contact your local arc for more information about setting up your astrometricobservations.
Check source: Make sure a check source is included in the observation plan. Even though observed typically
only a few times per observation, for a shorter time than the phase calibrator, the check source image
quality and its positional offset are an indication of the image quality and position accuracy of the target.
This is minimal but useful information for assessing the accuracy of the target position.
Second Phase Calibrator: If the check source is sufficiently strong and close to the target, then it can be used
as a second phase calibrator by obtaining antenna-based phases in the same manner as that for the main
phase calibrator. How to use two or more phase calibrators to provide better astrometric accuracy should
be discussed with your local arc astrometric expert. This multi-phase calibrator observation requires UserSpecified Calibration and is therefore a non-standard mode. One example is the use of two calibrators on
approximately opposite sides of the target. The antenna-based phases derived from each of the calibrators
can be averaged to determine an estimate of the phase calibration near that of the position of the target.
Experiments of this type of calibration can produce astrometric precision to 0.5 mas with baselines 7 km
or longer.
Phase Stability: Request better than average phase stability at the frequency of the experiment, although keep
in mind that the observatory cannot guarantee this. While large phase fluctuations are a detriment to
all ALMA observations, the effect on positional accuracy is more serious than that for image quality. For
example, image distortions can be reduced using self-calibration techniques, whereas it does not improve
the astrometric precision.

10.6.7

Self-Calibration

If the target has significant emission at the longer spacings, then self-calibration should be considered. Thismethod simply uses the CASA gaincal task on the target data using the phase-referenced image (input image
model from clean) in order to determine the residual phase errors between the data and model.
To determine if self-calibration is possible, the correlated flux density of the target at the longer spacings
should be at least that needed to detect a phase calibrator, which is listed in Table 10.2 For example at Band7, with 7.5 GHz bandwidth, the correlated flux density of the target must be > 125 mJy at the longer baselines
in order for self-calibration to be successful. Such precise knowledge about the target may not be known, but
the PI should have some indication of small-scale structure to indicate whether self-calibration is a possibility.
When in doubt try the self-calibration. It will be obvious if the SNR of the solutions are poor, especially forantennas near the end of the array.

10.6.8

Total-Power Calibrations

For sources that are significantly more extended than the 7 m primary beam size, the 12-m TP Array (the PM
antennas each used for scanning over a source) are used to make on-the-fly raster observations that cover theappropriate target area. The observing modes are discussed in Chapter 8 and the imaging in Chapter 7.
Tsys Calibration: The data are calibrated into a brightness temperature in units of Kelvin using the equation
T a∗ = Tsys (ON − OF F )/OF F , where Tsys is the system temperature and ON and OFF are, respectively,

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the measurement on-source (during the raster scanning) and off-source (observations towards a definedreference position which should contain only background emission).
Baseline Subtraction: After applying the Tsys calibration, the off-source regions within the on-the-fly area
should be near zero emission for all spectral channels. However, atmospheric changes during the observations can produce a small change across the spectrum at these off-source positions. These off-source
offsets can be used to correct the data from all raster positions. More details are given in Section 8.6.
Flux Calibration: In order to convert the single-dish data from units of Kelvin to units of Jy/beam, a conversion
factor and the effective primary beam size, after the gridding used to determine the total power image, isapplied. These corrections are stable over long periods of time and are measured by the ALMA staff asneeded, and applied in the total power reduction scripts.

10.6.9Acknowledgments

Many people contributed to the checking, revising and improving of Chapter 10. I thank: Yanett Contreras,
Akihiko Hirota, Neil Phillips, Carmen Toribio, and to Catherine Vlahakis for her detailed and germane comments.

Chapter 11

Quality Assurance
The goal of ALMA Quality Assurance (QA) is to ensure that a reliable final data product is delivered to the PI,
that is, the product has reached the desired control parameters outlined in the science goals (or is as close tothem as possible), it is calibrated to the desired accuracy, and calibration and imaging artifacts are mitigatedas much as possible. The QA analysis will be based on a calibration plan that specifies which observations mustbe acquired and at which intervals to monitor system performance and environmental factors as they evolvewith time. Furthermore, it will also be used in assessing the merging of data within each science goal takenwith different configurations, the inclusion of 7-m Array and TP Array data, and the final image quality. Errors
introduced by user supplied parameters, such as incorrect source coordinates, inadequate frequency setting (e.g.
an incorrect redshift) or inadequate sensitivity limits (leading to an inadequate integration time or inadequate
uv plane coverage) are outside the scope of the ALMA QA, unless the error occurred due to faulty informationor tools provided by the Observatory.
To be more efficient in detecting problems, ALMA QA has been divided into several stages that mimic themain steps of the data flow. The broad classification of this multi-layered QA approach is:
QA0: Monitoring of calibrations and overall performance during observations
QA1: Measurement of performance parameters and telescope properties by the observatory
QA2: Full Calibration and generation of science products
QA3: Issues found with the data by the PI or the ALMA contact scientist after data delivery
The QA0, QA1 and QA2 stages will be handled by the Program Management Group (PMG) and the DataManagement Group (DMG) (with contributions from ARC personnel) using the ALMA Quality Assurance(AQUA) Tool (see Section 11.6). Responsibility for data quality assurance in Chile rests with the Data Manager
and his Deputy, within the Department of Science Operations, drawing upon the resources of the Program
Management Group and the Data Management Group. The final output of the ALMA QA0-QA2 process is a
“QA Report” per ObsUnitSet (Member or Group1 ) that summarizes all the relevant QA information for eachof the different QA stages up to, and including, the final imaging2 . This report is included in the data package
delivered to the PI. The QA3 stage will be handled separately, by the ARCs, via JIRA3 tickets created by the
ARC personnel (see below). A more detailed description of the different stages of QA is given below.
1 Group ObsUnitSet processing, that is, the combination of datasets taken in different configurations/arrays, will only be done
sporadically during Cycle 5. It is expected that group processing will be implemented as a regular data reduction strategy in later
ALMA cycles.
2 For datasets that have been processed manually or those that required additional imaging, no imaging report will be provided
during Cycle 5
3 JIRA is a proprietary issue tracking product, commonly used for bug tracking, issue tracking, and project management

157

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11.1

CHAPTER 11. QUALITY ASSURANCE

Cycle 5 Quality Assurance Goals

The ultimate goal for ALMA QA is that the delivered products are considered "Science Ready", suitable forpublishing with little need for the user to reprocess. However, ALMA cannot guarantee that all the scheduled
Cycle 5 projects are completed (especially those with grades B and C), or that specific criteria like sensitivity
or angular resolution are precisely met, give the restrictions of the array configurations, system performance atthe time of the observations, etc. The observatory will therefore attempt to meet the sensitivity and resolution
stated by PIs in their Science Goals, within certain tolerances as described later in this chapter. In principle,
each project component ("Schedule Block" or SB) is scheduled for the number of executions that are expected
to reach these goals (based on nominal Array performance values). Additional executions may be needed during
the observing cycle if specific executions do not pass QA0 or QA2 (see below).
Observers may need to invest their own time and expertise to ensure that the data products are of theappropriate quality and to re-reduce the raw data if the quality is not satisfactory. This may include the needto visit the relevant ARC or ARC node to get help and to assist with quality assurance and potential data
reduction.

11.2

QA0

QA0 is a near-real-time verification of data quality. It deals with rapidly varying performance parameters (ontimescales of an SB execution length or shorter) and thus has to be performed at the time of data taking.
Assessment is performed by AoDs (Astronomers on Duty) at the OSF, with support from the Science Archive
Content Managers, using the AQUA software tool, based on semi-real time output of the calibrations (obtainedby the real-time TelCal ALMA software) as displayed by QuickLook and the “Calibration Summary” files thatare produced at the end of each execution of an SB. This information is complemented with reports derived using
Monitor and Control display tools to monitor specific parameters not directly tracked by the calibrations (e.g.,
total power level variations, weather parameters, etc). AQUA can currently generate the complete Calibration
Summary file contents using the information available in the ASDM files for each Execution Block.
QA0 metrics/parameters have been selected to check the health of the whole signal path from the atmosphere
down to the back-ends. These parameters can be grouped into the following categories:
Atmospheric Effects: Weather Parameters, Sky Opacity, System Temperature, Phase Fluctuations, Total
Power Levels, WVR Outputs.
Antenna Issues: Antenna Gain, Relative/Offset Pointing, Focus, Antenna Tracking, Geometric Shadowing,
Nutators (unavailable for Cycle 5).
Front-End Issues: RF Bandpass, Sideband Ratios, Receiver Temperatures, LO Lock Status.
Connectivity Issues: Total Power levels, Delay Measurements, System Temperatures, RF Bandpass, LO Lock
Status.
Back-End Issues: Total Power levels, RF Bandpass, Delay Measurements.
The tolerances for these parameters that have been adopted by ALMA for this Cycle are listed in Section 11.7.
Apart from these, the metadata is checked for inconsistencies and the amplitude calibrator for recent flux
measurements. Each SB execution is classified into three categories, i.e. QA0_PASS, QA0_SEMIPASS and
QA0_FAIL, based on the criteria described in that Section. QA0_PASS are datasets that comply with all the
QA0 criteria and that will be used for the final imaging. QA0_SEMIPASS are datasets that do not fulfill all
the QA0 criteria, but contain data that is deemed of scientific value4 . QA0_SEMIPASS data are not includedin the final data products, but PIs can access those data and reduce them if they wish. QA0_FAIL datasets
are those that are not included in the other two categories. Since they represent unusable/uncalibratable data,
they are not visible to the PIs in the Project Tracker.
4 For instance, the presence of usable calibrator data.

11.3. QA1

159

For operational purposes, individual SB executions during Cycle 5 will be counted as a normalized fractionof the theoretical sensitivity that a given execution should have reached based on the number of antennas thatshould be in an array in Cycle 5 (i.e., forty-three 12 m antennas on the main array, ten 7 m antennas on the
Morita Array, and three TP 12 m antennas), and the average system temperatures expected at the frequencyof the observations. Executions with higher RMS noise levels than the reference will have fractional executions
between 0 and 1, while those with lower RMS noise levels, which can be achieved, for instance, with a larger
number of antennas in the array, or with lower system temperatures, will have a fractional execution value
above 1. The number of executions may be changed (i.e., increased/decreased) based on the total execution
fraction of a given member OUS at a given point in time.

11.3

QA1

QA1 tracks array performance parameters which vary slowly (on timescales longer than a week). They aremeasured by AoDs and System Astronomers executing standard calibration SBs created as specified by the
Calibration Plan. The QA1 related parameters are, in general, measured at predefined periods during the monthas “Observatory Tasks”, or if significant deterioration of performance is detected during operations. Currently,
the various tasks to measure these parameters are done by different software packages. This situation will change
in the near future by including some of the packages within TelCal and/or CASA. Reduction of “Observatory
Tasks” output is done jointly by the AoDs and System Astronomers within the DMG. The product is a setof parameters with errors that are ingested into the TMCDB (up-to-date view of the parameters used in any
observation), so that they can then be used during observations. Any problems with QA1 that would significantly
downgrade the quality of the data will be solved by the observatory by stopping the science observations andre-calibrating the problematic parameters of the array.
The tasks that fall into this category are:Array Calibrations: Baseline measurements, Delays
Antenna Calibrations: All-sky pointing, Focus curves, Surface measurements, Beam patterns (including polarization observations), Relative delays between polarizations of the same band
Source Calibrations: Monitoring of solar-system flux standards, and secondary quasar flux standards

11.4

QA2

QA2 deals with QA at the level of data reduction and imaging using the Science Pipeline or performed interactively by the ALMA Data Reducers Team. It is only at the stage of data reduction that the science goals
set by the PI can be compared with the actual value in the data products (i.e., RMS, angular resolution, SNR,
dynamic range, etc). The official software for ALMA data reduction is CASA.
During Cycle 5, it is expected that, for the ALMA standard observing modes, the automated Pipeline (seeChapter 13) will be used for the calibration of the data and imaging. The Pipeline provides a Weblog page
with detailed information on the quality of the calibration, which will provide the basis for Pipeline QA2. This
information will also be made available to the AQUA tool during Cycle 5, and the weblogs will also be includedin the data packages sent to the PIs. For manually-reduced datasets, the QA2 will be carried out with special
purpose scripts whose outputs will be included in the data packages delivered to PIs. The QA2 metrics which
determine the success of an observation are given in Section 11.7.
A summary list of QA2 parameters/issues checked during data reduction (calibration of individual Execution
Blocks and joint imaging) are:
Calibration Issues:

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CHAPTER 11. QUALITY ASSURANCE• Bandpass quality• Flux scale calibration: is the absolute flux scale accurate enough?
• Phase transfer and astrometry: Cycle time and sky separation between phase reference and target;
typical and extreme (unflagged) phase differences between phase reference scans.
• Calibration consistency if multiple arrays and/or single-dish data are combined.
Final Data Characterization:• Longest baseline, visibility coverage and time on target (after flagging).
• Synthesised beam (spatial resolution) for specified weighting scheme; specific imaging requirements(if stated by the PI). See Section 11.7 for tolerances.
• Spectral resolution and channel ranges used to make sample images.
• RMS noise in target images: Values are compared with those predicted from data after flagging andwith those requested. See Section 11.7 for tolerances.
• Residual imaging artifacts: Sidelobe Levels, effects of “missing spacings” and possible dynamic range
limitations.
• Combinations of array configurations and/or total power, e.g. amplitude scale consistency.
• Mosaicing and/or contamination by bright sources outside FOV or aliasing in clean.
• Polarization purity: minimum fractional polarization detectable, and polarization angle accuracy (ifrelevant).
The data reduction scripts sent to the PI will include any modifications to the standard scripts which were
found to be essential during QA2.
There are three possible QA2 states a reduced dataset can be placed into. QA2_PASS implies that thescientific goals, as defined by measurable parameters such as noise RMS, LAS and angular resolution, havebeen achieved within the specifications listed in section 11.7. QA2_SEMIPASS refers to those datasets thatfall short of meeting the PI requested science goals, but are otherwise of good quality (or as good as possible
with the observations that could be achieved). QA2_FAIL is a temporary state used during an observing cycle
when an observation fails to meet the PIs goals by a significant margin (see Section 11.7 of this handbook) andneeds to be scheduled for additional observations. If these data fail to obtain enough additional observations topass QA2 by the end of an observing season and they are not grade A proposals, their QA2 state is changed to
QA2_SEMIPASS and they are delivered to the PI.

11.5

QA3

QA3 is post-reduction evaluation of the data products delivered to the PIs. It is advisable that PIs check the data
products themselves and report any problems that they find to their Contact Scientist via the ALMA Helpdesk(https://help.almascience.org/). The QA3 process will be triggered by the PI, the contact scientist of other
ARC personnel. They will open an ALMA Helpdesk ticket reporting a problem with the data products which
may reflect an underlying problem with the data, observing procedure or calibration. The ARC receiving theHelpdesk ticket will retrieve the data from the archive and evaluate the nature of the problem. The evaluation by
the ARC should include an assessment on whether the problem is present only in a particular dataset or whether
others taken under similar set-ups and conditions also show it. If the problem is deemed to reflect a problem
with the performance of the array, the calibration or data reduction processes, or the QA process, the ARC willcommunicate their findings to the observatory, which will work on solving the problem in collaboration with
the ARCs. The result will be communicated back to the reporting investigator. An extension of the proprietary
period of delivered datasets with QA3 issues will be granted based on the policies in the Cycle 5 User Policies
document.

11.6. THE QUALITY ASSURANCE REPORT

11.6

161

The Quality Assurance Report

During Cycle 5 the Quality Assurance Reports of QA0, QA1 and basic QA2 will be accessible to the PIs using
SnooPI. These reports will be generated using the AQUA tool. For Pipeline calibrated datasets, additional
reports (Weblogs) will be sent to the PI as part of the data delivery. For non-standard observing modes that
require manual data reduction, script-generated QA2 reports will be delivered instead.
The basic unit of a Report is the ObsUnitSet, which represents a scientific goal stated by the PI during
Phase 1 (project creation and review). An ObsUnitSet will typically contain several executions of SBs. For
each execution QA0 and QA1 reports are generated by the AoDs using the information available at the time ofthe observations, which includes TelCal outputs and other monitoring data (weather, total power levels, CorrGUI outputs, etc). A given execution is only cleared for reduction if it has passed both QA0 and QA1. There
will be only one QA2 report for the whole ObsUnitSet5 generated by the DMG/ARCs at the end of the data
reduction process; this also has to be approved before the data products are delivered to the PI. It is expectedthat sometime during Cycle 5, a complete interface between the Pipeline and AQUA is made available. Fromthat point onwards, complete QA Reports will be generated using the AQUA software and delivered as such(including the Weblog information). The final report per ObsUnitSet delivered to the PI would in that case bea concatenation of all the relevant QA0 and QA1 reports per execution with the QA2 report. Comments oneach stage of the QA process (with supporting images, if required) would be added to the Report.
The standard policies for QA0 and QA1 failures are that the observations of those Execution Blocks thatfailed have to be repeated. Failures to pass QA2 may trigger additional observations if the achieved RMS
or imaging parameters do not fullfil the QA2 pass criteria. Additional observations may not be possible incircumstances, such as projects with very tight weather, very specific configurations, or time constraints. If theavailable data are insufficient to reach the required sensitivity, but are otherwise of good quality, they will be
released to the PI at the end of the cycle.

11.7

QA Criteria

For an execution to be considered QA0_PASS it must have a phase RMS (post-calibration) of ≤0.5 rad, enoughcalibrator data to be able to calculate necessary calibration terms (bandpass, amplitude, complex gain, and, if
relevant, polarization), and enough science data to be useful (see below). Furthermore, the execution has tobe "significant" in terms of the fractional execution (i.e., more than 0.2) OR in terms of sensitivity (i.e., morethan 50% of expected Cycle 5 sensitivity per execution of a given SB). If it does not meet these criteria, but
has some useful data (calibrator or source), it is classified as QA0 SemiPass. Such data are available throughthe ALMA archive, but they will not be used in the generation of the imaging data products. If neither of these
hold, the execution is deemed to have no useful data and declared QA0_FAIL.
The QA0 pass/semipass/fail criteria that have been adopted by ALMA during Cycle 5 5 are based on thefollowing:- Antennas: QA0_SEMIPASS for fewer than 20 antennas available in the 12-m Array or fewer than
5 antennas in the 7-m Array or fewer than two Total Power Array antennas. Situations that will beconsidered to render an antenna unavailable include issues with the antenna itself (including large pointing
scatter of > 1/10 HPBW, and bad band focusing with offsets from model of > 1/5λ in Z and >λ in X/Y),
as well as issues with the receiver bands not being available at the antenna for a given observation.
- Bandpass: QA0_SEMIPASS if the bandpass calibrator signal is too weak, with amplitude wiggles acrossthe spectral window of > 3 dB on the autocorrelations (not due to atmospheric features) or strong CW
signals, and the phase/gain calibrator cannot be used instead.
- System Temperatures: QA0_SEMIPASS if more than 20 antennas in the 12-m Array, or more than 3antennas in the 7-m Array, or more than one Total Power antenna have Tsys values > 50% of the others,
5 As stated above, processing of group ObsUnitSets will not be regularly done during Cycle 5. PIs should assume that allstatements here apply to member ObsUnitSets.

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have differences between polarizations > 50%, or have Tsys > 2000 K.
- Gain: QA0_SEMIPASS Phase RMS > 0.5 rad, on scans of the gain calibrator, for a significant fractionof the baselines after WVR phase correction (using all possible bandwidth in a given spw)
- Execution: QA0_SEMIPASS All datasets whose execution failed at some point and contain less than
20% of the expected execution time of a given SB execution.
- Calibrations: QA0_FAIL Datasets missing critical calibrations that render them uncalibratable. Execution Blocks only containing usable calibrator data shall be labelled QA0_SEMIPASS.
- Storage: QA0_FAIL Data that could not be read from the Archive- Time-Critical Observations: QA0_SEMIPASS if observations have not been carried out at the requested dates and times.
For any other situation, the data will be accepted, although it may require some additional flagging for misbehaving antennas, baselines, etc. Any problems with QA1 that would significantly downgrade the quality of thedata will be solved by the observatory by stopping the science observations and re-calibrating the problematicparameters of the array using standard observatory tasks.
For QA2 at the GOUS (Group OUS) level (or at the Member OUS, MOUS, level if no data combination isrequired), the main criteria are the achievement of the requested noise RMS in the images (it must be within
10%, 15% and 20% of the goal for Bands 3/4/5/6, 7/8, and 9/10, in flux units per beam, respectively), thesynthesized beam shape6 (the angular lengths of the major and minor axes of the synthesised beam must bewithin ±20% of the angular resolution requested by the PI) and the calibration quality (phase RMS of 5 degrees
after calibration, and absolute flux scales within the ALMA specifications7 ). For the individual MOUS thatmust be combined at the GOUS level, the RMS values quoted above should be scaled by the relative sensitivitiesof the configurations, using the most compact 12-m Array configuration as reference.

6 During Cycle 5, SBs shall be executed following the recommendations given by the OT, which will select the configuration that
produces the closest values to the requested angular resolution.
7 Absolute Calibration accuracy is regularly checked as an observatory task.

Chapter 12

Data Flow and Logical Data StructureThis chapter describes the data flow process from the observations until data is ingested into the ALMA Archive.
It includes a brief description of all the main software subsystems involved in the data acquisition and archiving,as well as a summary of the metadata structure adopted by ALMA.

12.1

Data and Control Flow

This section describes the overall control of the ALMA system and the flow of data. A summary of the main
actors and operations involved in the observations is shown in Figure 12.1.
Each of the gray boxes in Figure 12.1 represent an ALMA subsystem involved in the observations. The restof the boxes, colored according to the actor involved, include labels for the actions performed either by external
agents (actors) or by those subsystems.
A typical observing session would be started by the Telescope Operator interacting with the Executive
subsystem via one of the dedicated control computers in the Control Room (the so-called “Standard Test
Environment” or STE). The Executive subsystem is in charge of starting up the ALMA Common Software(ACS) and its Common Object Request Broker Architecture (CORBA)-based services and then initializing allof the various software subsystems involved in the observing and data storage process. Once all the components
are ready, the Executive also handles asynchronous events from several of the subsystems and responds tothem accordingly. Among the events, the Executive also publishes a list of error conditions to the attentionof the operator and the requests for status of the Control, Telescope Calibration, Correlator and Schedulingsubsystems.
The actual observations start by manually creating an array, which means selecting all the antennas thatwill be involved in the observations. A Scheduling Block (SB) is selected from the list provided by the Scheduler
subsystem, and the execution is started. An SB is the smallest, calibratable element of a project and they are
kept in the proposal along with other ancillary information, in a series of XML tables (XML is the Extensible
Markup Language format, common in database systems). All the SBs for a given observing Cycle are stored
in the Archive after successful Phase 2 completion. The Scheduler subsystem keeps a local up-to-date databaseof all the SBs (including their status) for that Cycle. The Telescope Operator and Astronomer on Duty (AoD)
can either let the Scheduler suggest possible SBs to execute, or they can carry out targeted searches of the local
database. For standard SBs the Scheduler can produce a ranked list of optimum SBs to execute next based on
weather conditions and forecast, hardware and configuration status, project completion status, representative
source position on sky, proposal rank and score and Executive percentages. The Telescope Operator and AoD
can follow the suggestion of the Scheduler and select one of the top-ranked SBs or something else for execution.
Selections that do not follow the advice of the Scheduler must be fully justified by the AoD and will be used to
improve the selection algorithm within the Scheduler. It is expected that by Full Operations the algorithm will
be optimized to the point that the Scheduler can run an automatic sequence of SBs.

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Figure 12.1: Main actors and roles during observations with ALMA. The horizontal direction represents time
evolution.

Once the execution of the SB has been selected from the Scheduler, the observation is set up. The SBcontains which observing script to use. The observing scripts, which reside in the Science Observing Scripts
module, uses the information from the SB as input to determine the necessary execution sequence. After the
SB has been selected, the SSR scripts (1) use the information in the SB, including the observing script, to set
up the observation and calibrations. The SSR script then sends this information to the Control subsystem asa sequence of scans and subscans. The scan and subscan specifications specify for each subscan the tuning,phase center and antenna pointing, calibration device position, intent metadata (to convey the purpose of
the scan/subscan), and other parameters that may need controlling from the observing script level. Control
executes the scan/subscan sequences by commanding all relevant hardware, the relevant correlator subsystem(Baseline (BL) or Atacama Compact Array (ACA)) and the Total Power Processor (TPP), resulting in raw
data and metadata being sent to the archive subsystem and made available to the online Telescope Calibration(TelCal) subsystem. TelCal publishes results from calibration scans it reduces, which are sent to the archive ascalibration tables, and received by the QuickLook GUI and other software to display results to the Operators
and AoD to evaluate the observation progress. To carry out its function, Control has many interfaces to the
instrumental hardware. It is in fact one of the truly real-time subsystems within ALMA because it is in chargeof synchronization of the actions of all antennas (scanning, source acquisition, etc) and the correlator to within
48 ms (Timing Event (TE)). Control is also in charge of storage of data from all monitor points set in the
hardware of the ALMA array.
Each run of an SB produces an Execution Block (EB) that is stored into the archive through two parallel12.1. DATA AND CONTROL FLOW

165

paths1 and is handled by a part of the Control software called the “Data Capture” module (see, for instance, the2006 ADASS contribution by Hafok, Caillat and Mcmullin). The best way to describe the Data Capture module
is as an interface between the real-time domain of the data taking and the storage side. As an interface, it
captures and stores into the Archive all the relevant meta-data information pertaining to a complete descriptionof the data and their supporting calibration. In addition, it also monitors datasets and condenses all that
information into a set of XML tables. The contents of all these tables are defined in the ALMA Science Data
Model (ASDM). Together with these tables, Data Capture also creates the relevant links of these metadata to
the actual bulk data that the correlator stores directly into the archive. Furthermore, it also provides calibration
data to the TelCal subsystem for calibration reduction and the Quicklook GUI for displaying in semi-real time.
Finally, when the SB is finished, Data Capture is in charge of checking that all products representing the raw
data have been produced and stored in the archive, and announces the completion of the SB to the Scheduler
subsystem. It is clear from the list of roles above that Data Capture is a very complex module: it has tointerface with the Correlator, coordinate the backend data with the metadata, and receive, store, and link
together supporting observation information (source information, spectral set-up, etc) and monitoring datafor data reduction (weather, pointing, etc). All this information originates in different hardware and software
elements, each of which can be sampled at different rates and with limited view of the behaviour and state of
the observing system.
A summary plot of the main elements involved in data flow is shown in Figure 12.2. As indicated in the
figure, all components passing through the Data Capture module contribute in the generation of the metadata
associated to a dataset, which is in XML format. The bulk of the data (binary) is sent to the Archive andlinked to the metadata using requests to the Archive.

Figure 12.2: Data flow components.

1 There are two types of data that are stored to the archive: meta-data (which is XML/text data stored by Data Capture) andbulk data (which is binary data stored by the correlators). The meta-data stored by Data Capture contains the relevant references
to the bulk data, so that when a user retrieves an ASDM from the archive, the meta-data and corresponding bulk data are retrievedat the same time. For more info on this, please read Chapter 14 of this Handbook.

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The ALMA Science Data Model

The ALMA Science Data Model2 (ASDM; Viallefond, F. 2006, Astronomical Data Analysis Software andSystems XV, 351, 627) defines the collection of information recorded during an observation that is needed forscientific analysis. As described above it contains both bulk binary data and metadata (XML) organized intables. The tables contain links to other XML tables and addresses pointing to the actual bulk data in theArchive. The ASDM contains 16 core tables that are common to all observing modes, and up to 23 additional
tables that are only created for specific observations. On top of these, TelCal also creates associated tables
whenever it processes any of the calibrations that can be done online. All tables are organized with a similar
structure, with the columns listing the contents and the rows including the actual values. The core tables havebeen defined to outline some of the following: hardware characteristics, array configuration, antenna tracking,targets, auxiliary monitoring data, overall project and post-processing. A list of the core tables is shown in
Figure 12.3. The term referenced in the tables means that a given table is linked to other tables via somereferences, that is, some of the information is shared between tables.

Figure 12.3: ASDM Tables. Outlined set of tables are the core ones (i.e., present in all ASDMs).
The associated tables produced by TelCal all have a name starting by “Cal” and then a self-explanatory
string on the type of calibration they are associated with, except for the CalDevice table which is unrelated to
TelCal. The list of these associated tables is being upgraded as new observing modes and calibrations become
available (see Chapter 10). The current list is shown in Figure 12.4. In the figure CalDM stands for Calibration
Data Model, which has been implemented by TelCal.
2 In order to be able to have a general schema for any ALMA project, the information on any Observing Project is stored in
the ALMA Archive following the APDM, the ALMA Project Data Model. The APDM defines a series of generic structures thatare shared by all Observing Projects, including the project status, the proposal information, the outcome of the proposal review
process, and the scheduling blocks with their interdependencies. All these structures are filled with the relevant information (orwith links to it in the Archive) at the time of the creation of the project, and updated accordingly during its complete lifecycle.

12.2. THE ALMA SCIENCE DATA MODEL

167

Figure 12.4: Current list of ASDM associated tables generated by TelCal.
Most users interact with the ASDMs via the Common Astronomy Software Applications (CASA) data
reduction package. At that point, the original ALMA data format has been converted to a format moreconvenient to CASA, the Measurement Set (MS). Information on the MS content is described in the CASA
manuals and description documents available at http://casa.nrao.edu.

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Chapter 13

Pipeline Processing
13.1

Overview

The ALMA Science Pipeline is used for the automated calibration and imaging of ALMA interferometric andsingle-dish data. It consists of modular calibration and imaging tasks within the Common Astronomy Software
Applications (CASA) data reduction package that are selected and put together in a specific order based onstandard prescriptions or “recipes”. The standard ALMA recipes cover the processing of the standard ALMA
observing modes, as defined in Section 5 of the Proposer’s Guide for each ALMA proposal cycle. These recipes
are submitted for execution on the computing systems at the Joint ALMA Observatory (JAO) and ALMA
Regional Centers (ARCs) to produce standard products (calibration and flagging tables and FITS images),
informative logs and scripts, and a “weblog” consisting of a collection of webpages with diagnostic messages,
tables, figures, and “Quality Assurance" (QA) scores. These products are reviewed as part of the ALMA Quality
Assurance process (see Chapter 11 of this handbook), and, if satisfactory, are stored into the ALMA Science
Archive.
The Pipeline is data-driven and includes specialized algorithms or “heuristics” that automatically set task
parameters or trigger different procedures based on the observing mode or quality of the data. Examples ofheuristics are whether to flag certain data, or whether to smooth data before producing a calibration table.
This chapter describes the basic workflow for ALMA Pipeline Processing, and its use in ALMA Science
Operations. Detailed information on the individual Pipeline tasks, heuristics, and QA scores are given in the
Pipeline User’s Guide and Pipeline Reference Manual, which are updated at the start of each public Pipeline
software release (including the start of each ALMA observing cycle), and are available from the ALMA Science
Portal.
The pipeline recipes are deterministic and should always give the same result for the same data. The
documentation referenced above describes how to use the archived pipeline products to reproduce the standard
ALMA calibration and/or imaging products. However, the CASA pipeline tasks are designed to be highly
flexible, so that they can have the default inputs over-ridden with user-specified values, or be added, subtracted,
or rearranged to produce alternative processing recipes. This enables a manual “mix and match” mode for data
reduction and imaging that combines standard CASA pipeline tasks with other CASA commands or python
code to produce scripts that are better tuned to the idiosyncrasies of a specific dataset. Some common “manualmode” modifications are presented in the Pipeline User’s Guide.

13.2

Pipeline In ALMA Operations

13.2.1

Standard and Non-standard Observing Modes

One of the criteria for whether an ALMA Observing Mode is considered standard or non-standard is whether
the ALMA Pipeline has been commissioned for that mode. The standard and non-standard modes for a given

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cycle are listed in the Call for Proposals for that cycle. Data associated with standard observing modes will
be sent to the ALMA Pipeline for processing. Data from non-standard modes may be considered for pipeline
processing (e.g. high frequency data with sufficiently bright calibrators), but as a rule will be sent instead for
manual data reduction.
Since a project may have science goals that include both standard and non-standard observing modes, theirresulting products may be a mix of both pipeline processed and manually processed data.

13.2.2

Pipeline Triggering

As described in Chapter 12 of this document, the structure of an ALMA project is broken down into a hierarchyof Observing Unit Sets (OUSs). There are OUSs at the Science Goal, Group, and Member levels. An OUS
will include one or more datasets, each resulting from a successful execution of a Scheduling Block. These
individual datasets, called Execution Blocks, are in ALMA Science Data Model (ASDM) format, and hence areoften referred to as ASDMs. Each ASDM is assigned a Quality Assurance, level 0 (QA0) score (see Chapter
11 for more details). The QA0 scores are “QA0 Fail” (no useful data), “QA0 SemiPass” (some useful data but
missing critical calibration or science data), or “QA0 Pass”. Only ASDMs with “QA0 Pass” score are used for
subsequent data processing.
The OUS level determines when the Pipeline is triggered and which products are produced. Member OUSs
become eligible for data reduction after they transition into the “Fully Observed” state. Group OUS processing
is triggered when all Member OUSs are completely processed and pass level 2 of Quality Assurance (QA2 - see
Chapter 11). At the current time, the Pipeline is only commissioned for Member OUS processing; Group OUS
combination is left to individual researchers.
The pipeline triggering conditions for projects with different Science Goal OUS structures are depicted in
Figures 13.1 – 13.3. Figure 13.1 shows the conditions for a Science Goal consisting of a single Member OUSs,
resulting in one pipeline processing request and one set of archived science products. Figure 13.2 shows theconditions for a Science Goal consisting of two Member OUS each under their own Group OUS, typical of
multi-epoch observations. In this case, each epoch is processed independently by the pipeline, and separate setsof science products are archived. The final figure, Figure 13.3, depicts a Science Goal that includes two Member
OUSs under a single Group OUS. This structure is typical of multi-array observations, where observations fromdifferent array components (distinct 12-m Array configurations, the 7-m Array, and/or the TP Array) each aregrouped into separate Member OUSs, but gathered under a single Group OUS. In this case, each Member OUS
is independently processed through the pipeline with its products separately archived and delivered. When
all constituent Member OUSs have been successfully processed, the Group OUS becomes complete and readyfor joint processing at the group level. When this level of processing is commissioned within the Pipeline, thecalibration for each Member OUS will be restored and the data processed to produce an additional combined
set of imaging products. This is expected to be available in ALMA Cycle 6 or shortly thereafter.

13.2.3

Pipeline Runs

A pipeline run consists of executing a pre-established sequence of commands known as a recipe. There are
separate recipes for the following pipeline procedures:• Calibration of standard-mode interferometric data.
• Imaging of interferometric data.
• Calibration+imaging of standard mode interferometric data.
• Calibration+imaging of standard-mode single-dish data.
• Calibration+imaging of “simple" ALMA Calibrator Survey data.

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Science Goal OUS

Group OUS•Group Processing Trigger: No Group processing
needed in this case because there is only one Member
OUS.
PROCESS=FALSE

Member OUS•Member Pipeline processing trigger: after the required
theoretical sensitivity has been achieved by repeating theSB, the pipeline processing for the Member OUS is
triggered.
PROCESS=TRUE

Scheduling Block•SB may need to be repeated several
times to build up required sensitivity

ASDM (Execution Block) each time the SB is repeatedFigure 13.1: Pipeline processing of a Science Goal for single epoch, single array data. The same SB may need
repeating N times to build up the requested sensitivity. This Science Goal would result in 1 Pipeline processing,with 1 set of science products delivered to PI.

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Science Goal OUS
Group OUSGroup OUS

•Group Processing
Trigger: No Group
processing needed
PROCESS=FALSE•Group Processing
Trigger: No Group
processing needed
PROCESS=FALSE

Member OUS

Member OUS•Member Pipeline
processing trigger:•Keywords: When theconditions to finish a
Member’s observations
have been met then
PROCESS=TRUE•Member Pipeline
processing trigger:•Keywords: When theconditions to finish a
Member’s observations
have been met then
PROCESS=TRUE

Scheduling Block

Scheduling Block

SB for Epoch 1

SB for Epoch 2

ASDM each time SB isrepeated

ASDM each time SB isrepeated

ASDM contains data from
Epoch 1

ASDM contains data from
Epoch 2

Figure 13.2: Pipeline processing of a Science Goal containing multi-epoch observations. Each epoch is processedindependently by the Pipeline, with science products created for each epoch. Data from different epochs are
not processed together to form a combined product (the Member OUS from each epoch are in different Group
OUS). This Science Goal would result in two Pipeline processing runs, with two sets of science products archived
and delivered.

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13.2. PIPELINE IN ALMA OPERATIONS

Science Goal OUS
Group OUS
•Group Processing Trigger: Group processing needed inthis case (combined reduction of Member OUSs). Group
processing is triggered after processing both Member
OUSs separately is completed.
PROCESS=TRUE

Member OUS

Member OUS•Member Pipeline
processing trigger:•Keywords: When theconditions to finish a
Member’s observations
have been met then
PROCESS=TRUE•Member Pipeline
processing trigger:•Keywords: When theconditions to finish a
Member’s observations
have been met then
PROCESS=TRUE

Scheduling Block

Scheduling Block

SB for configuration A

SB for configuration B

ASDM each time the SB is run

ASDM each time the SB is run

ASDM contains data from
Config A

ASDM contains data from
Config B

Figure 13.3: Pipeline processing of a Science Goal containing multiple ALMA 12-m Array configurations orcontaining data from different arrays (e.g. 12-m Array, 7-m Array or TP Array). The data from the different
configurations/arrays are grouped into separate Member OUSs, each of which is processed independently, resulting in separate science products for each MOUS being archived and delivered. Once the processing of theMOUSs is complete, they are eligible for Group OUS processing, although this is not yet commissioned in thepipeline.

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In the future, these recipes will be expanded as non-standard observing modes (e.g. polarization; solar
observing) are commissioned in the pipeline and become standard.
At the end of each pipeline run, the results are reviewed and the success or failure of the pipeline results
assessed. If the pipeline run was successful, the data move on to the next stage of processing using the appropriate
recipe (e.g., from interferometric calibration onto interferometric imaging). If the pipeline run was not successful,it may be repeated after some manually introduced mitigations are applied (e.g., editing a template flagging filethat the pipeline will automatically apply when the pipeline run is re-executed), or sent to manual processing(calibration and/or imaging) for treatment that is not available within the pipeline (e.g. self-calibration; using
the phase calibrator to calculate a failed bandpass solution). As a result, the final delivered products may too
be a mix of pipeline and manual efforts (e.g. pipeline calibrated but manually imaged or vice versa). Since
single-dish data only has a single calibration+imaging recipe, single-dish products will never be a mix of pipeline
and manual reductions.

13.3

Details on Pipeline Processing

As mentioned above, detailed information on the individual Pipeline tasks, heuristics, and QA scores are givenin the Pipeline User’s Guide and Pipeline Reference Manual, which are updated at the start of each public
Pipeline software release (including the start of each ALMA observing cycle), and are available from the ALMA
Science Portal. This subsection briefly describes a few aspects of pipeline operations that proposers may wish
to be aware of.

13.3.1

Pipeline Runtime Database Queries

The ALMA Pipeline queries various ALMA databases for measurements that may have been updated since thedata were initially obtained (such as calibrator fluxes from the ALMA Source Catalog; antenna positions fromthe Telescope Monitor and Control Database), or that must be provided outside the pipeline (Kelvin-to-Jansky
conversion factors for single-dish observations).
At the current time, not all of these databases are available or fully enabled in the pipeline, and the updates
may instead be done with observatory scripts that are not part of the official pipeline tasks, but are integrated
with the pipeline recipes. The product of these scripts are text files that contain the updated information
which are applied to the data during pipeline execution. These text files are included with the archived pipeline
products.

13.3.2

Observatory “Fixes”

In previous cycles, issues with the data, metadata, or observing scripts were discovered after the start of theobserving cycle that required special workarounds to modify the data and/or to include special calibrations
not included in the current pipeline tasks. The modular design of the pipeline tasks allows these fixes tobe incorporated into the pipeline processing by modifying the pipeline execution script to insert additional
processing commands between the standard pipeline tasks, most commonly after the initial import of the raw
ASDMs (similar to how the unavailable database queries described in the previous subsection are enabled).
These “fixes” will be included in the processing files archived and delivered with the pipeline products so thatthey are properly applied when the data is reprocessed by user’s.

13.3.3

Flagging Heuristics

The pipeline has a number of flagging heuristics, which are described in the pipeline documentation. However,these heuristics are only run on calibrators. The heuristics will extend the scope of the flags to flag all data orcalibration tables associated with bad antennas or baselines, which will propagate to science targets. However,13.3. DETAILS ON PIPELINE PROCESSING

175

this will not catch bad data that is only associated with science targets. As such, investigators should carefully
review the calibrated data for their science targets for any such data.

13.3.4Treatment of Multiple Execution Observations

During data calibration, each ASDM is calibrated independently. In the calibration processing, the Pipeline
runs sequentially through each pipeline task, applying that task to each ASDM. For example, the Pipeline firstimports the data from each ASDM; it then performs deterministic flagging on each ASDM; it then moves onto
the next task etc. This proceeds until all the flagging and calibration steps have been performed for each ASDM.
As a consequence, the calibration and flagging tables are stored separately for each ASDM.
In the weblog, ASDMs that were obtained within the same observing “session” (continuous science observing
period without a software restart) are grouped together. In the future, some calibrations may be “sessionized”,
meaning that calibrations obtained in one ASDM can be applied to other ASDMs in the same session, but thisis not yet developed within the pipeline.
Imaging (of calibrators and science targets) is not done on a per-ASDM basis, but by including all ASDMs
within the OUS.

13.3.5Low SNR Heuristics in Interferometric Pipeline Processing

The interferometric pipeline has the following heuristics that are triggered if the signal-to-nose ratio (SNR) on
a calibrator is too low.
• Using the Gain Solutions Obtained from the Aggregate of all Spectral Windows.
If the SNR on the phase calibrator is too low, then the aggregate gain solution obtained by using all spectral
windows is used to determine the time variable gain solutions. The bandpass calibrator observations areused to determine the phase offsets between the gain solutions for individual spectral windows and theaggregate solution.
• Additional Bandpass Pre-averaging.
If the SNR on the bandpass calibrator is too low when calculating the prior gain calibration on a perintegration basis, then the time solution interval for this calculation is increased. If the SNR is too low
when calculating the bandpass solution at high spectral resolution, then the frequency solution interval
for this calculation is increased.

13.3.6

Total Power Pipeline Processing

There is a maximum of one single dish (Total Power) Science Scheduling Block per Member OUS. The Science
SB will have one or multiple science targets, each with a corresponding rectangular observing field. It is advisable
to make the mapped area large enough that there are emission-free regions around the edges of each field.
The single-dish pipeline recipe performs Tsys and blank-sky calibration, Kelvin-to-Jansky conversion (perantenna, per spectral window), spectral baseline subtraction, subsequent flagging, and imaging to process data
for science targets. The Kelvin-to-Jansky conversion is not calculated by the single dish pipeline but instead
extracted from an observatory database. This database is compiled from observations of standard amplitude
calibrators (planets and bright quasars) using the 12 m antennas in the TP Array to derive the trends of the Gain
(Jy/K) conversion factor for each of the antennas as a function of frequency, ambient temperature, elevation,and day-night dependence. As a consequence, the amplitude calibration observations are not included in thedata products. Instead, a list of the applied Kelvin-to-Jansky factors is added to the data products.
During the imaging stages, the single-dish pipeline subtracts a low-order spectral baseline from each spectrum, using an automated line-identification algorithm to determine the channel ranges to be masked. Readers
should refer to the Pipeline User’s Guide for a detailed description of the line identification algorithm. This

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algorithm has been optimized to detect emission lines with a moderate width (wider than 100 channels) awayfrom the edges of the spectral window. As a consequence, users should set up their spectral windows so that they
are centered on the expected line frequencies and have sufficient bandwidth to provide an adequate number ofline-free channels on either end. If the baselines are not flat due to inadequate line-identification and subsequent
spectral baseline subtraction, the project will be sent to manual reduction.

13.3.7

Imaging – interferometric

The interferometric imaging pipeline is still relatively new. As such, the default pipeline products are expected
to be reliably calibrated, but in many cases the images could be improved, in some cases significantly. For
example, the continuum identification algorithm uses statistical measurements of the dirty cubes to identify
frequency ranges that should be free from line emission. Its internal heuristics have been tuned to give reliable
results over a wide parameter space; however they will not be optimized for every spectral window or sciencetarget, and investigators should anticipate that a more careful per-target, per-spw evaluation could improvetheir results. Additionally, the Cycle 5 pipeline will for the first time use an auto-masking algorithm in theimaging deconvolution (clean) step that is similarly tuned to work under a wide range of parameter space;more carefully defined masks and interactively defined cleaning thresholds may produce better results. Finally,
the pipeline does not include science target self-calibration. Therefore, the pipeline imaging products of brightsources will be dynamic range limited.
The imaging pipeline is computationally demanding, and long imaging runs could impact the delivery ofdata to other investigators. As a result, there are automatic heuristics in the interferometric pipeline tasks that
limit the generation of full-channel, full-source, full-field-of-view images if the estimated time to produce thefull products is more than a few days. The pipeline imaging scripts can be modified after-the-fact to produce
the missing imaging products. Investigators may wish to consider visiting their supporting ARCs if their homecomputing resources are inadequate. These requests should be submitted to the ALMA helpdesk.

13.4

Pipeline and the ALMA Quality Assurance Process

For each pipeline processing step, the Pipeline calculates Quality Assurance (QA) measures that are reported
within the “Pipeline QA” section of the task weblog page, and a single QA score is reported for the entire
processing step. These QA scores and any associated messages are primarily an indication of how successfulthat step was. They do not, by themselves, indicate whether the final products are deliverable.
That assessment (level 2 of the ALMA Quality Assurance process, QA2 – see Chapter 11) is made separately
on the products from the pipeline using the ALMA Quality Assurance tool (AQUA), taking into account therequirements specified by the Primary Investigator when the proposal was submitted. Only data that pass (orsemipass) QA2 will be ingested into the archive and delivered. The pipeline QA scores for each task are passed
to the AQUA subsystem to aid in this assessment, as is the pipeline weblog, but the pipeline scores themselves
do not determine the QA2 status of the OUS.
The main point of the pipeline QA scores and associated messages or warnings is to indicate whether any steps
should be looked into more carefully, to possibly improve the processing and final products. It is important
to note that data may pass QA2, but still benefit from a more careful manual review (e.g. data flagging,
continuum identification, clean masking). The pipeline QA scores and weblog are tools to help researchers
make this assessment. See the Pipeline User’s Guide for more details.

13.5

Output of the Pipeline Processing

The main output from the pipeline are final images and cubes in FITS format, a weblog with informative plots
and information on each pipeline task, and calibration and flagging tables and processing scripts that will either
convert raw data into calibrated measurement sets, or run the pipeline tasks on the raw data to reproduce the13.5. OUTPUT OF THE PIPELINE PROCESSING

177

pipeline products. There are also text files that can be edited to modify the pipeline run (e.g., by changing theflux scale or the continuum frequency ranges used for continuum subtraction - see the ALMA Pipeline User’s
Guide for details).
Regardless of how your data have been processed (manually or through the pipeline), there will be two typesof archive products: the processed products (FITS images, scripts etc.), and the original raw visibility data. You
can inspect/manipulate the processed FITS images in any package you like (although CASA is recommended).
However, if you want to re-make images or combine data e.g. as in Figure 13.3, you will also need to download
the raw visibility data and re-run the calibration scripts in CASA. Once you have regenerated the calibrated
visibility data you can re-image (e.g. at a different spectral resolution) using the provided imaging script asa template. If you want to self-calibrate there are CASA Guides to help, or you can consult your local ARC
through the helpdesk.

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Chapter 14

Data Archiving
14.1

Introduction

The ALMA Archive is at the center of the ALMA data flow (Fig. 14.1). It is a combined database and binary
data storage system that is accessed by the different software subsystems through the same software layer.
The ALMA Archive stores all metadata and data of ALMA from the user accounts, over the proposals, theobservatory and antenna configuration and monitoring to the raw and reduced science data. The science data
and metadata are made available to PIs and archival researchers for querying and download following ALMA’s
data access policy.
The ALMA Archive is divided into two parts. The ALMA Frontend Archive (AFA) and the ALMA Science
Archive (ASA). The AFA provides the core persistence functionality. The ASA holds a small subset of metadataof the AFA in a relational database and provides access to external interfaces like the Archive Query interface
and in the future Virtual Observatory (VO) tools. The storage architecture is based on the Next Generation
Archive System (NGAS) with Oracle technology for replicating the metadata.
Each of the three ALMA Regional Centers (ARCs) in North America, Europe and East Asia holds a copyof the entire ALMA Archive for backup, user support and data distribution to the ALMA PIs and archival
researchers. The ARCs provide a completely identical user experience to their communities and a user can
download data from any ARC.
An ALMA Science Archive Manual is available from the ALMA Science Portal(https://almascience.eso.org/documents-and-tools/cycle5/science-archive-manual).

14.2

Data Flow and Archive

Data from the correlator, together with monitor and weather data, are sent via dedicated optical fiber links(1-10 Gbit/s) to the OSF, where they are archived. A peak data rate of 66.6 MB/s can be sustained for shortperiods of time, i.e. days. This peak rate is a technical limitation of the data capture and data flow systems
and will be imposed by the Observing Tool at the proposal validation stage.
The Pipeline processing system and Archive storage system have been designed to cope with an averagedata rate of 10% of the peak rate, i.e. 6.6 MB/s leading to a yearly amount of 200 TB of data. The volume ofdata products from the pipeline are expected to approximately equal the raw data volume, resulting in about
400 TB/yr being ingested into the ALMA archive.
The ALMA Archive at the OSF is designed to provide up to a year of temporary storage for the instrumental
data (in the form of files in the “ALMA Science Data Model”, or ASDM, format) and the monitoring data. The
instrumental data are then transferred to the main archive at the SCO, where the pipeline is run and from

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where the data and pipeline products are distributed to the three ARCs. The process of copying the data to
any of the archives involves a replication of the metadata (support data) and of the bulk data (ASDM and FITS
files). All data transfer is done over the network. Metadata replication from SCO to the ARCs happens withina few seconds, transfer of bulk data can take longer (up to several hours), depending on the amount of data totransfer to the individual ARC.
PIs of large programs are expected to return processed data products to the project. These data will betransferred to JAO from where they will be ingested into the ASA.

Figure 14.1: The ALMA Archive is in the center of the ALMA data flow.
As soon as data is taken and has passed (or semipassed) the QA0 quality control step (see Chapter 11.2),
its metadata are harvested from the AFA into the ASA and made available for search. This allows archival
researchers to see which data will become public in the future. Metadata harvested include all the informationneeded to describe the observations, including date and time, source coordinates, frequency settings for each
spectral window, and spectral and spatial resolution.
Once the pipeline processed an ObsUnitSet (hereafter OUS, see 8 for details on the OUS structure) and thescience products have passed QA2 they are ingested into the ASA.

14.3

PI Data and Data Delegation

The unit of data delivery to the PI is the OUS. As soon as QA2 on an OUS has passed and the data products
have been replicated to the user’s home ARC, PIs will receive an email notification containing a link to theirdata, and supporting information. This sending of the notification to the PI triggers the start of the proprietary
period of 12 months for standard proposals and 6 months for Director’s Discretionary Time (DDT) proposals.
Extensions of the proprietary period can be granted under certain circumstances. When a Group OUS consistingof several Member OUSs is processed (for example, a combined TP, 7-m and 12-m Array observation), the GroupOUS products are released separately, with their own 12-month proprietary period.
The data deliveries consist of one or more bundles of raw (ASDM-format) data, and one "products" bundle

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14.4. ARCHIVE QUERY

tar file which includes the FITS files, logs, scripts, QA information and calibration tables.
Often PIs want to make their proprietary data available to collaborators, e.g. CoIs. To this end a datadelegation service is available so that PIs do not have to give away their Science Portal password to anyone.
Instead, PIs can give access rights to the data of a project to any registered ALMA user. To do so, PIs need tolog into the Science Portal, go to their user profile page in the top right corner of the Science Portal page andthen add delegates in the "Project delegation" tab.

14.4

Archive QueryAt http://almascience.org/alma-data/archive users can query the holdings of the ALMA Science Archive (Figure14.2). They then can download the data corresponding to their queries, if those data are public or if the users
are authenticated and have the proper access rights to those data.

Figure 14.2: The ALMA Science Archive Query Form
Queries can be made by physical quantities along the Position, Energy, Time and Polarization axes. Helpon how to query is provided in the tooltips of the query fields as well as through the “Query Help” link. Query
constraints using standard operators for strings (*, ?) and numbers (>, <, .. ) can be placed into the form
fields. There is also a name resolver available for non-solar system objects (Sesame), which queries the Simbad,
NED and Vizier databases. No operators can be used in the name resolver field.
By default, the Archive Query Interface will present users with the metadata of the observations, although
they can choose to also see the metadata per project or per publication. On the results page, users can sort andsubfilter the results and add or remove columns from the result table to narrow their search. The sky coverageof the observations is visible in a graphical window.
The results page also offers to download the results in VOTable, TSV (Tab-separated values) or CSV(Comma-separated values) format for further processing in tools like topcat1 . The URL used for the exporting
1 http://www.star.bris.ac.uk/~mbt/topcat/

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Figure 14.3: The ALMA Science Archive Results Pageof the query results can also be modified to access the ALMA Archive queries programmatically. Astroquery2
can be used to encapsulate and simplify programmatic access to the ASA. Neither Topcat nor Astroquery arepart of the offical ALMA software, and support of users of these tools will be limited to best efforts.

14.5

Request Handler

Once data of interest are defined, they can be selected via checkboxes on the results page and submitted to the
ALMA Request Handler for download. The data are displayed in the full OUS hierarchy. This allows users tocheck immediately if there are data from other Member OUS or higher-level Group OUS products available.
By default, only data products (i.e. FITS-format, and ancillary processing documentation) will be selected for
download. Users who want to download the raw data as well are asked to select “include raw” before hitting
the Download button or to select the desired data manually. The sources row can be expanded to show all thesource names that are part of the package. Furthermore, a readme file is provided summarising the structureof the data and providing the full links to the OUS.
Four possibilities exist for the download itself:• The first option is to use the download script. This script runs under Linux and MacOS and downloads
files in parallel streams and is also adapted for downloads to a processing environment where no web
browser is available.
• The second option is to use the download manager applet with the FireFox browser. This method is very
convenient and allows for parallel downloads, too. It requires a Java Browser Plugin.
• It is also possible to use the download manager through Java Webstart technology.
2 https://astroquery.readthedocs.org/en/latest/alma/alma.html

14.5. REQUEST HANDLER

183• Finally, a page with the links to all selected files can be displayed which then can be conveniently downloaded, e.g. using a browser plugin like "DownThemAll".
The Request Handler also allows selecting individual files for download. Only the data deliveries that users havepermission to download can be selected. If they are not authorised to access any data delivery in the request,no "Download selected" button appears.
If the user is authenticated before requesting data for download, the request will be stored. This allows
users to go back to previous requests. Note that these requests are stored only at the ARC the user is currently
accessing. If data should be downloaded from a different ARC, then a new request has to be issued. For verylarge data requests PIs or archival researchers have the possibility to ask via the ALMA Helpdesk for datadelivery on hard media, i.e. USB hard-disks. The ARCs may have different policies regarding the details of theshipping of the hard-disks.

184

CHAPTER 14. DATA ARCHIVINGAppendix A

Antennas
A.1

Design and Properties

ALMA is composed of a total of 66 antennas, 54 with a diameter of 12 m and 12 with a diameter of 7 m.
The four 12 m antennas used for total power observations and the twelve 7 m antennas together form the
Atacama Compact Array (ACA). The ALMA antennas are manufactured by three different contractors. These
are VertexRSI (North America) which provided 25 12 m antennas, Alcatel Alenia Space European Industrial
Engineering MT Aerospace (AEM, Europe), which also provided 25 12 m antennas and Mitsubishi Electric
Corporation (MELCO; East Asia), which provided the four 12 m total power antennas and the twelve 7 mantennas (Figure A.1).
All antennas have been designed to meet very stringent ALMA performance criteria, and to successfully
operate under the extreme environmental conditions at the Array Operation Site (AOS), i.e. strong winds,
large temperature ranges and gradients, solar irradiation and snow. The primary operating conditions are thefollowing:• Range of Ambient Temperatures: -20 ◦ C ≤ Tamb ≤ +20 C• Gradient of temperature: Delta(Tamb ) ≤ 0.6/1.8 ◦ C in 10/30 minutes• Wind Velocities ≤ 6/9 m/s (day/night)• Full solar loading
The antennas have the following specifications within the Primary Operating Conditions:
Antenna Surface: RMS deviation of 25 (20) microns or less for 12 m antennas (7 m antennas) relative to an
ideal parabola.
Pointing: Absolute pointing ≤2.0 arcsec all-sky. Offset pointing ≤0.6 arcsec within a 2 degree radius on thesky.
Primary Beam: The total power pattern response of each ALMA antenna shall be determined to a measurable
and repeatable precision better than 1% at frequencies <400 GHz and 2% at frequencies >400 GHz.
Subreflector: 6 degrees of freedom to allow for alignment with the corresponding receiver beam.
Subreflector Motion: Maximum horizontal (X) and vertical (Y) displacements of ±5 mm. Maximum focal
displacement (Z) of ±10 mm. The maximum rotation around the axes is 1.2 degrees. Positioning mustbe accurate to 5 microns.

185

186

APPENDIX A. ANTENNAS

Antenna Location: The phase center position of the ALMA antenna shall be determined to a radial precisionof 65 microns (including the antenna structure and pad), stable over two weeks.
Configuration: The ALMA antennas shall be relocatable.
Lifetime: a minimum of 30 years.
Antennas used during ALMA Cycle 5 have both 12 meter and 7 meter diameters, with the receivers mounted
at the secondary (Cassegrain) focus. The 12 m dishes have a focal length of 4.8 meters, but the distance from thesecondary focus to the plane of the subreflector of the 12 m antennas is 6000 mm, giving an effective focal ratio
f/8, with an effective secondary focal length of 96 m and a plate scale of 2.15 arcsec per mm. The subreflector
has a diameter of 750 mm. The 7 m dishes have a focal length, to the primary focus, of 2.572 meters. Given an
effective focal ratio f/8, an effective secondary focal length is 56 m. The subreflector has a diameter of 457 mm.
The main reflectors of the ALMA 12 m and 7 m antennas are composed of individual panels. The size andnumber of panels varies between the different types of antennas:
VertexRSI: 264 panels spanning 8 rings with 12 (rings 1 and 2), 24 (rings 3 and 4), and 48 (rings 5 through8) individual panels which are roughly a half-meter-square in area.
AEM: 120 panels spanning 5 rings with 8 (ring 1), 16 (ring 2), and 32 (rings 3 through 5) individual panels
which are roughly one-meter-square in area.
Melco 12 m: 205 panels spanning 7 rings with 5 (ring 1), 20 (rings 2 and 3), and 40 (rings 4 through 7)
individual panels which are roughly one-meter-square in area.
Melco 7 m: 88 panels spanning 5 rings with 4 (ring 1), 12 (ring 2), and 24 (rings 3 through 5) panels which
are each roughly one-meter-square in area.

Figure A.1: The four different ALMA Antenna designs: Vertex 12 m, MELCO 12 m, AEM 12 m, and MELCO
7 m (from left to right).
Each panel has up to 5 adjustment screws, which can be used to optimize the surface accuracy of theindividual antennas (based on holographic measurements). The surface of the panels are etched to scatter
optical and near infrared solar radiation.
The antennas are equipped with a movable aluminium subreflector. Subreflector adjustment is used tomaximize the transfer of power into the receivers by compensating for changes in the focus position due togravitational- and temperature-induced deformations. The backplane of the subreflector is attached to a hexapod that controls its position and orientation. The hexapod has six degrees of freedom, displacement and tilt
around the three axes, horizontal (X), vertical (Y) and along the optical axis (Z).

187

A.2. ANTENNA FOUNDATIONS

Vertex
Melco 12 m
Melco 7 m
AEM

BUS

Number PanelRings/ MatePanels rial

Quad
type1

Cabin

Drive
System2

Metrology System3

CFRP
Al
Invar
CFRP
Steel

8/264

Al

+

Steel

Gear

7/205
5/88

Al
Al

+
+

Steel
Steel

DirectDirect5/120

Nickel x
Rhodium

CFRP

Direct4 linear displacement sensors + 1
two-axis tiltmeter (above the azimuth bearing)
Reference Frame metrology
Thermal (main dish), Reference
Frame metrology
86 thermal sensors + 2 tiltmeters inyoke arms

CFRP
Invar

Table A.1: Design Properties of the Different ALMA Antennas.
Notes: 1 Shape of the quadrupod supporting the subreflector as seen looking along the optical axis of theantennas when they are pointed to the viewer. 2 A gear drive consists of a main motor driving a series ofconnected reduction gears (i.e., gearbox) that do the actual precision work. A direct drive system does not
require such gears and takes the power directly. The direct drives used in ALMA antennas are magneticallysupported. 3 Jointly used to correct in semi-real time the pointing of the antennas, under a wide range ofenvironmental conditions, to meet the ALMA specifications.
All antennas have a Cassegrain cabin that is kept at a constant temperature of 20 degrees Centigrade andcontains the receivers, the amplitude calibration device and associated electronics.
A shutter protects the inside of the Cassegrain cabin when the antenna is not operating. A membranetransparent to the frequencies that can be observed with ALMA is located below the shutter to prevent airflow
from the cabin to the outside when the shutter is open. The current design uses a 0.5 mm thick Goretex
membrane.
The different antennas use a combination of steel, aluminium, Carbon Fiber Reinforced Polymer (CFRP)
and Invar to achieve the best compromise between stiffness, robustness, smoothness, and low thermal expansion(see Table A.1 for a summary of properties). Common to all antennas is that they have a steel pedestal.
All antennas have built in metrology systems which allow thermal and wind deformations to be computedand corrected. For these purposes, the antennas are fitted with thermal sensors, linear sensors and inclinometers(tiltmeters).
The Vertex antennas have a drive system that is gear-driven whereas the AEM and MELCO antennas havemagnetically supported direct drives.
The antennas are controlled using the ALMA Control Software (ACS). ACS sends instructions to the Antenna
Bus Master (ABM) computer, which are then sent to the Antenna Control Unit (ACU) through a CAN bus.

A.2

Antenna Foundations

The antennas are placed on specially-designed concrete pads to guarantee stable orientation and location (FigureA.2). All antennas are attached to the pads at three points at the vertices of a triangle. The three points (inserts)
are located on a circle centered at the antenna pad with a spacing of 120 degrees.
This interface guarantees a position repeatability error of the antenna, considered as a rigid body, notexceeding the values below:• X/Y plane < 2 mm (peak to peak)• Rotation around Z < 30 arcsec (peak to peak)• Parallelism with respect to Z +/- 10 arcsec with respect to Zenith

188

APPENDIX A. ANTENNAS

Figure A.2: Structure of an antenna pad (actual pad at the OSF) (left) and detail of antenna anchored to apad (right).

The minimum stiffness which the foundation must exhibit at each insert is:• Vertical stiffness (Z) > 13 x 109 N/m• In X/Y plane > 9 x 109 N/m
Stiffness includes the inserts, the concrete pad and the soil. This does not include the kinematic mountlower part nor the foot of the antenna. The position of the pads are measured to a precision of 65 microns,
and then monitored for stability for over two weeks. The pads are equipped with two vaults that contain the
power, communication, Local Oscillator (LO) and data transmission cables that are connected once the antennais placed on the pad.

Figure A.3: The ALMA array with eight 12 m antennas (left), and an antenna being transported to the AOS(right).

A.3. ANTENNA TRANSPORTATION

A.3

189

Antenna Transportation

Antennas are moved from one pad to another using a specially-designed transporter (Figure A.3, righthandpanel). ALMA has two of these vehicles. They are 20 meters long, 10 meters wide and 6 meters high, and eachhas 28 tires. The transporter positioning system performs a fine positioning of the antenna before setting it
down on the foundation in the 3 in-plane degrees of freedom (x, y, rot -z) and 2 in-tilt (rot-x, rot-y). Adjustment
in each of the 5 adjustment axes can be done independently. The adjustment range of the antenna positioning
system compensates for the inaccuracy of the vehicle position with respect to the antenna foundation (whichmust be smaller than 10 cm) to achieve the required antenna positioning accuracy. The antennas can bepositioned to within a few millimeters, ensuring accurate placement on the antenna foundation pads. Moreinformation on the transporters can be found on the ALMA EPO pages1 .

Figure A.4: Side view of ALMA front end showing cryostat assembly, with room temperature unit below.

A.4

Cryostat

The ALMA front end consists of a large closed-cycle 4 K cryostat containing individual cold cartridge assemblies(CCA) with mixers and LO injection for each band, along with room temperature electronics for the IF and
LO for each band (the warm cartridge assembly, WCA) and fore-optics and entrance windows for each band.
1 http://www.almaobservatory.org/en/technology/transporters

190

APPENDIX A. ANTENNAS

The water vapor radiometer (WVR) is mounted to one side of the cryostat using a pickoff mirror to direct theantenna beam into the WVR. The Amplitude Calibration Device (ACD) is mounted above the front end, andis described in Section A.5. Figures A.4 and A.5 show overviews of the front-end unit, with the cylindricalcryostat on top and the room temperature electronics beneath.
All of the receiver cartridges are in the same cryostat, with the mixers thermally-coupled to the same 3stage Sumitomo cryocooler (Figure A.6). The three stages have nominal temperatures of 4 K, 15 K and 110
K. To avoid overloading the cooler, only three bands can be switched on at a time. It takes about 1 minute toswitch between any of the bands that are switched on at a given time. For bands that are off, the time to fully
thermally-stabilize them from an off state is 15 minutes – this is mainly to ensure a flat bandpass shape. All of
the receivers are mounted off-axis to avoid extra rotating band-selection mirrors, which necessitates a pointing
offset of the antenna to change band. The band pointing offsets are known and well-measured; the reference
band for pointing is Band 6, and all offsets are with respect to this band. The four higher-frequency bands(Bands 7-10) are mounted close to the central boresight to minimize aberrations.

Figure A.5: Bottom view of ALMA front end, showing WCAs.

A.4. CRYOSTAT

191

Figure A.6: Views of cryostat assembly, showing different windows (top) and the portholes for the WCAs foreach band (lower view).

192

A.5

APPENDIX A. ANTENNAS

Amplitude Calibration Device

The ALMA specification for relative amplitude calibration repeatability2 has been set to be better than 1% forfrequencies below 300 GHz and better than 3% for all other frequencies covered by the ALMA Front End. To
achieve this goal, ALMA has adopted a two-load amplitude calibration approach.
The Amplitude Calibration Device (ACD) is located above the cryostat. It consists of a robotic arm attachedto the top plate of the front end (Figure A.7). The arm holds two calibration loads, one at ambient (i.e., receivercabin) temperature and the other one maintained at 80 ◦ C (353 K). In addition, this arm also holds a solar
filter to attenuate solar radiation during observations of the Sun. The arm is designed to allow the two loads
to be placed in the path of any of the receiver beams (Figure A.8). Typically it takes 2 seconds to move thearm from the park position to the position where one of the loads is in the beam, and also 2 seconds to change
between loads.

Figure A.7: Lateral view of the ACD on top of the ALMA front ends.
To accurately calibrate radio astronomical data to a temperature scale, the actual brightness of the twoloads has to be precisely known. Critical to this calibration precision is the coupling of the load to the beamof a given band. This coupling must be very good at any telescope elevation and free of reflections of the load
emission. This is because any reflection from the loads back into the cryostat would be terminated at a different
temperature and would cause standing waves. Both loads have thus been designed so that the actual effective
brightness temperature and that computed from the measured physical temperature (with sensors embeddedin the loads) using known emissivities differ by, at most, ±0.3 K and ±1.0 K for the “ambient” and “hot” loads,
respectively. This requirement also sets a limit to the fluctuations and departure from the set temperature thatare allowed for the “hot” load. Furthermore, the return loss specifications for these loads are -60 dB and -56
dB, respectively.
2 “Calibration Repeatability” means being able to make repeated measurements of the same flux densities (or brightness temperatures) for the same source under different conditions (weather, telescope elevations, front-end status, etc.).

193

A.5. AMPLITUDE CALIBRATION DEVICE

Figure A.8: Top view of an ALMA front end showing the robotic arm of the ACD retracted during normal
observations or on top of one of the front-end inserts for calibration. The current design has been improved byplacing all the loads in a wheel.

A.5.1

Atmospheric Calibration Procedure

The ACD is used to measure the receiver temperature and the sky emission by comparing the signals on the sky,
ambient and hot loads. This is known as atmospheric calibration (ATM calibration), and is required to correct fordifferences in the atmospheric transmission between the science and the celestial amplitude calibrators. Normally
ATM calibration is done during observations, both near the science target, as well as near the amplitude
calibrator.
Traditionally, most mm and submm observatories have used the single-load calibration method, but several
simulations have shown single-load calibration is not capable of reaching the relative amplitude calibration
accuracies required by ALMA at all of its observing frequencies. However, that method has the very desirable
feature that it is only weakly dependent on the opacity of the sky at the time of the observations. A method,using the two calibration loads within the ACD, has been devised in the past to try to achieve the same weak
dependence on the opacities at the time of the observation. This method (“the α method”) uses the voltage
outputs from the observations of both loads to simulate a single load with a brightness temperature close tothat of the atmosphere at the observing frequency. This fictitious single load is defined as a weighted sum of thevoltages of the “hot” and “ambient” loads so that the temperature calibration factors are almost independent of
the optical depth. The fictitious load voltage output, VL , is defined as:
VL = αVL1 + (1 − α)VL2(A.1)

where α is the weighting factor, and VL1 , VL2 the output voltages when the two loads are measured. From thisdefinition and some algebra, one can find the optimum weighting factor needed to minimize opacity dependency,
and the corresponding resulting calibration factors are:

α

=

TCal

=

ηJM + (1 − η)JSP − JL2
JL1 − JL2
(JMs − JBGs ) + gη eτs −τi (JMi − JBGi )

(A.2)
(A.3)

where η is the forward efficiency of the antenna, g the sideband ratio, τ the opacity, and JM , JSP , JL1 , JL2
and JBG are the emissivity temperatures of the average sky, the spill-over, the two loads and the backgroundradiation, respectively. The subscripts s and i represent the signal and image bands, respectively. The systemtemperature is then derived using the formula:
TSys = TCalVSky
VL − VSky

(A.4)

194

APPENDIX A. ANTENNASFor ALMA it has been found that with the current system, the non-linearities are the dominant source oferror for this calibration. The system electronics and SIS mixers are not fully linear and dominate the relative
amplitude calibration accuracy that can be achieved for Cycle 5.

A.6

Water Vapor Radiometers

In the mm and submm regions, variations in the water vapor distribution in the troposphere that move across aninterferometer cause phase fluctuations that degrade the measurements. ALMA uses the so-called “Water Vapor
Radiometry” technique to correct for these phase fluctuations. Water Vapor Radiometry involves estimating
the excess propagation path amount due to water vapor along a given line-of-sight by measuring the brightness
temperature of the sky at frequencies near the atmospheric water vapor resonances. These temperatures canthen be transformed into a path length and the difference between any pair of antennas in the array gives the
final phase fluctuations to be corrected for a given baseline. ALMA has implemented this technique by placing
a Water Vapor Radiometer (WVR) on each 12 m antenna (the 7 m antennas do not have WVRs). For the
WVRs to be effective, the measurements have to be taken with a cadence that is fast enough to map the actual
variations in the atmosphere. The relevant shortest timescale is the antenna diameter divided by the wind speed
as the path delay is averaged over the whole antenna beam and cannot therefore be corrected at any finer time
resolution than that. The effective diameter is about 10 m for the ALMA antennas and the relevant windspeed
is usually 10 m/s or a bit less so the fastest necessary sampling speed is 1 Hz. On timescales shorter than this
1 Hz timescale, the water vapor path fluctuations are expected to lead to small apparent pointing fluctuations
which are analogous to the seeing effects in single-aperture optical telescopes. ALMA selected the 183 GHz line
because it is quite bright and allows a more compact design than would the 22 GHz water line. It was decided
to measure the temperature of the 183 GHz line in four regions offset from the center using filters of different
bandwidths. The positions of the filters are indicated as blue boxes superimposed on the profile of the water
vapor line in Figure A.9. The sensitivity specification for the WVRs is 0.08–0.1 K per channel RMS.

Figure A.9: WVR filters superimposed onto the 183 GHz water vapor emission line.
It is very important that the WVR illuminates the same area of the sky as the ALMA band receivers in
the near-field region. This is because the origin of the water vapor fluctuations is usually located in the lower
troposphere (i.e., near the observatory), with one to several layers of water vapor clumps encompassing a wide
range of sizes. Since the ALMA backends are located at the Cassegrain focus, an offsetting optical system (seeFigure A.10) had to be designed to allow the WVR to measure along the optical axis of the antennas.
The WVRs are only able to detect the variations in atmospheric brightness temperatures due to the “wet”

195

A.6. WATER VAPOR RADIOMETERS

Figure A.10: Offset optics used to collect the sky emission along the optical axis of the antenna into the WVR.
atmosphere (i.e., the precipitable water vapor). There are also variations due to the changes in bulk ambient
temperature at different heights above the observatory. It is expected that these could become significant during
day time and some techniques are being currently studied to try to measure them (including thermal soundersof the atmosphere that use the profiles of the emission of the oxygen molecules). The brightness temperature
variations of the sky that the WVRs have to detect are sometimes quite small, so the quality of the receiving
system becomes very important. In fact, the current specification for the ALMA WVRs is that they need toallow corrections of the path fluctuations (in µm):

δLcorr ≤ 1 +w 
10µm + 0.02δLraw .
1mm

(A.5)

where w is the precipitable water vapor (PWV) content in mm along the line of sight, and Lraw the total
fluctuations observed at any given time. Therefore, this formula includes the expected error of about 2% inmeasuring the total fluctuations, and states the total resulting path errors after correction (Lcorr ). For a 1
mm PWV, the residual term in the formula would be 20 µm. The stability specification for the WVRs is very
stringent (0.1 K peak-to-peak over 10 minutes and 10 degree tilts). To achieve this, a Dicke-switching-radiometer
approach was adopted. The input into the mixer is switched periodically (5.35 Hz) between two calibrated loads(the “cold” and “hot” loads at 293 K and 351 K, respectively), and the sky using a rotating vane embedded in
the light path as shown in Figure A.11.
Calibration of the measurements is done following the usual method for a 2-load system. The ratios of theoutput powers when observing the “hot” and “cold” loads can be used to determine the receiver temperatures.
Furthermore, these output powers from the loads are also used to extrapolate to a virtual load that has abrightness temperature similar to that of the atmosphere. The specification for the absolute accuracy of thecalibration is 2 K (maximum error). The mixer system is an un-cooled DSB Schottky diode pumped by an

196

APPENDIX A. ANTENNAS

Figure A.11: Optical layout within the WVR encasing, showing the loads, the chopper vane and the input feedto the mixer.
LO at 15 GHz that undergoes 2 stages of multiplication. The receiver noise temperature is about 1000 K.
After amplification, the IF signal is split into four complete chains (one per filter) and a bandpass filter isapplied to select the four desired sampling regions in the profile of the water vapor emission line. In each
IF chain, the signal is detected with diodes and after a Voltage-to-Frequency conversion, sent to the Control
section for accumulation and control. There is a possibility of LO leakage out of the WVRs that could affectthe ALMA receivers in the same antenna and others nearby. To avoid coherence, all the WVRs are tuned to afrequency slightly different (offsets by consecutive integer multiples of 10 kHz up to the total number of WVRs
available). The final products sent to the ALMA Control system are time-stamped, calibrated measurementsof the brightness temperatures in the 4 filter regions. The path length error due to the PWV can be calculated
from these brightness temperature measurements and used to correct the data. Corrections at the scales of thesampling rates of the WVRs are possible at the correlator and refinements for longer timescales can also bedone offline in CASA using the wvrgcal tool. Currently both streams of data are being recorded (WVR phasecorrected and WVR non-corrected) in order to rigorously assess effectiveness.

Appendix B

The LO and IF System
In this Appendix, the signal path, LO chain, and the relation between these systems and the observer’s spectral
setups are described. To the system, a spectral setup effectively consists of the settings of the local oscillatorsand correlator in the system such that each spectral window (spw) covers the desired lines and/or continuum
frequencies. To the end-user, the spectral setup is normally defined in the Observing Tool (OT) just in terms of
the observing frequencies and spectral resolutions, and there is no need to worry about the details of each LO
setting. For full details of the OT and how to use it, see the OT User and Reference Manuals, available fromthe ALMA website1 (and also in the OT itself).
The following sections show how the LO system works. For those only interested in the spectral setups andnot the details of the components in ALMA, please see Chapter 6.

B.1

Functions of the LO and IF System

In the signal path from the front end to correlator, ALMA uses three frequency conversions. The associatedLO and IF systems perform multiple functions:
1. Down-conversion of the sky frequencies to basebands in the range 2–4 GHz, which then alias down to 0–2
GHz for digitization.
2. Amplification and adjustment of the correct power levels into the digitizers.
3. Adjustment of the spw center frequencies (in the Correlator FDM modes) within the basebands. This isactually done in the correlator using the TFB LO, but can effectively be treated as a 4th stage of the LO
system.
4. Application of frequency corrections for fringe rotation, and compensation for the slight differences in the
Doppler shifts at each antenna due to the differential line-of-sight velocities with respect to the target.
5. Provision of geometric delay corrections.
6. Separation of the signal and image sideband. In the case of DSB receivers, selection of the wanted
sideband(s). This is done through frequency offsets and phase modulation at each antenna using Walshpatterns.
7. Suppression of spurious signals and reduction of the effects of DC drifts in the samplers. This is doneusing phase modulation of the LOs using Walsh patterns.
1 http://almascience.org/documents-and-tools/

197

198

APPENDIX B. THE LO AND IF SYSTEM

Frequency down-conversion therefore effectively occurs in four stages: two hardware Local Oscillators (LO1and LO2), a 4 GHz sampler/LO and a digital LO synthesised in the tunable filterbanks (TFBs) in the Correlator2 . Section 6 shows how to setup the system to observe spectral lines (particularly multiple spectral lines)
and continuum. Some other aspects of frequency setups are then discussed, including the usable bandwidth,
spurious signals, and rules and limitations pertaining to this observing Cycle. An overview of the LO and IF
operation in ALMA is given in Sections B.2 and in Section B.3, the hardware and how the LO frequencies aresynthesised and distributed around ALMA are described.

B.2

Summary of Operation

Figure B.1: Overview of ALMA frequency downconversion, LO mixing and delay corrections. This takes placein the front end, back end, and correlator. Example frequencies are given for an observation at a sky frequencyof 100 GHz seen in the USB. Some LOs (e.g. LO1) are continuously tunable; others have quantized tuning steps,
such as LO2 (which can be changed in a multiple (“N”) of 125 MHz plus a finely-adjustable offset of “fts”), the
TFB LO (which uses a multiple “L” of 30.5 kHz) and the Bulk Delay Correction (which has steps of 250 ps,
with a factor of “P”). See text for descriptions of each stage.
Figure B.1 shows a simplified block diagram of the ALMA LO/IF system, showing example setups for an
observing frequency centered on 100 GHz. Referring to this diagram, the system operates in the following way:
1. The front-end mixer uses LO1 to downconvert the observing frequency into an IF range covering up to
4-12 GHz. This wide range is needed to cover the IFs of all the ALMA bands, since the mixers for Bands
2 Note that the ACA correlator is designed to appear like the 64-input Correlator to the end user, although it does not use TFBs
in the same way as the BLC

B.3. FREQUENCY GENERATION AND DISTRIBUTION IN ALMA

199

3, 4, 7 and 8 have an output IF of 4-8 GHz, Band 6 a range of 5-10 GHz and Bands 9 and 10 a range of
4-12 GHz. Over most of the front-end tuning range, LO1 and the front-end mixer can be used in upper orlower sideband; although at the edges of the tuning band, only one sideband is possible. LO1 consists of acommon reference component for all antennas, plus a smaller offset component generated in the FLOOG(First LO Offset Generator) which is different for each antenna (see LO1 Section B.3.4). The FLOOG isused to perform coarse fringe tracking (i.e. rough correction for the small offsets in the observing frequency
at each antenna), to offset the LO1 frequencies slightly to suppress internally-generated interference, andfor sideband separation or selecting the sideband. It is also used to offset the LO1 phase in conjunction
with a Walsh switching pattern on the antennas. A 180 degree phase offset is used to remove spurious
signals and DC offset while a 90 degree phase offset is used for sideband suppression and, in the future,for sideband separation on the DSB receivers (Bands 9 and 10).
2. In the back end (BE), the IF processor (IFP) splits the IF into basebands, each with a frequency rangeof 2-4 GHz, via a set of filters and tunable second LOs (LO2) (see IFS/IFP in Section B.3.5). LO2 isused to offset the individual baseband frequencies within the IF range. The LO2 and second mixer only
operates in LSB, with a possible LO2 tuning range of 8-14 GHz. The LO2 signal itself is generated bya course synthesiser which can be set only in steps of 125.0 MHz, plus a second fine-tuned synthesiser(fts) which provides an offset in the range 20.0-42.5 MHz (marked as “fts” in Figure B.1). The limited fts
range and the 125 MHz quantization means that LO2 setting is not fully contiguous; consequently there
can be up to ∼30 MHz difference between the desired and the set value. With a single baseband, this canbe compensated by a suitable offset of LO1, but with multiple basebands this is not always possible. So
without additional correction, setups with multiple basebands could have the requested lines offset fromthe spw center by up to 30 MHz. However, the remaining differences in the different spws are compensatedby applying an opposite offset to the TFBLOs (LO4 - see below.)3 . An algorithm used by the OT andthe realtime system generates the best LO tuning “solution” for LO1, LO2 and LO4 which minimizes theoffset of the requested observing frequencies from the centers of the spws. Other uses of LO2 are thatthe finely-tunable fts is used for fine fringe tracking and LO2 can also be used to offset the frequencies in
conjunction with LO1 to suppress interference and select the sideband.
3. The 2-4 GHz analog IF signal from the second mixer in the IFPs is digitised (or sampled) with a 4.0 GHz
clock (DGCK). A fine delay (or time) offset is applied to this clock in units of 1/16 of the clock period(250 ps) (the “fine delay correction”).
4. In the FDM correlator mode, up to 32 digital filters (known as TFBs, or "Tunable Filterbanks") areapplied to each digitised baseband signal, each of which can be individually adjusted across the baseband
frequency (the TFB offsetting). This is effectively applying a digital LO (the TFBLO, or LO4), which isadjustable in steps of 30.517578125 kHz4 and allows the spectral windows to be moved around within the
basebands. At Phase 2, the TFB is centered on the baseband if the TFB “offset” is set to the default of
3000.0 MHz; it can be moved up to +/-900 MHz from that frequency, the range depending on the spw
bandwidth. The TFB outputs are resampled and sent to the correlator. The TFBLO can also be used tooffset the frequencies in conjunction with LO1 to suppress interference and select the sideband. Finallythe correlator software is used to perform the finest level of residual delay correction.

B.3

Frequency Generation and Distribution in ALMA

Figure B.2 shows a summary of the main units involved in the LO generation and distribution. The LOs are
generated by the Central LO (CLO) (Section B.3.1) in the AOS Technical Building (lower half of diagram).
A fiber-optic system is used to distribute these signals out to the antennas (Section B.3.1) incorporating a
realtime path length correction system (Section B.3.3). In the antennas, the important outputs are LO1 (FE
1st LO) (Section B.3.4), LO2 in the IF Processer (Section B.3.5) and the digitizer clock (DGCK). All of these3 This is done automatically when the OT generates a spectral setup in an SB from a proposal. However, it is repeated at runtime.
See https://safe.nrao.edu/wiki/pub/ALMA/AlmaLamaMemos/lamaMemo808.pdf for more details on the tuning algorithm
4 The Phase 2 OT has an "adjust" button which quantizes the value entered by the user by this unit

200

APPENDIX B. THE LO AND IF SYSTEM

are required in each antenna, shown in the upper part of Figure B.25 . In the following subsections, some ofthese components are described.

B.3.1

Reference and LO Signal Generation

The Central Local Oscillator (CLO) generates and distributes the reference, timing and LO signals to all ALMA
components to ensure that antenna movement, electronics, and data acquisition are synchronized. These signals
are distributed to the antennas through optical fiber using the light of three infrared lasers. The ALMA frequency
and phase standard is a Hydrogen maser (installed in 2014), known as the Master Frequency Standard (MFS,
lower right), which produces a signal at a frequency of 5 MHz. This is fed into the Central Reference Generator(CRG) module, which produces several signals at multiples of the 5 MHz signal. The 125 MHz signal becomes
one of the standards used by many components in the ALMA system. At the AOS Technical building it isused by the Slave Lasers in the Laser Synthesizer modules (Section B.3.2). At the antennas, it is fed into the
FLOOG, the Digital Clock (DGCK, see Section B.3.6), the IFPs, and the LO2 Synthesizers. The 2 GHz signal
goes into the DTS cards at the antennas. All the reference signals are modulated onto a 1532 nm IR laser in
the Central Reference Distributor (CRD) module. The CRD has an internal 48 ms (known as a TE, or Timing
Event) clock that is also modulated into the same signal, and is used to synchronize many of the hardware
events in the observatory. The modulated 1532 nm signal is sent to an optical distributor (with 80 outputs), theLow Frequency Reference Distributor (LFRD), that feeds it into the Sub Array Switch (SAS) modules, where
it is merged with the signals from the Master and Slave lasers (see Section B.3.2). The reference and LO signals
are fed to the antennas through the fiber-optic distribution system (see Section B.3.3).

B.3.2

LO1 Signal Generation and Distribution

LO1 is distributed through fiber-optics and regenerated photonically in each antenna front end by mixing thetwo infrared laser carriers (known as the Master (ML) and Slave Lasers (SL)) to produce a fixed frequency for all
the antennas. Figure B.3 shows a block diagram of this part of the LO system. There are six Slave Lasers (Laser
Synthesizers, LSs), each containing fpour tunable units, that can produce six different LO1 frequencies whichallow simultaneous observations at different frequencies with different subsets of the array (multiple arrays or
sub-arrays), and may be used for observing modes that will benefit from rapid switching between frequencies(e.g., band-to-band transfer or spectral scans).
The laser frequencies are generated in the CLO in the following way:
• The Master Laser (ML) generates a 1556 nm fixed optical reference signal, which feeds the Master Laser
Distributor (MLD) – essentially a 6-way splitter.
• The Central Reference Generator (CRG) produces reference signals that are fed into the six Laser Synthesisers (LS) fed into the six Central Variable Reference modules, which the LSs use to control the frequencyof the the Slave Lasers producing a frequency offset of the SL signal of 27-120 GHz with respect to the ML
signal. The SL signals are added to the ML signal. The offsets between the ML and SL signals provides
the beat note which is used to generate the LO1 frequency in the photomixers in the Warm Cartridge
Assemblies (WCAs) in the front end (B.3.4). It is used by the software to set up the front-end observing
frequency. With six LSs it is possible to generate six separate LO1 frequencies.
• The Photonic Reference Distribution (PRD) feeds the optical signals to the Sub Array Switch (SAS)module (one per antenna), which chooses the sub array to connect to.
Figure B.46 shows the three laser signals after combination in the Sub Array Switches (SAS). The Masterand Slave laser signals have wavelengths of about 1556 nm and the laser carrier signal for the reference signals
from the CRD has a wavelength of 1532 nm. The signals are distributed via a single-mode fiber optic line to
5 Note: The figure needs an update. The frequency of 25 MHz displayed in blocks LORR and LORRD, LFRD, CRD, and CRG
needs to be replaced by 125 MHz. In addition, IFP received a 125 MHz signal from LORR.
6 This figure needs an update. The Slave Laser (variable) wavelengh is ∼1557 nm.

B.3. FREQUENCY GENERATION AND DISTRIBUTION IN ALMA

201

Figure B.2: Summary block diagram of the LO distribution system. The components in the lower section of the
diagram (below the the dashed-dotted line) form the Central LO (CLO), located in the AOS Technical Building.
The components above are located in each Antenna (only one antenna is depicted in this diagram). These arelinked by the exterior buried fibers linking the Technical Building with the antenna pads (shown middle-left ofthe diagram). Thin lines with arrows represent cable distribution, thick lines represent fiber-optic distribution.

202

APPENDIX B. THE LO AND IF SYSTEM

Figure B.3: LO block diagram, showing the Central LO (CLO) and the LO section in the WCA in each front
end. Yellow lines represent common synchronization and reference signals fed to all antennas, blue lines are LO
signals which are individual to each antenna. For a description of acronyms, see text.
each of the antennas. The fibers are distributed in buried trenches, and fed into the Cassegrain cabin on eachantenna through Az and El fiber wraps. All are fed through Line Length Correctors (LLCs), which are used tocorrect for changes in the optical fibers. The LLCs are described in B.3.3 below.

Figure B.4: The ALMA fiber signals. The 1532nm carrier contains the frequency reference signals, and the1556/1555 nm carriers are used to remotely generate LO1. Within each antenna, the optical signals are split
and fed to both the LO Reference Receiver (LORR) for the demodulation of the reference/timing signals, andthe LO Photonic Receiver for the LO Reference signals.

B.3.3

Line Length Corrections

The LO Reference signals are generated at the AOS Technical Building and need to be distributed via opticalfibers to all the antennas. In order to guarantee that the phase of the LO signals is stable during the observations
for fibers of up to 15 km in length, compensation for changes has to be done in real time. The method adopted
by ALMA is based on a round-trip optical interferometer. Phase fluctuations for an optical fiber transmission
system are mainly caused by thermal expansion of the fiber and mechanical stresses, which produce birefringent
effects and changes in the absolute polarization of the signals. These changes, in turn, cause differential grouppropagation delays (PDM) that show up as LO phase jitter. The method implemented by ALMA to correct
for this is known as the Line Length Corrector (LLC). Part of the LLC can be seen in Figure B.3, and a moredetailed block diagram of the system is shown in Figure B.5.
The two-wavelength laser synthesizer signal (master and slave lasers) is adjusted in polarization and mixed
at the SubArray Switch (SAS) and then passed through a 3-port polarizing beam splitter assembly (PBS). The
polarization is aligned so that all the light passes through the beamsplitter. It then passes through a piezodriven fiber stretcher assembly and the fiber to the antenna. At the antenna end there is a 3-dB coupler, so that

B.3. FREQUENCY GENERATION AND DISTRIBUTION IN ALMA

203

Figure B.5: Block diagram of the Line Length Corrector system for ALMA. The FRM (Faraday Rotation
Mirror), shown upper right, is located in the Band 9 cartridge of every front-end. It rotates the polarisation of
the incoming light, and the resulting reflected signal is fed back though the buried optical fiber, to be comparedwith the outgoing signal. This allows the optical path length to be adjusted in a closed loop using the fiber
stretchers.
half of the light goes to the turnaround assembly and half to the photomixer in each WCA. The turnaroundassembly consists of a fiber frequency shifter (located at the LO Photonic Receiver module) and a Faraday
Rotator mirror located within the WCA of specifically the Band 9 cartridge in each front end. The frequency ofthe signal traveling back to the AOS technical building receives thus twice a frequency shift of 25 MHz, thus itcomes back offset by 50 MHz from the original. The Faraday rotator reflects the signal but turns its polarization
angle by 90 degrees to the incident polarization. This means that the outgoing and returning light is orthogonal
everywhere along the fiber between the PBS and the Faraday Mirror. Back at the PBS, the returning signal
is sent to a third port where it is mixed with a sample of the Master Laser reference signal in a low-frequency
photodetector. This results in an output at the 50 MHz offset frequency. This output is compared in a phasedetector with a 50 MHz reference signal and the phase of the whole loop is kept constant by a servo driving thefiber stretchers.
The current stretchers can cover ranges up to 5 mm in two modes. A “slow” mode (about 10Hz) copeswith the large deformations (about 3 mm, allowing for some headroom at the ends of the ranges) and a “fast”
response mode (about 1 kHz) copes with the small range variations (about 0.1 mm). The LLCs are reset to
mid-range at the start of every SB execution.

B.3.4

The First Local Oscillator (LO1)

The reference signal required to tune LO1 in the receivers is obtained as the difference of the wavelengths oftwo phase-locked infrared lasers, the Master and Slave lasers. The Master Laser (ML) has a fixed wavelength of1556 nm and the tunable Slave Laser (SL) is offset from this; both are generated in the CLO (see Section B.3.2).
The offset frequency can be anywhere in the range 27 to 38 and 65 to 122 GHz. The beat note from the twolasers constitutes the Photonic LO Reference; the LO1 reference signal is generated from this by photomixers
located in the Warm Cartridge Assembly (WCA) of each receiver. This reference signal is used to drive a YIG(Yttrium Iron Garnet) oscillator operating at frequencies around 10–30 GHz (the exact range depending on theband), via a Phase Locked Loop (PLL) circuit. This produces LO1 for the SIS mixers via two sets of multipliers

204

APPENDIX B. THE LO AND IF SYSTEM(see example Figure B.6 for Band 7). The same photonic reference signal is distributed to all antennas in thesame sub-array. However, to correct for different delay rates required in different antennas, the First LO Offset
Generator (FLOOG) in each antenna generates a small but variable (and different) offset frequency in the range
20–45 MHz which is also fed into each PLL. The FLOOGs for all the antennas are continuously tracked during
an observation.

B.3.5

LO2 and the IF Processor Units and IF Switch

The output of each front-end cartridge is connected to an IF Switch unit (IFS) situated in the front end, which
selects between bands, provides some amplification, and has variable attenuators to set the output levels. The
four (or two) outputs from the IF switch unit are fed into two IF Processor units (IFP), one per orthogonal
polarization. Figure B.7 shows a basic block diagram of one IF Processor (only one polarisation channel isshown). The Bands 3, 4, 6, 7 and 8 receivers are dual-sideband (2SB), where both the upper and lower sideband
signals are provided separately and simultaneously. So there are four outputs from each receiver cartridge inthese bands, two sidebands times two polarisations. Each output has an IF bandwidth of up to 4 GHz. For
Bands 9 and 10, the receivers are double-sideband (DSB), where the mixer produces a downconverted output
from signals in both USB and LSB. These bands have only two outputs, one per polarization, but the signal IF
bandwidth of these DSB receivers is 8 GHz per output.

Figure B.6: Block diagram showing generation of LO1 in a WCA - in this case Band 7 (diagrams for the otherbands are shown in the description of the individual bands). Note that an additional multiplier, not shown
here, is used to generate the LO1 frequency at 282.9 – 365.1 GHz (in this case, an x3 multiplier). The photonic
LO signal (green) feeds a photomixer which creates a beat signal between the ML and SL frequencies. Thisis mixed with a fraction of the LO from the YIG (x6), and the difference frequency is used in the PLL. The
FLOOG also generates a small offset frequency for the PLL, which is different for each antenna. See text for
details.
The IF processors divide the incoming IF bands from both sidebands into four 2 GHz basebands anddownconvert them to the 2-4 GHz range using the second LO (LO2). Since each baseband is fed by a separate
LO2, it is possible to locate them at different frequencies within the IF bandwidth of the receiver (see Chapter 6

B.3. FREQUENCY GENERATION AND DISTRIBUTION IN ALMA

205

and Table 6.2 for limitations). The LO2s are common to both mixer polarizations which means that bothpolarizations will have the same spectral setups.
The LO2s are digitally-tuned YIG oscillators with a range of 8-14 GHz. LO2 is generated from a harmonicof 125 MHz, plus a fine-tuned synthesiser (fts) of range 20-42.5 MHz, added or subtracted depending on thelock sideband selected by the software. Note that this does not give continuous LO2 coverage, and has to becompensated elsewhere in the LO system.
The IFP unit has 0.5 dB stepped attenuators and Total Power detectors for tuning/optimization of the
IF power levels into the digital samplers; these levels are set up at the start of each scan. It is important tonote that the switch network layout in the IFP means it is NOT possible to select IF configurations with one
baseband in one sideband and three in the other (except for DSB receivers, where this is done using sideband
selection). The IFP has anti-alias filters, one set of which is switchable depending on whether the IF range in
use is in the upper or lower part of the IF band. As well as downconversion, the LO2s can also be used forsideband separation when combined with the first LO (Section B.1).

Figure B.7: Block diagram of one polarisation channel of the IF Processor. This has two IF inputs (at left),and feeds 4 baseband (BB) outputs to the digitisers (to the right of the diagram).
The IF processor also has anti-aliasing filters, which define the 2 GHz baseband width and remove out-ofband signals (Section B.3.6). This results in the higher noise levels on the upper and lower 50-100 MHz ofchannels in the TDM correlator mode (see Section 6.4). These filters cause a decrease in the effective IF range
to approximately 1.875 GHz.

B.3.6

Digitization and Signal Transmission

The outputs of the IF Processor units are fed into the Data Transmission System Transmitter (DTX), that
include digitizers and formatters to convert the signals to optical wavelengths for transmission via optical fibers.
There are four DTX units per antenna, each one handling data for a given baseband pair (i.e., the same 2 GHz
baseband from each of the two orthogonal polarizations). Each baseband is digitized by a separate digitizer
at 4 GHz (i.e., Nyquist sampling for a 2 GHz bandwidth), quantizing each sample into 3 bits (8 levels) per
polarization, so that a total of 6 bits must be transferred per baseband pair. The digitized signal is thentransferred to the formatter part that packages the data in frames of equal size. The output of each DTX
module is fed to three optical fibers, each transporting 2 bits, and the signal leaves the antenna after passing
through a Fiber Optic Multiplexer (FOM). All DTX modules are fed with reference/timing signals from anassociated Digital Clock (DGCK), which is also used to do the fine delay tracking.
The outputs of the DTX are sent, via the optical fibers, to the AOS Technical Building where the process isinverted (conversion from optical to digital signal) at the DRXs (Data Transmission System Receiver modules),before the signals are sent to the correlator. Delay corrections due to changes in the length of the opticalfibers are done using metadata information to realign the frames sent from the transmitting side at the antenna

206

APPENDIX B. THE LO AND IF SYSTEM(DTX) and the receiving side at the Technical Building (DRX). Figure B.8 shows a block diagram of a single
DTX module.

Figure B.8: The Data Transmission System Transmitter (DTX) module, as used in each antenna.

B.4

Other functions of the LO/IF

In addition to frequency downconversion, the LO/IF performs several other tasks, detailed below.

B.4.1

Delay Corrections

ALMA handles delay corrections via the “Delay Server” software package. It computes the corrections for all
the different components involved with a cadence of one minute and distributes them buffered. The three main
components along the data flow chain where the corrections are applied are: the First LO Offset Generator(FLOOG), the Digital Clock (DGCK) and the correlator (see Figure B.1). Fringe tracking is done at the
FLOOG by slightly offsetting the frequency of the LO1 signal. Currently, the delay handled by the FLOOG isin steps of 250 ps. The FLOOG is also used for phase and frequency switching for suppression and separationof sidebands, and for rejection of internally-generated interference, described in the next subsections.
Fine delay corrections are handled by the DGCK that feeds the corrections into the four DTS modules ineach antenna. The delay correction resolution of these is 1/16 of the FLOOGs (i.e., 1/16th of 250 ps). The bulk
delay correction is handled by the Correlator in integer multiples of the 250 ps units. On top of these corrections,the correlator also handles the “residual” delay corrections at much higher temporal resolution (<250 ps/16)
by applying a linear phase gradient across the passband after correlation. Also, the correlator applies relative
delay corrections between all the basebands and polarizations of a given ALMA band receiver. Currently, thefirst baseband of the X polarization is used as reference.

B.4. OTHER FUNCTIONS OF THE LO/IF

B.4.2

207

Sideband Suppression - LO Offsetting

Some of the ALMA receivers (e.g. Bands 3, 4, 6, 7, and 8) are inherently single sideband (SSB), either throughhaving a mixer or quasioptic design which rejects the unwanted sideband7 . Their intrinsic sideband rejection istypically only about 10-15 dB, which, although adequate for rejection of the unwanted sky noise, is not enoughto remove strong lines from the other (image) sideband. Others receivers (Bands 9, 10) are double sideband(DSB), and the relative response of the two sidebands may not be equal, significantly affecting calibration.
Accordingly, additional schemes are necessary for more effective removal of the unwanted sideband (known as
sideband suppression), and for correlation of both sidebands independently (or sideband separation - see next
section). Sideband suppression in ALMA is done using the FLOOG, and either LO2 (2LO offsetting) or a
combination of LO2 and LO4 (3LO offsetting). A small frequency offset Fo is added to LO1 and subtracted
from the other LOs, so that while the signal sideband remains at the same frequency, the image sideband is
shifted 2Fo away from its nominal value. A different value of Fo is applied at every antenna (the offsets aredefined using a Walsh pattern), so that all signal sidebands are at the same frequency, but all image sidebands
are at slightly different frequencies and no longer correlate.
Note that each of the basebands has an independent LO2 and LO4. So by setting the sign of the offset in(LO2+LO4) differently, each baseband can be set up to observe in a different sideband.
For single-dish observing, such interferometric sideband rejection methods cannot be used, and a frequency
scanning method is under development which will allow image rejection.

B.4.3

Interference Rejection - 180 degree Phase Switching

The FLOOG is additionally used to reject spurious signals prior to digitization by applying 180 deg phaseswitching according to orthogonal Walsh function patterns, with a pattern cycle time of 16 ms. The Walshpattern is different on each antenna, and is demodulated by a sign change within the DTS; as a result, thewanted signals correlate, and the unwanted signals are canceled out. This rejects spurious signals generated
in the system between the receiver and the sampler, and also suppresses sampler DC offsets. 180-Walsh is a
default setup for all observations. For further details please see Section 5.5.4.

B.4.4

Sideband Separation - 90 degree Walsh Switching

It is possible to apply a 90 deg phase switch in the FLOOG and in the correlator processing, allowing correlationof the upper and lower sidebands separately. For Bands 9 and 10 (DSB) it will effectively double the bandwidthfrom 8 GHz to 16 GHz per polarization from the DSB receivers. For further details please see Section 5.5.4.

7 Although they have mixers to allow both sidebands to be observed separately and simultaneously

208

APPENDIX B. THE LO AND IF SYSTEM

209

210

APPENDIX C. ACRONYM DICTIONARYAppendix C

Acronym Dictionary
2SB
ACA
ACD
ACS
ALMA
AoD
AOS
APDM
APP
APS
AQUA
ARC
ASA
ASC
ASDM
ASIC
AZ
BB
BDF
BE
BL
BLC
BWFN
BWSW
CASA
CCA
CCC
CDP
CFRP
CLO
CLT
CORBA
CRD
CRG
CSV
CW
DC
DEC
DFP
DGC

Dual Sideband
Atacama Compact Array
Amplitude Calibration Device
ALMA Common Software
Atacama Large Millimeter/Submillimeter Array
Astronomer on Duty
Array Operation Site
ALMA Project Data Model
ALMA Phasing Project
ALMA Phasing System
ALMA Quality Assurance software
ALMA Regional Center
ALMA Science Archive
ALMA Sensitivity Calculator
ALMA Science Data Model
Application Specific Integrated Circuit
AzimuthBasebandBinary Data Format
BackendBaseline
BaseLine Correlator
Beam Width between First Nulls
Bandwidth Switching
Common Astronomy Software Applications package
Cold Cartridge Assemblies
Correlator Control Computer
Correlator Data Processor
Carbon Fiber Reinforced Plastic
Central Local Oscillator
Chilean Local Time
Common Object Request Broker Architecture
CentralReference Distributor
Central Reference Generator
Commissioning and Science Verification
Continuous Wave
Direct Current
Declination
DTS-Rx and FFT Processor
Differential Gain Calibrator

211

DGCK
DMG
DRX
DSB
DSO
DTS
DTS-Rx
DTX
EB
EHT
EL
EM
EPO
ES
ESO
FDM
FE
FITS
FLOOG
FOM
FOV
FPGA
FT
FWHM
FWHP
FWBN
FXF
GMVA
GPS
HA
HEMT
HPBW
IF
IFP
IRAM
JCMT
JPL
LAS
LFRD
LLC
LO
LO1
LO2
LO3
LO4
LORR
LS
LSB
LSRK
MD
LTA
MCI
MFS

Digital Clock
Data Management Group within DSO
Data Receiver module
Double Sideband
Division of Science Operations
Data Transmission System
Data Transmission System Receiver
Data Transmitter module
Execution Block
Event Horizon Telescope
Elevation
Electromagnetic
Education and Public Outreach
Early Science
European Southern Observatory
Frequency Division Mode
Frontend
Flexible Image Transport System
First LO Offset Generator
Fiber Optic Multiplexer
Field of View
Field-Programmable Gate Array
Fourier Transform
Full Width Half Maximum
Full Width to Half Power
Full Width Between the Nulls
Filtering, Correlation, and Fourier transform type correlator
Global Millimiter VLBI Array
Global Positioning System
Hour Angle
High Electron Mobility Transistor
Half Power Beam Width
Intermediate Frequency
Intermediate Frequency Processor
Institut de Radioastronomie MillimetriqueJames Clerke Maxwell Telescope
Jet Propulsion Laboratory
Largest Angular Resolution
Low Frequency Reference Distributor
Line Length Corrector
Local Oscillator
First LO
Second LO
Digitizer Clock Third LO
Tunable Filterbank LO
LO Reference Receiver
Laser Synthesizer
Lower Sideband
Local Kinematics Standard of Rest
Mixer De-tuned
Long Term Accumulator
Monitor and Control Interfce
Master Frequency Standard

212

APPENDIX C. ACRONYM DICTIONARY

ML
MLD
MRS
MS
NGAS
NRAO
NVSS
OMC
OMT
OSF
OST
OT
OTF
OUS
PBS
PDM
PI
PLL
PMG
PRD
PSF
PWV
QA
QA0
QA1
QA2
QA3
QL
RA
RF
RMS
SAS
SB
SCO
SD
SED
SIS
SL
SNR
SPW
SRON
SSB
SSR
STE
STI
TA
TDM
TE
TelCalTFB
TFB LO
TMCDB
TP
Tsys

Master Laser
Master Laser Distributor
Maximum Recoverable Scale
Measurement Set
New Generation Archive System
National Radio Astronomy Observatory
NRAO VLA Sky Survey
Operator Monitoring and Control
Ortho-mode Transducer
Operations Support Facility
Observation Support Tool
Observing Tool
On the Fly
Observing Unit Set
Polarization Beam Splitter
Propagation Delay Measure
Principal Investigator
Phase Lock Loop
Program Management Group within DSO
Photonic Reference Distribution
Point Spread Function
Precipitable Water Vapor
Quality Assurance
Quality Assurance Level 0
Quality Assurance Level 1
Quality Assurance Level 2
Quality Assurance Level 3
QuickLook pipeline
Right Ascension
Radio Frequency
Root Mean Square
Sub Array Switch
Scheduling BlockSantiago Central OfficeSingle Dish
Spectral Energy Distribution
Superconductor-Insulator-Superconductor Mixer
Slave Laser
Signal-to-Noise Ratio
SPectral Window
Stichting Ruimte Onderzoek Nederland (Netherlands Institute for Space Research)
Single Sideband
Science Software Requirements
Standard Test Environment
Site Testing Interferometer
Technical Assessment
Time Division Mode
Time Event
Telescope Calibration subsystem
Tunable Filterbanks
Local Oscillator at the Tunable Filterbanks
Telescope Monitor and Configuration DataBase
Total Power
System Temperature

213

Trx
USB
VLA
VOM
VO
WCA
WVR
XF
YIG

Receiver Temperature
Upper Sideband
Very Large ArrayVLBI Observing Mode
Virtual Observatory
Warm Cartridge Assembly
Water Vapor Radiometer
Correlation-Fourier Transform Type Correlator
Yttrium-Iron Garnet Oscillator

Indexuv-coverage, 92
uv-plane, 22
uv-taper, 96
12-m Array, 9, 12
64-input Correlator, 9, 12, 59, 60
7-m Array, 9, 11, 13, 64

power response, 19
response, 16
specifications, 185
surface, 185transportation, 189
transporters, 11
types, 186
ACA Correlator, 9, 62
AOS Technical Building, 199
Airy function, 19
Aperture, 17
Alcatel Alenia Space European Industrial Engineering
synthesis, 19
MT Aerospace (AEM), 185
Application Specific Integrated Circuit, 62
Aliasing, 28
Array
ALMA
performance, 160
Archive, 179
Array Operations Site (AOS), 11
Common Software (ACS), 163
Astronomer on Duty, 109, 158
Frontend Archive (AFA), 179
Atacama Compact Array, 9, 11
location, 11
Atacama Large Millimeter/Submillimeter Array, 9
Science Archive (ASA), 179
Atmosphere
Science Data Model (ASDM), 165, 166
opacity, 131
ALMA Common Software (ACS), 11
Atmospheric calibration (ATM), 193
ALMA Project Data Model (APDM), 109
Atmospheric transmission, 31
ALMA Regional Center (ARC), 179
Auto-correlation, 20
ALMA Science Data Model, 141
Autocorrelation
ALMA subsystem, 163
data, 142
Control, 163
Executive, 163
Barlett weighting, 68
Scheduler, 163
Baseband(s), 12, 13, 59, 75
Telescope Calibration, 163, 164
desired center, 77
Amplitude, 15, 22
Baseline, 20
Amplitude Calibration Device, 33, 148Baseline Correlator, 59
Amplitude Calibration Device (ACD), 192
Beam shape, 92
Angular resolution, 88, 92
Bessel function, 19
Antenna
Binary Data Format, 71
delay offset, 146
Brightness, 16
position, 147
temperature, 28
power response, 19
Brightness temperature, 28
Antenna beam, 144
Bulk binary data, 166
Antenna(s)Calibration
beam size, 17
amplitude, 115
CM, 12antenna pointing, 148
design and properties, 185atmospheric, 115
foundations, 11, 187
bandpass, 113
pads, 187
baseband, 149
panels, 186
flux, 113
performance specifications, 12, 185
flux density, 151
PM, 12

214

215

INDEX

gain, 150
phase, 113
plan, 159
polarization, 152receiver temperature, 147
summary, 158
system temperature, 147
system-defined, 112
user-defined, 112
water vapor radiometer, 147
Calibration observation, 111
Calibrations
apriori, 143
offline, 144
online, 144
Cartridge assembly, 31
Cassegrain focus, 186
Chajnantor, 11
Chajnantor Plateau, 10
Cittert-Zernike theorem, 22
Clock rate, 62Complex visibility
function, 141
Complex visibility, 22
distribution, 22
Configurations, 88
Contact scientist, 160
Correlator
64-input, 12
ACA, 12, 59
capabilities, 66
FX, 13, 62
XF, 12
Correlator delay model, 141
Correlator and Integration Processor, 62
Correlator Data Processor, 62
Correlator mode
FDM, 199
Cosmic Microwave Background, 132
Cross-correlation, 20
Cryostat, 189
Cycle 0, 9
Datadelegation, 181delivery, 180
download, 182
replication, 180
Data and Control Flow, 163
Data Capture module, 165
Data Management Group, 157
Data rate, 12
average, 179
peak, 179

Data receivers, 64
Data Reducers Team, 159
Deconvolution techniques, 24
Delay
artificial, 20
geometrical, 20
Digital Transmission System Receiver, 62
Digital Transmitter, 64
Digitizers, 64
Director’s Discretionary Time, 180
Dirty
beam, 24
image, 24
Dirty beam, 88
Doppler shift, 197
Doppler tracking, 84
DTS and FFT processor, 62
Dump rates, 13
Early Science
Operations, 9Earth rotation, 23
Electromagnetic power, 16
Ephemeris file, 84, 119
Execution Block (EB), 111
Feathering, 104
Field of view, 23, 99
Field programmable gate array, 61
FITS format, 182
Flagging
calibration-based, 149
on-line, 149
Flux density, 16, 28
Focus model, 145
Fourier transform, 15
Fraunhofer approximation, 19
Frequency
center offset, 77
definitions, 77
generation, 199
rest, 77sky, 77
synthesizer, 76
Frequency and phase standard, 200
Frequency Division Mode (FDM), 60
Frequency Profile Synthesis, 62
Fringe, 22
rotation, 197
spacing, 23
tracking, 199
Frontend, 31, 189
Full Width Between Nulls, 18
Full Width Between the Nulls, 18
FXF, 60

216

Gibbs phenomenon, 96
Grid source, 114
Group Observing Unit Set (GOUS), 111
Half Power Beam Width, 17Hanning function, 67
Helpdesk, 160
Image fidelity, 24
Imagingsimultaneous, 77
Integration time, 102
Interferometer
resolution, 26
two-antenna, 20Interferometry
single field, 113
Intermediate frequency, 33, 75
Jansky, 16
Joint ALMA Observatory (JAO), 11
JPL Horizon format, 119
Koh-ichiro Morita, 14
Lasers, 200
LO and IF systems, 197
operations, 198
Local Oscillator, 33, 59, 75
offsetting, 81
Local Oscillator (LO), 12
Long Term Accumulator, 62
Lower sideband, 75
Maximum recoverable scale, 13, 26, 97, 100
Member Observing Unit Set (MOUS), 111
Metadata, 166
Metrology, 187
Mitsubishi Electric Corporation (MELCO), 185
Morita Array, 9Mosaicing, 23, 99, 114
Multiple pointings, 114
Multiple Region Modes, 119
NED, 181
Next Generation Archive System, 179
Observations
on-the-Fly Mapping, 114
total power, 114
Observingproject, 109
proposal, 109
script, 109, 112
session, 111
Observing mode(s), 9

INDEX

Observing session, 163
Observing Unit Set, 161
Observing Unit Set (OUS), 111
On-the-fly scan (OTF), 13
Operation Support Facility (OSF), 11
Otho mode transducer, 35
Output radiance, 131
Pampa la Bola, 11
Parallactic angle, 118
Phase, 15, 22
Phase 1, 75, 109
Phase 2, 75, 109
Phase calibration, 80
Phase center, 21
Phase switching, 83
Pipeline, 10Plateau de Bure, 16
Pointing model, 144
Polarization, 16, 82, 115
instrumental, 116
off-axis, 116
Position switching, 13
Precipitable water vapor, 66
octiles, 131
Precipitable water vapourt
octiles, 132
Primary beam, 17, 99
correction, 23
Primary focus, 186
Program Management Group, 157
Proposer’s Guide, 9, 111
Proprietary period, 180
Quality Assurance, 157
categories, 158
classification, 157
report, 161
Quantization, 59
efficiency, 72
Radiometer
Dicky-switching, 195
Rayleigh resolution, 18
Rayleigh-Jeans limit, 28
Receiver(s)2 sideband, 134
double sideband, 134, 135
heterodyne, 134
Rectangular field, 114
Reflector
secondary, 19
Robustness, 93
San Pedro de Atacama, 11

217

INDEX

Scan, 111, 164
Scheduling Block, 158
Scheduling Block (SB), 109
Sciencegoal, 109, 114
parameter(s), 109
Science Archive Content Manager, 158
Science Pipeline, 159
Science Software Requirements, 111
Sensitivity, 78, 131
point-source, 136
surface brightness, 137
Shadowing, 26, 91
Shutter, 187
Sidebanddouble, 32, 81
double (DSB), 12
dual, 12, 32
single, 32
Sidelobes, 18, 24, 87, 96
Simbad, 181
Sky brightness distribution, 15, 22
Sky frequency, 75
Snapshot, 96
Solar observations, 121
Solar system objects, 119
Spatialfiltering, 24, 97
frequency, 15, 21
Spatial coherence function, 114
Specific intensity, 16, 28
Spectral setup, 75, 77
Spectral window (spw), 61, 75
Standard observing modes, 159
Standard Test Environment, 163
Stokes parameters, 115
Sub-arrays, 12
Submillimeter Array (SMA), 16
Subreflector, 186
Subscan, 164
Subsystems
QuickLook, 112
Control, 112
Scheduler, 111
Telescope Calibration, 112
Surface characteristics, 144
Synthesized beam, 24
Technical Handbook, 9
Telescope
filled-aperture, 20
Telescope Monitor and Configuration Data Base, 145
Telescope operator, 163
Temperaturesky, 131
system, 131
Tiltmeters, 187
Time Division Mode (TDM), 60
Tools
AQUA, 158, 161
JIRA, 157
Monitor and Control, 158
Project Tracker, 158
QuickLook, 158
TelCal, 158
Total Power Array (TP Array), 11
Total Power Array (TP Array), 9, 13, 14, 64
Transporter, 189
Tunable Filter Bank (TFB), 12, 60, 198
Tuning range, 81
Upper sideband, 75User Policies, 160
Van Vleck relationship, 72
Velocity definition
Optical, 84Radio, 84
Relativistic, 84
Velocity reference, 83
Barycentric, 84
LSRK, 84
Topocentric, 84
VertexRS, 185
Virtual Observatory, 181
Visibility, 15
Visibility function
weighted, 87Vizier, 181
Voltage response, 19
VOTables, 181
Walsh-switching, 59, 83
Water Vapour Radiometer (WVR), 12, 66, 194
Weblog page, 159
Weighting
Briggs, 93
natural, 87, 92
uniform, 87, 93
WVR Correction, 66
WVR correction, 59
XML tables, 165
Zero spacing, 114
Zero-point fluctuations, 133
Zero-spacing problem, 13, 26