Doc 4.3, ver. 1.0 | March 22, 2016

ALMA Cycle 4 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

1.0
1.0
1.1

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

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

Replace figs 7.9 and 7.10

Authors
Itziar de Gregorio - Chapter 1; Antonio Hales - Chapter 2; James Di Francesco - Chapter 3; Shin’ichiro
Asayama - Chapter 4; Seiji Kameno - Chapter 5; Bill Dent - Chapter 6; Eric Villard - Chapter 7; Baltasar Vila
Vilaro - Chapters 8 ,10 and 12; Andy Biggs - Chapter 9; Ed Fomalont - Chapter 10; Erik Müller - Chapter 11;
Liz Humphries - Chapter 13; Felix Stoehr - Chapter 14.

Contributors
Mark Adams, Eiji Akiyama, Paola Andreani, Yiping Ao, Denis Barkats, James Braatz, Crystal Brogan,
James Chibueze, Stuartt Corder, Juan Cortes, Paulo Cortes, Carlos De Breuck, Jennifer Donovan Meyer,
Darrel Emerson, Daniel Espada, Roberto Galvan-Madrid, Bunyo Hatsukade, Cinthya Herrera, John Hibbard,
Akihiko Hirota, Todd Hunter, Remy Indebetouw, Akiko Kawamura, Takeshi Kamazaki, Eelco van Kampen,
Rüdiger Kneissl, Shinya Komugi, Yasutaka Kurono, Mark Lacy, Stephane Leon, Harvey Liszt, Carol Lonsdale,
Andreas Lundgren, Brian Mason, Geoff Mathews, Jeff Mangum, Nuria Marcelino, Ivan Marti-Vidal, Rie Miura,
Koh-Ichiro Morita, Hiroshi Nagai, Lars-Åke Nyman, Sachiko Okumura, Rosita Paladino, Alison Peck, Dirk Petry,
Neil Phillips, David Rabanus, Matias Radiszcz, Suzanna Randall, Mark Rawlings, Anita Richards, Masao
Saito, Markus Schmalzl, Scott Schnee, Kimberly Scott, Kartik Sheth, Richard Simon, Hiroko Shinnaga, Giorgio
Siringo, Thomas Stanke, Kenichi Tatematsu, Ignacio Toledo, Rein Warmels, Al Wootten, Jorge F. García Yus,
Martin Zwaan.
In publications, please refer to this document as:
ALMA Partnership, 2016, S. Asayama, A. Biggs, I. de Gregorio, B. Dent, J. Di Francesco, E. Fomalont,
A. Hales, E. Humphries, S. Kameno, E. Müller, 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 4 Receivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.1 Band 3 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.2 Band 4 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.3 Band 6 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.4 Band 7 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.5 Band 8 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.6 Band 9 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2.7 Band 10 Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

31
33
33
35
38
41
44
47
50
53

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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5.2 Spectral Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

57
58
58
59
60
60
62
62
64
64
64
64
65

3

4

CONTENTS

5.5.3 Time Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Practical Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.1 Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.2 Linearity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Final data product - the ASDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66
68
68
68
69

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 Band 9 & 10 and DSB Considerations . . . . . . . . . . . . . . . . . . .
6.4 Usable Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.5 Spectral Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.6 Spurious Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.7 Doppler Setting and Velocity Reference Frames . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.8 Limitations and Rules for Spectral Setups in Cycle 4 . . . . . . . . . . . . . . . . . . . . . . . . .

71
71
73
73
74
76
76
77
78
78
79
79
80

7 Imaging with ALMA
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2 Cycle 4 Configurations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.3 Shadowing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.4 Resolution and Beam Shape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.5 Response and Snapshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.6 Spatial Scale Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.7 Mosaicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.8 Multi-array and Multi-configuration Observations . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.9 Multi-array and Multi-configuration Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

81
81
82
85
86
90
92
93
94
97

5.6

5.7

8 Observing Modes
103
8.1 Observing Project Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
8.2 Program Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
8.3 The Observing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
8.3.1 The source selection algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
8.4 Single Field Interferometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
8.5 Pointed Mosaic Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
8.6 Single Dish (Total Power) Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
8.7 Polarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
8.7.1 Sessions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
8.8 Multiple Region Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
8.9 Observation of Ephemeris Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
8.10 Solar Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
8.10.1 Solar Observing Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
8.10.2 Array Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
8.10.3 Single Dish Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
8.11 VLBI Observing Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
8.11.1 General VLBI Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
8.11.2 ALMA Considerations for VLBI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
8.12 High Frequency Observing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123

CONTENTS

59 ALMA Sensitivity Calculator
125
9.1 Calculating the System Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
9.1.1 Sky temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
9.1.2 CMB temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
9.1.3 Receiver temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
9.1.4 Ambient temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
9.1.5 DSB receivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
9.1.6 System temperature (OT version) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
9.1.7 System Temperature (Applet and GUI version) . . . . . . . . . . . . . . . . . . . . . . . . 129
9.2 The Sensitivity Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
9.2.1 12-m and 7-m Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
9.2.2 Total Power Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
9.3 User Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
9.4 Total Time Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
10 Calibration and Calibration Strategies
135
10.1 The Measured Visibility Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
10.1.1 The Data Format and the Correlator Model . . . . . . . . . . . . . . . . . . . . . . . . . . 135
10.1.2 The Visibility Function Dependence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
10.2 Main Interferometric Calibration Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
10.2.1 Phase Referencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
10.2.2 Antenna-based Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
10.2.3 Major Calibrations Affecting Interferometric Data . . . . . . . . . . . . . . . . . . . . . . 136
10.2.4 The Organization of the Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
10.3 ALMA-Supplied a Priori Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
10.4 Online Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
10.5 Offline Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
10.6 Special Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
10.6.1 Phase Referencing, especially above 400 GHz . . . . . . . . . . . . . . . . . . . . . . . . . 143
10.6.2 Phase Calibration with Narrow Bandwidths . . . . . . . . . . . . . . . . . . . . . . . . . . 144
10.6.3 Astrometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
10.6.4 Long Baseline Observations with Baselines > 2 km . . . . . . . . . . . . . . . . . . . . . . 147
10.6.5 Total-Power Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
10.6.6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
11 Quality Assurance
149
11.1 Cycle 4 "Best Efforts" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
11.2 QA0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
11.3 QA1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
11.4 QA2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
11.5 QA3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
11.6 The Quality Assurance Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
11.7 QA Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
12 Data Flow and Logical Data Structure155
12.1 Data and Control Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
12.2 The ALMA Science Data Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
13 Pipeline Processing
159
13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
13.2 Pipeline In ALMA Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
13.2.1 Pipeline Triggering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
13.2.2 Pipeline Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
13.2.3 Pipeline Runtime Database-querying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
13.2.4 Pipeline and the ALMA Quality Assurance Process . . . . . . . . . . . . . . . . . . . . . 160

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CONTENTS

13.2.5 Standard and Non-standard Observing Modes . . . . . . . . . . . . . . . . . . . . . . . . . 164
13.3 Pipeline Processing of an ALMA OUS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
13.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
13.3.2 Pause after Data Import . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
13.3.3 Output of the Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
13.4 Pipeline Initialisation & Calibration Table Editing . . . . . . . . . . . . . . . . . . . . . . . . . . 164
13.5 General Interferometric ALMA Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
13.5.1 Data Import & Calibrator Flux Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
13.5.2 Deterministic & Manual Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
13.5.3 Flagging lines in Solar System Object Flux Calibrators . . . . . . . . . . . . . . . . . . . 165
13.5.4 Raw Data Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.5 Reference Antenna Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.6 System Temperature Calibration & Flagging . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.7 Antenna Position Corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.8 Offline WVR Calibration for 12m Array Data . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.9 Gain Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.10 Bandpass Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
13.5.11 Mapping Phase Gain Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
13.5.12 Setting the Fluxscale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
13.5.13 Deriving the Fluxes of the Phase and Bandpass Calibrators . . . . . . . . . . . . . . . . . 167
13.5.14 Time Gain Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
13.5.15 Applying the Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
13.5.16 Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
13.5.17 Exporting the Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
13.6 Low SNR Heuristics in Interferometric Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . 168
13.6.1 Mapping the Gain Solutions from Broad Spectral Windows to Narrow Ones . . . . . . . . 168
13.6.2 Using the Gain Solutions Obtained from the Aggregate of all Spectral Windows . . . . . . 169
13.6.3 Additional Bandpass Pre-averaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.7 Total Power Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.7.1 Data Import . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.7.2 Deterministic & Manual Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
13.7.3 Tsys and Sky Calibration Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
13.7.4 Kelvin-to-Jansky Calibration Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
13.7.5 Applying the Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
13.7.6 Automated Line Identification and Baseline Subtraction . . . . . . . . . . . . . . . . . . . 170
13.7.7 Baseline Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
13.7.8 Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
13.7.9 Exporting the products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
14 Data Archiving
173
14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
14.2 Data Flow and Archive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
14.3 PI Data and Data Delegation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
14.4 Archive Query . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
14.5 Request Handler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
A Antennas
177
A.1 Design and Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
A.2 Antenna Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
A.3 Antenna Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
A.4 Cryostat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
A.5 Amplitude Calibration Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
A.5.1 Atmospheric Calibration Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
A.6 Water Vapor Radiometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

CONTENTS

7

B The LO and IF System
189
B.1 Functions of the LO & IF system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
B.2 Summary of Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
B.3 Frequency Generation and Distribution in ALMA . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
B.3.1 Reference and LO signal generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
B.3.2 LO1 signal generation and distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
B.3.3 Line length corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
B.3.4 The First Local Oscillator (LO1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
B.3.5 LO2 and the IF processor units and IF switch . . . . . . . . . . . . . . . . . . . . . . . . . 196
B.3.6 Digitization and signal transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
B.4 Other functions of the LO/IF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
B.4.1 Delay corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
B.4.2 Sideband suppression - LO offsetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
B.4.3 Sideband separation - 90 degree Walsh switching . . . . . . . . . . . . . . . . . . . . . . . 199
B.4.4 Interference rejection - 180 degree phase switching . . . . . . . . . . . . . . . . . . . . . . 199
C Calibration Sources
201
C.1 ALMA Catalog Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
C.2 Phase Calibrator Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
C.3 Bandpass Calibrator Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
C.4 Other Calibrator Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
C.4.1 Absolute and Relative Flux density Calibration . . . . . . . . . . . . . . . . . . . . . . . . 204
C.4.2 Polarization Calibrators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
C.4.3 Astrometric Calibrators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
C.4.4 Check Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
D Acronym Dictionary

207

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 4 operations will include standard and non-standard observing modes. Non-standard modes areobserving modes that are less well characterized for which the data cannot be processed by the pipeline andneed to be reduced manually by ALMA staff. Up to 20% of the PI observing time in Cycle 4 will be allocatedto proposals requesting non-standard modes. Users should refer to Appendix A (Capabilities) in the ALMA
Cycle 4 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 its limitation of the Cycle
4 setup for ALMA users, to a deeper level than what is described in the ALMA Early Science Primer. It should,
however, not be necessary to use the Technical Handbook to prepare an ALMA proposal.
The handbook is divided in 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 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 4. 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 4 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 4 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 pipeline in data calibration.
Chapter 14 describes how the data are stored, the data flow and the ALMA archive.
The Technical Handbook concludes with a number of Appendices, which contain supplemental material
about concepts and hardware, such as the antenna, transporter (Appendix A), LO system (Appendix B), andthe calibrator source selection algorithm (Appendix C).

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

Chapter 2

Array Components
In this chapter we describe the main characteristics of each ALMA array. Unless otherwise noted, the description
is appropriate for the fully completed ALMA.

2.1

The ALMA Telescope

Upon completion, ALMA will be composed of 66 high-precision antennas. Fifty of these antennas will be 12meter dishes in the 12-m Array, used for sensitive, high-resolution imaging. These will be complemented by the
Atacama Compact Array (ACA or Morita-san 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 4, ALMA will cover most of the wavelength range from 3.6
down to 0.32 mm (from 84 to 950 GHz in frequency), and when ALMA is completed the coverage will be from10 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 software 3 (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 see
Appendix 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 4) will be published in the Capabilities section of the document
ALMA Proposer’s Guide. Complementary background information on ALMA and its capabilities for Early
Science can be found in the document A Primer for Early Science. Both documents can be found on the link
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

http://www.almascience.org/documents-and-tools/.

Figure 2.1: The ALMA 12-m Array in its compact configuration (left hand-side of the image). The ACA with
all CM (dashed-orange circles) and 4 PM antennas (blue circles) are distributed in the right hand side of theimage (highlighted). A few unoccupied stations can be seen, to which antennas of the 12-m Array can be movedby 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 backend 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 those 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 (Section B) are transmitted to the antennas on optical fibres 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 sub-sections of the 12-m Array (e.g., two ‘sub-arrays’) can
simultaneous independent observations. Please note that the sub-arrays feature of the 12-m array is currently
being developed and tested and is not yet a capability that is offered for Early Science observations. The 8 GHz
total IF bandwidth from the selected receiver is divided into four 2 GHz-wide basebands which are digitized atfour Gsamples/s, with three-bit resolution, and transmitted on optical fibres (B). Total data rates are therefore
96 Gbits/s per antenna. With formatting, the bit rate is 120 Gb/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 correlators. The
64-input Correlator (Section 5.2) 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.

2.3. THE ATACAMA COMPACT ARRAY

13

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 modes. The correlated data are fed to a group of processors which do thetransforms 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 or Morita-san 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 0m up to 12m spacings as auto-correlations. The 7-m Array samples baselines from 9m to 30m,
bridging the baseline sampling gap between the 12-m Array and the TP Array. The number of array elements
available is published for each observing cycle.
The ACA is controlled via control software developed on the ALMA Common software (ACS) and is operated
in a similar fashion to the 12-m Array. To achieve this unified operation, the ACA system is as compatible withthe 12-m Array as possible at the level of hardware, interface, data, and observing modes. When ALMA iscomplete, the standard observing modes for the TP Array will 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 andauto-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 (A). Similar to 12-m Array antennas, each antenna contains one front-end, including a cryostat,
amplitude calibration devices, and one backend. Unlike the antennas of the 12-m Array, the 7-m antennas 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., from inside
the AOS building.
The ACA Correlator is normally used for the ACA, and can work with two sub-arrays. It is an FX correlatorr(Fourier transform first, then cross-correlate) with 3−bit input and 4 bits in the correlation. The correlator
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

CHAPTER 2. ARRAY COMPONENTS

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 GB/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 are designed to fill missing spacings in from about
9m to ∼30m (Chapter 7). Each cartridge (Chapter 4) receives two orthogonal polarizations.

2.3.2

The TP Array

The TP Array can fill in baseline coverage from 0m to about 12m, 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 antennas will be fitted with a nutating subreflector (also known as
wobbler or chopper) in full operations, but is not yet employed. The ALMA nutator is a single axis device,used to alternatively point the primary beam of the antenna between two defined sky positions by tilting thesubreflector along the azimuth direction, at constant elevation. A modulation of the observed signal at a wellknown frequency is introduced by rapidly switching between the celestial source and a nearby reference position.
A synchronous demodulation technique is then used to extract the flux of the source. This method can greatly
improve the quality of single dish observations by suppressing atmospheric and noise components at frequencies
lower than the nutator frequency.
The TP Array is usually connected to the ACA Correlator, but its antennas can also be connected to the 64input Correlator and used for cross-correlation. The call materials describe the observing mode 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 Morit, 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, we describe the principles and concepts behind interferometry, so that ALMA users
can plan and understand their observations better. If more information is desired, the topic of interferometry
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.
We first provide 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 thanpossible with a single antenna. The interference modifies the angular sensitivity of the antennas to include asinusoid of constructive and destructive nodes. In this sense, the only emission measured by the interferometeris 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 two antennas.
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 tothe 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.
In the following, we expand upon these basic ideas. We begin by introducing the concepts of basic radio
astronomy, and then move 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, we define brightness, or equivalently specific intensity, Iν , 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 thatboth modes of polarization can be detected simultaneously.) As with all telescopes, antennas bring incident
EM power to a focus after reflecting it off a primary surface. The antenna response, i.e., its sensitivity, is asummation 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, we have described an idealized antenna. Actual antenna power response can be altered by19

3.3. VISIBILITIES AND APERTURE SYNTHESIS

various effects, including the degree by which the secondary is illuminated, diffraction by the arms supporting
the secondary, 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), we can define Iν (θ, ϕ) andPN (θ, ϕ) 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. In this section, we build on the concepts introduced
previously to discuss aperture synthesis in more detail.
Earlier, we described how a plane-parallel wavefront arriving on-axis to an antenna is brought to a focus
by a parabolic surface. 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, we can rewrite the expression for received

20

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

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

(3.9)

Next, we can further rewrite this expression in terms of the sums of element pairs which are the same and thosewhich 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, we see that 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 thecontributions 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. We can measure this distance in units of the observing wavelength, λ. In terms of familiar units oflength, 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, we can describe a small angle from the axis 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, we can consider all distances in our 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, we can introduce β, a direction on the sky orthogonal to α. Also, we definem = sin β as the small angle analog to l in this new direction, and v = b cos ϕ where ϕ is the angle of the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.
position so on the sky from the reference position orthogonal to θ. Finally, we define y as the extra path length
introduced in this new direction, in units of the wavelength of emission, i.e., y = v sin β = vm. With thesechanges, the two-dimensional voltage response of antenna 2 is:V2 = V1 e2πi(ul+vm) .

(3.12)

We identify u and v 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, we identify l and m 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 thephase 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 Ä are incoherent, the time
averages of the correlation of those signals will be zero. Thus, the product of the integrals in Equation 3.13 canbe 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 we have described an interferometer with idealized antennas. 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.
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. We can then characterize the sampling distribution 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, we can rewrite Equation 3.24 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 we have been speaking generally about true sky brightness distributions so far, a special note should
be made for the 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 ofthe dirty beam (e.g., see Equation 3.25). Moreover, the complex visibilities of the point source have the same

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.)
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 we 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
how the interferometer antennas are arranged in configurations. In general, distributions connected through a

26

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

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 centre 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 we use 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 dataobtained in multiple configurations, where more extensive coverage of the uv-plane is attained. For example, the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

same 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, we end this Chapter 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, we 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, we see 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 4, Band 3, 4, 6, 7, 8, 9, and 10 are available (see available frequency and wavelength ranges forthese bands in Table 4.1). The receivers are described in more detail in the following sections as well as in thereferences listed in Table 4.2.

Figure 4.1: The ten ALMA receiver bands. Receiver bands for Cycle 4 are shown in red superimposed on a
zenith atmospheric transparency plot at the AOS for 0.5 mm of PWV.
The ALMA receivers in each antenna are situated in a single frontend assembly (see Appendix A, Section
A.4). The frontend assembly consists of a large cryostat containing the receiver cold cartridge assemblies(including SIS mixers and LO injections) and the IF and LO room-temperature electronics of each band (thewarm cartridge assembly, WCA). The cryostat is kept at a temperature of 4 K through a closed cycle coolingsystem. The Amplitude Calibration Device(ACD) is mounted above the frontend (see Appendix A.5). Each

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
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

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
6
7
8
9
10

Table 4.1: Receiver Characteristics. 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 thetwo 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 autocorrelationnoise performance is degraded by a factor of up to about 1.5 below 5.5 GHz (Section 4.2.3) 4. Maximum
instantaneous IF bandwidth: As both upper and lower sidebands both pass through the same IF bandwidth
but are subsequently separated, the effective signal bandwidth given in this column for 2SB receivers is twice
the actual IF filter bandwidth. In addition, this is per polarization, so the total effective bandwidth for each
receiver is then another factor of 2 higher. Note that the effects of the anti-aliasing filters have been included(see Section 6.4). 5. In future Cycles, the maximum bandwidth will 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.4.3). 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 real 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
B6
B7
B8
B9
B10
Optics
WVR

Claude et al. 2008
Asayama et al. 2014
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)
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
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

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, dependingon the optimum technology available at the different frequencies; each receiver is described in more detail inthe sections below.
To avoid overloading the cryostat cooler, only three bands can be switched on at a time. From a hardware
point of view, it takes only about 1.5 seconds to switch between these bands, but in reality, switching between
phase calibrator and science source can take up to three minutes. For bands that are not switched on, the time
to fully thermally stabilize a receiver from an off state is up to 60 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. This 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 0-2 GHz in order to send
the signals to the correlator. The frequency down conversion involves a set of Local Oscillators (LOs). The LO
and Intermediate Frequency (IF) systems are described in detail in the Appendix (B).
The frontend 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, 7, and 8 have an output
range of 4–8 GHz, Band 6 a range of 6–10 GHz and Band 9 and 10 a range of 4–12 GHz (Table 4.1). The
possible sky frequency ranges covered by each receiver with the first Local Oscillator (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 . This is illustrated in Figure 4.2. Note that the maximum IF bandwidthin Table 4.1 may be a few percent less than the IF range in Table 4.1 (see Section 6.4).

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

4.2

The Cycle 4 Receivers

The Band 3, 4, 6, 7, and 8 receivers are dual sideband (2SB) receivers, where both the upper and lower sidebands
are provided 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 (reduced to aneffective 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 noisein the unwanted sideband, but not adequate for suppressing astronomical signals 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, which depend on the antenna, such that the signals from two antennas in theimage sideband do not correlate.
The Band 9 and 10 receivers are double sideband (DSB) receivers, where the IF contains noise and signals
from both sidebands. They only have two outputs, one per polarization. However, the IF effective bandwidth is
7.5 GHz per sideband (after passing through the IF processing units), so the total instantaneous bandwidth is
the same as Bands 3, 4, 6, 7 and 8. In Cycle 4, only one sideband per spectral window is correlated, and the otherrejected using LO offsetting, as mentioned above. This does not remove the noise from the rejected sideband.
The noise of the sideband that is kept twice that of the DSB noise level. In the future, suitable phase switching
will be introduced in the correlator, and both sidebands can be correlated and processed independently, thus
doubling the effective system bandwidth.
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 4 RECEIVERS

4.2.1

35

Band 3 ReceiverBand 3 is the lowest frequency band available in Cycle 4, 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 two linear
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 cold optics, OMT, SIS mixers and the 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 specification for the Band 3 receiver noise performance (Trx ) is <41 K at LO=104 GHz, and <45 K for
any other valid LO setting.The atmospheric transmission over most of Band 3 is very high, even with a large
PWV (Figure 4.6) which means observations in Band 3 can, in principle, take place with 10 mm or more of
PWV. The resulting system temperature (Tsys ) shows the expected rise at the higher end, due to an atmospheric
oxygen line (Figure 4.7).

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 4 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 ortho-mode-transducer (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 Trx ). However, the performance ofthe receiver is considerably better than 50 K over the band. The resulting system temperatures (Tsys ) for 1.262
mm PWV are shown in Figure 4.11.

4.2. THE CYCLE 4 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. Note the single feedhorn which feeds the OMT, splitting the two polarization signals forthe 2SB SIS mixers. The Band 4 cartridges are 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: Typical 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-overor background terms have been included. Temperature is given in Kelvin.)

4.2. THE CYCLE 4 RECEIVERS

4.2.3

41

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 4.12). A single
feedhorn feeds an ortho-mode-transducer (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, isshown in Figure 4.13.

Figure 4.12: 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 blocker. Note the slightly inclined inner window, designed tominimize standing waves.
The Band 6 IF frequency has been chosen to allow for multiple simultaneous line observations1 ; it now covers
the range 5.0–10.0 GHz. There is ∼10-25% excess noise below 5.5 GHz due to LO1, however this multi-transition
setup is still considerably more efficient than observing each line separately. However, it is recommended thatfor 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 4.14 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 <138 K
over the whole band (SSB Trx ). The measured results are considerably better, typically 50 K over most of theband. The resulting system temperatures (Tsys ) for 1.262 mm PWV are shown in Figure 4.15.

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

42

CHAPTER 4. RECEIVERS

Figure 4.13: 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 4 RECEIVERS

43

Figure 4.14: 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 4.15: 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.)

44

4.2.4

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 4.16).
A block diagram of the Band 7 receiver, including the cold cartridge and warm cartridge assembly, is shown in
Figure 4.17.

Figure 4.16: 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 4.18 for three typical PWV values. The specification of the Band 7 receiver noise temperature is Trx <147 K over 80% of the range and <221 K over the wholetuning 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 is considerably better than this. The resulting
system temperatures (Tsys ) for 1 mm PWV are shown in Figure 4.19. 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.

4.2. THE CYCLE 4 RECEIVERS

45

Figure 4.17: Band 7 frontend receiver block diagram, and (right) annotated image of the Band 7 cartridge. Notethe polarization-splitting grid and LO injection in the cold optics above the mixers. The Band 7 cartridges werebuilt at IRAM in France.

46

CHAPTER 4. RECEIVERS

Figure 4.18: 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 less prominent absorption feature at 369
GHz is due to oxygen.

Figure 4.19: Typical Tsys at zenith for Band 7 with PWV=0.913 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 4 RECEIVERS

4.2.5

47

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 ortho-mode-transducer (OMT) which splits the two linear polarizations and feeds the 2SB
SIS mixers (Figure 4.20).

Figure 4.20: Optical layout of the Band 8.
A block diagram of the Band 8 receiver, including the cold cartridge and warm cartridge assembly, is shownin Figure 4.21. 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 4.22 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 thewhole tuning range. However, the performance of the receiver as measured in the lab is considerably better
than this. The resulting system temperatures (Tsys ) for 0.472 mm PWV are shown in Figure 4.23.

48

CHAPTER 4. RECEIVERS

Figure 4.21: 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 are constructed at the Advanced Technology Center (ATC).

4.2. THE CYCLE 4 RECEIVERS

49

Figure 4.22: 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 4.23: Typical Tsys at zenith for Band 8 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.)

50

4.2.6

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 4.24).

Figure 4.24: 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. In Cycle 4, LO offsetting is used
to reject 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 toa high fringe rate so that the signal is smeared over a larger bandwidth increasing noise incoherently. 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 andwarm cartridge assembly, is shown in Figure 4.25.
The Band 9 atmospheric transmission is significantly dependent on the PWV, as illustrated in Figure 4.26
for 3 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, and Figure 4.27 shows the
expected Tsys for 0.472 mm of PWV, over most of the band given the expected receiver noise. Phase stability
also limits when observations can be made. Therefore, most observations in Band 9 will be done at night
during austral winter. As well as having a lower atmospheric transmission and a less stable atmosphere, Band
9 observing provides several challenges for observing: finding sufficiently bright calibrators (most QSOs are
relatively faint at this frequency), requiring accurate pointing for the relatively small primary beam, and theneed for the highest level of stability in the rest of the system.

4.2. THE CYCLE 4 RECEIVERS

51

Figure 4.25: 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 Band 9 receiver was built at SRON in
the Netherlands.

52

CHAPTER 4. RECEIVERS

Figure 4.26: Band 9 zenith transmission for PWV = 0.2, 0.5 and 1 mm. Frequency is in GHz.

Figure 4.27: 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 4 RECEIVERS

4.2.7

53

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 frontend 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 4.28). 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 4.29.

Figure 4.28: Schematic of ALMA Band 10 optics. ALMA Band 10 optics is 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 4.30
for 3 low values of PWV. Figure 4.31 shows the expected Tsys for 0.472 mm of PWV, over most of the band
given the expected receiver noise. Phase stability also limits when observations can be made. Therefore, mostobservations in Band 10 will be done at night during austral winter. As well as having a lower atmospherictransmission and a less stable atmosphere, Band 10 observing provides several challenges for observing: finding
sufficiently bright calibrators (most QSOs are relatively faint at this frequency), requiring accurate pointing forthe relatively small primary beam, and the need for the highest level of stability in the rest of the system.

54

CHAPTER 4. RECEIVERS

Figure 4.29: 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 are constructed at theAdvanced Technology Center (ATC).

4.2. THE CYCLE 4 RECEIVERS

55

Figure 4.30: Band 10 zenith transmission for PWV = 0.2, 0.5 and 1 mm. Frequency is in GHz.

Figure 4.31: 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.)

56

CHAPTER 4. RECEIVERS

Chapter 5

The Correlators
A correlator is a virtual focal plane of an interferometer array. It accepts voltage-based signals from individual
antennas, calculates cross correlations and auto-correlations of them for each pair of antennas, and producescomplex visibilities that users will reduce to synthesize images. The correlator also provides pre-correlation
delay and phase tracking functions to adjust the response to the wavefronts of received signals in order tomaintain the coherence of the complex visibilities. Walsh-switching modulations for sideband separation (90◦switching) and spurious-signal suppression (180◦ switching) are demodulated in the correlator1 , too.
All signals received by ALMA antennas are processed in one of two correlators: the 64-input Correlator (alsoknown as the Baseline Correlator) and the ACA Correlator. The 64-input Correlator is used primarily for themain 12-m Array, while the ACA Correlator is used for the Morita Array which forms 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 usedwith 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 4 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◦ switching is modulated in the LO1 and demodulated in the digitizers. See also Section A.7.3
and Emerson 2005, ALMA memo No.537.
2 Crossbar switching allows for some flexibility in this arrangement.

57

58

CHAPTER 5. THE CORRELATORS

5.1

The 64-input Correlator

The 64-input Correlator employs hybrid design, also known as the 3 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 4 quadrants, all of which are available for Cycle 4. Each quadrant can handle a 2-GHz
dual-polarization BB for up to 64 antennas4 . The full set of 4 quadrants is capable to accept 4 BBs to cover
total 8-GHz bandwidth with a dual polarization.

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

One baseband
polarization pair
32-parallel outputs x 2-bits
per sample x 2-polarizaitons

Correlator station electronics

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 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-bit per sample (see
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

59

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
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 – see Section 6.4.

5.1.2

FDM mode

FDM is adequate for spectral-line observations that require a spectral resolution higher than that achieved
with TDM. Each 2-GHz BB is split into 32 62.5-MHz sub-bands in a TFB card where digital filtering, digitalmixer and LO (LO4) are implemented in Field Programmable Gate Arrays (FPGAs). The digital signal isre-quantized in the last stage of the TFB card which delivers 2-bit (4-level) samples7 at the Nyquist sample
rate of 125 MHz. The sub-bands are trimmed by 15/16 to avoid aliasing and band-edge filter responses, andare set at intervals of 58.59375 MHz. The correlator stitches together multiple sub-bands to output a seamless
15
cross power spectrum to form an SPW with 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 of valid sub-bands to form an
5 An SPW is a contiguous spectrum whose frequency channels are uniformly spaced. 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.
7 Although the TFB card can deliver 2- or 4-bit samples after requantization and accepts 3-bit samples, the cross-correlation
processor accepts only 2 bits in Cycle 4. See also Section 5.3.

60

CHAPTER 5. THE CORRELATORSSPW is selectable from 32, 16, 8, 4, 2, or 1 to cover 1875, 937.5, 468.75, 234.375, 117.1875, and 58.59375 MHz,
respectively. It is capable to have multiple (up to 4) SPWs in the same BB. While different spectral setups canbe set for SPWs in different BBs, all of SPWs in the same BB must have the same channel spacing.
The center frequency of each SPW can be tuned over the 2 GHz-wide BB using the digital LO (LO4) inthe 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 firmware in the TFB FPGAs. 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 antennas8 . There is a maximum of 8192 spectral points available with one BB being
processed per quadrant thus providing high spectral resolution in FDM with narrower bandwidth than 2 GHz.
It is possible to set different modes in different quadrants (i.e. BBs); for example, while one BB 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 over a dump period is performed in the CDP (Correlator Data Processor)
computers. See also Section 5.5.3 about time resolution. Section 5.5 describes in detail the correlator dataprocessing.

5.2

The ACA Correlator

The ACA Correlator is dedicated to observations with the Atacama Compact Array (ACA - Morita Array)that consists of the 7-m Array with twelve 7-m antennas and the Total Power Array (TP Array) with four12-m antennas. The ACA Correlator is based on the FX 9 design in which the incoming time-domain data
stream is converted into frequency-domain spectrum via an FFT (Fast Fourier Transform) module before crossmultiplication to form the power spectrum. The FFT part always accepts a full 2-GHz bandwidth and outputs
524288-ch spectra with 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, afrequency profile synthesis (FPS) is performed in the Correlator Data Processor (ACA-CDP) computer so thatthe outputs of both correlators are matched (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 performs the
220 -point FFT that produces a 219 -point complex spectrum10 (hereafter, voltage spectrum) for every BB per
antenna, with a channel separation of 3.815 kHz (= 2 GHz ÷ 524288 ch) 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 andIntegration 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
8 2016 cross-correlations (real and imaginary) and 64 auto-correlations (real) totals 4096 real correlations.
9 F and X stand for Fourier transform and correlation, respectively.
10 220 -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

61

Figure 5.3: Block diagram of in the ACA Correlator. One of four quadrants is shown. Time-series data fromeach antenna 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.

62

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
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 (§5.6.2), FPS andtemporal 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
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 be combined with those of the main array, thesevisibilities must be homogenized in terms of amplitude, phase, and spectral specifications. While amplitude
and phase calibrations refer to standard flux and phase calibrators offline, the spectral profile will be matched
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 the 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
auto-correlations of XX and Y Y . Cross-polarization products are not taken in Cycle 4. Single-dish dedicatedobserving 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 4.

5.2. THE ACA CORRELATOR

63

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 frequency range of an SPW is selectable fromthe 524288-point (512K) spectra across 2-GHz bandwidth. Additional channel-averaging within the selected
frequency range before output.

64

5.3

CHAPTER 5. THE CORRELATORS

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 equipped in the antenna back ends (BEs) to convert BB
signals into the ALMA digital format (Freund 2002, ALMA Memo No.420). The Digital Transmitter (DTX)on the BE transfers the digital signals through optical fibers to the data receivers (DRXs) in 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 thequantization levels to 4 (2-bit). The ACA Correlator handles 3-bit digital form in FFT and the spectrum isrequantized in 4-bit before cross multiplication. These quantization processes affect the sensitivity and linearity
in the power spectra. The the 64-input correlator yield sensitivity loss of 12% (TDM) or 15.5% (FDM) due tothe quantization, while the ACA Correlator does 4.8%, compared with an ideal analog system. 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 4 (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 pathlength fluctuation for each dump duration(online correction). This online corrected data is currently used for QA0 checks, but online WVR correction may
eventually enable longer time-integration of the visibilities (thus slower output data rates) whilst maintaining
coherence.
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1I
 Q  1  cos 2ψ U  = 2  sin 2ψ
0V0− sin 2ψcos 2ψ
−i0− sin 2ψcos 2ψ
i1hXX ∗ i /(GX G∗X )∗∗− cos 2ψ   hXY ∗ i /(GX G∗Y )  ,− sin 2ψ   hY X i /(GY GX ) 0hY Y ∗ i /(GY G∗Y )(5.1)

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 8.
The 64-input Correlator forms cross-polarization products of hXY ∗ i and hY X ∗ i only when polarimetry is
required. Although the ACA Correlator is capable of polarimetry, the cross-polarization products of the 7-m
Array or the TP Array observations will not be offered for Cycle 4.

65

5.5. CAPABILITIES OF THE CORRELATORS

5.5.2

Spectral Setup

Both correlators are capable of accepting eight 2-GHz-bandwidth signal streams consisting of four BBs andtwo polarizations, and to output multiple SPWs within the bandwidths. Each SPW corresponds to a continual
spectrum composed by uniformly-spaced spectral channels. Table 5.1 summarizes the spectral performances of
the correlators. See also Chapter 6 about multiple-SPW setup.
Correlator/Mode
TDM
FDM
FDM
FDM
FDM
FDM
FDM
ACA
ACA
ACA
ACA
ACA
ACA

Bandwidth(MHz)

Max. number of ch.
for dual parallel pol. (XX and Y Y )Ch. spacing
(MHz)

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

Table 5.1: Correlator modes and spectral performances per BB for dual parallel polarization (XX and YY).
For full-polarization observations (XX, XY , Y X, and Y Y ), the maximum number of spectral channels per
SPW becomes half and then the channel spacing is doubled. TDM and FDM stand for the Time Division Modeand Frequency Division Mode of the 64-input Correlator . The bandwidth and the number of channels in the
ACA correlator became to remain unchanged through FPS (Frequency Profile Synthesis) since Cycle 4. NOTE:
The channel spacing is not the same as the spectral resolution because of the applied weighting function. See
table 5.2. * Usable bandwidth except 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 theweighting 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 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 functions11 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.
Channel averaging is available to bin or average spectral channels in the CDP. Channels can be averaged
together; factors of N = 2, 4, 8, or 16 are available. The main purpose is to reduce the data rate to the archiveand the total data volume. It provides a broader spread of correlator functionality between the current 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) for different values
11 For a full description, see http://mathworld.wolfram.com/ApodizationFunction.html.

66

Uniform
Hanning
Hamming
Bartlett
Blackmann
Welch

Weighting

FWHM (ch)Max sidelobe

1.21
2.00
1.82
1.77
2.30
1.59

−0.217−0.026+0.007+0.047+0.001−0.086

0.6

Uniform
Hanning (default)
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

Table 5.2: Spectral resolutions (FWHM) and the
maximum sidelobe levels for different weighting
functions.

of N , using Hanning weighting, in the different bandwidth modes. The channel spacings are in parentheses.
N = 1 is the default unbinned case, where the resolution is 2× the channel spacing.
Usablebandwidth(MHz)

N=
Channels =

1875
937.5
468.8
234.4
117.2
58.6

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 (3906)
1952 (1953)
976 (977)
488 (488)
244 (244)
122 (122)

16
240
7813 (7813)
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 channel averaging factors (columns, N = 1 to 16), using Hanning smoothing. The number of channels can be reduced from 3840 (for the un-averaged case, N = 1) down to 240 (forN = 16). As N increases, the spectral resolution functions of adjoining channels are combined and then the
spectral resolution approaches to the channel spacing. Values are given for the 2-polarization case.
Note that the default Hanning window function gives a resolution 2 time 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 is a
non-reversible operation!
The ACA Correlator is an FX correlator where the uniform weighting in the FFT segment is equivalent of
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
became to remain unchanged through FPS since Cycle 4.

5.5.3

Time Resolution

As shown in Figure 5.8 the correlated data are processed in the CDP and accumulators before being archived.
The is limited by the shortest integration period in the correlators and also the maximum data dump rate. The
data dump rate, Rd , given by2
Rd = Nant
× NBB × Nch × Nbyte /Tint , (bytes/sec)

(5.2)

67

5.5. CAPABILITIES OF THE CORRELATORS

must be lower than the acceptable data rates described below. Here, Nant , NBB , Nch are the number ofantennas, BBs, and spectral channels (sum of polarization products), respectively. Nbyte (bytes/visibility) isthe byte size of the real or imaginary part of a visibility. Tint is the integration time in the correlator. Typically,a configuration of Nant = 42, NBB = 4, Nch = 3840 × 2 polarization products (XX and Y Y ), Nbyte = 2 andTint = 6 sec yields 18.1 Mbytes/sec, that is within the acceptable data rate of the 64-input Correlator. The
ALMA Observing Tool (OT) estimates the data dump rate for each science goal. It is required to consider
the optimal trade-off between time resolution, spectral resolution, polarization, number of BBs, and number ofantennas.

Correlator
Acuumulator#1
Transfer data
every dump time

WVR data
once per second

CDP
Accumulator#2
Truncate channels,
take average

Accumulator#3

BDF

BDF

Transfer data every
channel-average duration

Transfer data every
integration duration

Channel-averaged data

Spectral data

Archive

WVR data

Figure 5.8: Basic data processing and accumulation steps between the correlator and archive. The CDP applies
WVR correction before time integration of the spectral data and channel-averaged data. The set of WVR,
channel averaged data, and spectral data are packed in Binary Data Format (BDF) and archived.
Pulsar-gating function is not implemented in the ALMA correlators. Timing-sensitive analysis must be
taken offline under the time resolution limited by the condition of the integration duration.
• Integration duration of spectral data with the 64-input Correlator
The correlator dump time is 32 ms and 48 ms for TDM and FDM, respectively, and the integration
duration of spectral data in the CDP must be a multiple of the dump time. And the data rate must
accommodate the maximum data rate. Although the specification of the maximum data rate from the64-input Correlator is designed to be 62.5 Mbytes/s, it is regulated at 40 Mbytes/s in Cycle 4. The
64-input Correlator employs Nbyte = 2 where the real or imaginary part of the visibility is expressed witha 2-byte integer.
• 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 autocorrelation and cross-correlation, respectively. The maximum data rate from the ACA Correlator is 3.6
MB/s, independent of the number of antennas. However, the average data rate to the archive will belower during typical observing modes, because of overheads and the use of TDM in calibration scans.
• Integration duration of online WVR Correction

68

CHAPTER 5. THE CORRELATORS

When on-line WVR correction is employed, the integration duration of the 64-input Correlator must be
equal or longer than that of the WVR system, which is 1.152 sec. For Cycle 4, neither the 7-m Array nor
the TP Array uses online WVR.
• Channel-averaged duration
The average of power spectra across whole spectral channels in each SPW can be recorded in another
SPW with a channel-averaged duration that must be multiple of the correlator dump time and must be
equal or shorter than the integration duration of the WVR. This single-channel SPW, without bandpass
calibration, is not used for astronomy, but for recording time variations of phases and amplitudes.

5.6

Practical Performance

5.6.1

Sensitivity

Quantization in a digitizer diminishes information contained in the input analog signals and causes a sensitivity
loss. The ALMA digitizer employs 3-bit (8-level) quantization12 , and additional re-quantization processes areapplied in the correlators.
In Cycle 4, 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)13 .
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 loss of 4.8% (i.e. ηQ = 0.952; Kamazaki et al.
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 frequency band near atmospheric absorption lines) canviolate 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)
are known as the Van Vleck relationship, which is used for the non-linearity correction.
Figure 5.9 shows the Van Vleck relationships in 2-, 3-, and 4-bit quantizations. The correlation coefficientsof quantized signals keep adequate linearity for small correlation coefficients14 . 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 the both correlators, the CDPs measure total power ofdigitized signals and determine the Van Vleck relationship to correct the (cross) power spectra.
12 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).
13 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.
14 The departure from linear relation is δρ/ρ < 10−3 for ρ < 0.2

69

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

0.8

1.0

Analog Correlation Coefficient

0.0

0.2

0.4

0.6

0.8

1.0

Analog Correlation Coefficient

Figure 5.9: Van Vleck relationship of 2-, 3-, and 4-bit quantizations at the optimal signal power level and threshold 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 factor of η4 = 0.881,
η8 = 0.963, and η16 = 0.988 for 2-, 3-, and 4-bit quantizations, respectively.

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 into data structures called SPectral Windows (SPWs). All of thedata 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 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,
each requested spectral window maps into two output SPWs in the data: one with the requested dimensionsof 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 areused by the on-line telescope calibration system (TELCAL) and for real time diagnostic purposes (QuickLook),
and are typically not used downstream in the data reduction. Overall, this can lead to ASDMs with a large
number of 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.

70

CHAPTER 5. THE CORRELATORSChapter 6

Spectral Setups
In this chapter we describe the frequency setup of ALMA. In particular, we show how to define the spectral
setups from the user viewpoint and how these set the ALMA hardware. We summarise the local oscillator (LO)and Intermediate Frequency (IF) systems and the various functions that they perform, as well as some of theother points pertaining to the frequency setup. For those interested in more details of the LO & IF components
and how the hardware works, please jump to Appendix B.
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 to worry about the details ofeach hardware setting. For full details of the OT and how to use it, see the user manual and reference manuals,
available from the ALMA website1 (and also in the OT itself).

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,
the signals of frequency fsig are mixed to IF signals of frequency fIF using a Local Oscillator (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 may correspond to an input frequency above or below 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 downconvert the astronomical signal to 4GHz- to 8GHz-wide IF bands (bothUSB 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 these basebands it ispossible to place, in principle, up to 32 spectral windows (although in practise it is unlikely that more than
4 will be used per baseband). Each Spectral Window forms a final contiguous spectrum, with bandwidths in
FDM mode from 58.594 MHz up to 1.875 GHz wide (see Section sec:ubw).
Using the OT during both proposal preparation by the PI (Phase 1) and scheduling block (SB) creation by
ALMA staff (Phase 2), the user chooses the frequencies (or spectral lines) to be observed in each SPW and theirrequired bandwidths or spectral resolutions. During the spectral tuning, there are effectively four different LOs
used by the system (Figure 6.1):• LO1 which sets the frontend tuning frequency• LO2 which positions the basebands within the frontend receiver IF (each baseband uses a different LO2,
1 http://almascience.org/documents-and-tools/

71

72

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 fibres.
See Appendix B for a more detailed description of the components and the other tasks that the LO systems
perform.
hence there are four LO2s)• 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 synthesised in thecorrelators allowing positioning of the spectral windows within each baseband. Each SPW has effectively
a separate LO4
The OT and the realtime system have a tuning algorithm that attempts to find the best tuning solution
for LO1, 2 and 4 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. If no solution is possible, the OT will notify the user. A more detailed description of the LO
operation is given in Section B.2. Cycle 4 has similar restrictions on the spectral setups and tuning as Cycle 3(see Table 6.2 in section 6.8). The main limits are that the edges of the 2 GHz basebands cannot lie outside thereceiver tuning range listed in Table 4.1, and the edges of the (untruncated) spectral windows cannot lie outside
the 2 GHz-wide basebands 2 . The settings of each baseband in the correlator are independent, so the bandwidth,
resolution and correlator mode as well as the value of LO4 can be different for each baseband. For example, it
is possible to have a 58 MHz-wide SPW centered on a particular line in baseband 1, and simultaneously use abroadband time division multiplexing mode (or TDM mode - see correlator chapter) for all the other basebands.
Cycle 4 also allows for multiple FDM spectral windows within each baseband, described in Section 6.3.2 below;
2 Actually in Cycle 4 the system allows for a small overhang of the spectral windows, to enable differential Doppler corrections
to be made at runtime; ie slight differences in the Doppler correction for different SPWs.

73

6.2. FREQUENCY DEFINITIONS

however, currently the bandwidth of all the 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
is commonly set to the local kinematic standard of rest (LSRK), which is the conventional local standardof rest based on the average motion of the Sun with respect to the solar neighborhood.
Center Frequency (Sky) This is seen in the OT Phase 1, and is the actual central frequency of the SPW in
the local ALMA (ie 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 (ie the extra velocity from
Earth rotation and orbit) as this is not known until actual runtime. For example, for a source of radial
velocity 100km/s in the LSRK frame, the difference between rest and sky frequency in the OT will be theequivalent of 100km/s. At runtime, the extra velocity from the Earth orbit and rotation (up to ±28km/s
and ±1km/s), plus the motion of the LSRK (20.0 km/s toward RA=18 hrs, δ =30 ◦ for epoch 1900.0) are
included.
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, fSP W , is given in terms of this and Baseband Center Frequency by:
fSP W = fBB ± (fof f set − 3.0GHz)(6.1)

where the sign depends on the observing sideband.
Note that in certain circumstances (e.g. with complex tuning setups having multiple SPWs per baseband see below) it may not be possible to set the requested center frequencies to exactly the center channel in all the
SPWs. This is because of limitations in the tuning of the LOs. However, the tuning software will keep these
offset to a minimum, and in any case they will be a small fraction of the SPW bandwidth. See section B.2 formore details.

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 theBand 6 combination given). When <4 spectral windows are required for the primary lines, the others can be
set up to cover fainter lines or to observe the continuum, potentially in TDM mode. 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 in these SPWs (i.e. 1.875 GHz in FDM, or TDM– see Section 6.4). Also the continuum SPWs should cover as much of the IF band as possible, so they should
ideally not overlap in frequency. Not only will this maximize the continuum SNR on the science target, butthese continuum data can be used to improve phase and amplitude calibration. The continuum SPW frequencies
need to be setup manually, and one method of doing this is described below.

74

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 4 (bands 3, 4, 6, 7, 8, 9, & 10), showing the frequency of thestandard continuum settings as red shading. This gives the coverage of both USB and LSB, except for Band 9& 10, which have 8 GHz of bandwidth using the USB only. The available frequency coverage of each band isshown 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 4 in the opposite
sideband (offset by the frontend 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)• 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 frontend IF frequency (6.0 GHz for Band 3, 4, 7 & 8, and normally 8.0 GHz for Band 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 the
3 Note - this case assumes one SPW per BB

75

6.3. SPECTRAL SETUPS

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

Species/transition

Freq. (GHz)Sideb.

bandwidthStandard 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.
12
CO 2-1
continuum SPW
C18 O 2-1
13
CO 2-1
continuum SPW
Standard cont.
12
CO 3-2
HC15 N
HC15 N
continuum SPW
HCO+ 4-3
H15 CN 4-3
HCN 4-3
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

97.5
89.18888.632101.293/101.333
101.3
115.271113.499112.359102.5
100.5
145.01146.969
144.077
146.605145.603233.01230.538231.6
219.560
220.399218.5
343.51345.796344.200
345.340
343.200
356.734355.440354.505
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

dual
LSB
LSB
USB
USB
USB
USB
USB
LSB
LSB
dual
LSB
LSB
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
117 MHzTDM
117 MHz117 MHz
TDM
TDM
58 MHz58 MHz58 MHzTDM
58 MHz58 MHz117 MHz58 MHzTDM
58 MHzTDM
TDM
117 MHz117 MHz
TDM
TDM
TDM
469 MHz117 MHz234 MHz469 MHzTDM
469 MHz117 MHz
TDM
TDM

1

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
3
4

1
1
1
2
1

1
1
1
2
3
3
4
1
2
3
4

1
2
3
1
1
2
1
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=233.0
J=2-1 CO isotopes

LO1=343.5
CO/HCO+ /HCN

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 4. This includes the standard continuum-only setups,
and some multiple line/continuum configurations. Notes: 1. Frequency for standard continuum setups are themean 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. * Template spectral setup released with Cycle 4 version of
the OT.

76

CHAPTER 6. SPECTRAL SETUPS

continuum 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 Band8, 9 and 10, and near the water lines around 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.

6.3.2

Multiple Spectral Windows in the Same Baseband

Cycle 4 allows the capability to have up to four SPWs in each baseband, and each baseband can have different
setups. This is useful for projects where several lines need to be observed simultaneously at high spectral
resolution. However, in cases where four lines or fewer are observed in total, if the full bandwidth/resolution isneeded for each line and they are well-separated, it may be preferable to place each line in a different baseband.
Also, 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 SPW, and use the other SPWs in TDM mode to maximize
the total (agregate) bandwidth for phase calibration. Multiple SPWs per baseband does have some restrictions:each SPW within the same baseband must have the same bandwidth4 , and the correlator resources used foreach SPW in the same baseband (effectively the number of spectral channels, before channel-averaging) must
be equal. However, it is possible to set up different channel-averaging for each SPW, so the final number ofchannels in each SPW may not be equal. An example of this is shown in Table 6.1 for spectral setup 6 b,
where both C18 O and 13 CO are observed in the same baseband (3.1 and 3.2). Multiple SPWs are set up in
the Phase 1 OT simply by adding more spectral lines in the same baseband, and setting the SPWs to have acorrelator 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 in Cycle 4, however, the total number of spectral channels in each baseband is limited by
the correlator resources. So doubling the number of SPWs in one baseband will result in half the number ofchannels 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 amore complex spectral setup with multiple SPWs and baseband which is possible in Cycle 4. 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 receiver are shown as yellow shaded areas. The four basebands, illustrated in this caseby the green horizontal bars, can be moved around, but only within the two sidebands. The spectral windows
are also shown, labelled by the name of the primary spectral line or continuum. In this example, baseband 2 isset for a TDM SPW covering the whole 2 GHz baseband for a continuum measurement, whereas in some of theother basebands, multiple spectral windows are used. Baseband 1 has three SPWs of 58MHz bandwidth and960 channels per SPW. At the same time, we are observing two lines in BB3 with 58MHz/1920 channels per
SPW and one in BB4 with 125MHz bandwidth and 3840 channels. The basebands (and SPWs) may partiallyoverlap, as seen in this case with BB3 and BB4. Many combinations of SPWs and basebands can be set up in
this way.

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 4.1). 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 baseband 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.
4 although, as before, SPWs in different basebands can have different bandwidths

6.3. SPECTRAL SETUPS

77

Figure 6.3: Illustration of a frequency setup, based on the OT spectral display. Yellow areas are the IF ranges,
green bars are the 2 GHz-wide basebands (BB1-4), and smaller horizontal bars represent the spectral windows(1, 2 and 4 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 frontend (in this case a section of band 7), and the curved
line represents the nominal atmospheric transmission for the chosen PWV. The bandwidths of the SPWs areillustrated by the widths of the horizontal bars. The lines observed are given in example 7b in Table 6.1.

6.3.4

Spectral Setup in Band 9 & 10 and DSB Considerations

The spectral setup in Band 9 and 10 is effectively the same as other bands. The only difference is that theseuse double-sideband(DSB) receivers, so the unwanted (or image) sideband is suppressed using LO offsetting(currently using LO1 and LO2). LO offsetting can only be done in interferometric mode - see section B.4.2.
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, but observea line in the upper sideband in one baseband, and another in the lower sideband using the next baseband, justby having different signs in the LO2 offsetting. If this sounds confusing, don’t worry - just treat each baseband
independently as far as sideband choice is concerned. Note that different SPWs in the same baseband musthave the same sideband, as image suppression uses LO2, which is common to the whole baseband.

78

6.4

CHAPTER 6. SPECTRAL SETUPS

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 - see correlator chapters). So for 2 GHz nominal, the correlator outputs a bandwidthof 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.

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. The FDM spectrum has 3840 channels covering only thecentral 1.875 GHz, and the drop in power at the edges of this bandwidth is negligible (and comparable with thevariations in the bandpass). (The narrow spike in the center of the FDM data is a test signal).

6.5

Spectral Resolution

The spectral resolution of each SPW is set by a combination of the inherent resolution/bandwidth setup in
the correlator, the correlator weighting function and the channel-averaging factor (which is carried out at alate stage of processing in the correlator). This is described in the correlator section 5.5.2. The default setup
uses Hanning smoothing with no channel-averaging, which results in a spectral resolution of 2× the channel
spacing. Selecting a channel-averaging factor of 2 therefore results in only a small loss in the final resolution(of ∼15%), but has the advantage of halving the data rate. Unless the highest spectral resolution is needed, it
is recommended to apply some channel-averaging, to reduce the data rate and size of the data product; this is
more critical where fast dump times are needed, e.g. for long baseline observing.

6.6. SPURIOUS SIGNALS

6.6

79

Spurious Signals

Most spurious signals in the cross-correlation data are suppressed using Walsh-switching (see Section B.4.3).
This effectively suppresses signals generated after the frontends, but will not reduce those coming in at theobserving frequency. Results from tests with 180-degree phase switching using 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 throughthese methods. These are very narrow and will need 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:
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.
Other velocity reference frames are also possible, including Heliocentric and LSRD (Dynamical LSR, basedon the Solar velocity with respect to a rotating frame around the Galactic Center).
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 . It is also
possible to just make the correction 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 usedin the same execution for both the bandpass and amplitude calibration. For sources with an external ephemeris
file, the rate of change of distance between the target and the observatory taken from the ephemeris is used
to compute the source velocity at the start of the execution. This velocity is used throughout the observation(like non-ephemeris observations, the velocity from the ephemeris is not updated). Combining executions withdifferent velocities must be done in CASA offline (normally in the Clean process).
Note that the velocity and redshift can be defined in three different ways, resulting in different conversions
from velocity (or redshift) 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 z=(fo -f)/f. The user specifies the redshift rather than velocity.
In these equations, v and z are the source velocity and redshift, and f and fo are the observed and the rest frequencies of the line. For further details, see, for example, http://www.gb.nrao.edu/∼ghigo/gbtdoc/doppler.html
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.

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CHAPTER 6. SPECTRAL SETUPS

6.8

Limitations and Rules for Spectral Setups in Cycle 4

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

Rule

Description

1.
2.

LO1 must lie within the LO tuning ranges given in Table 4.1.
No part of the 2.0 GHz-wide basebands can extend over the edge of the IF passband.
This means that the baseband centers cannot be closer than 1.0 GHz to the IF passbandedge. For example, for 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 thebasebands over the IF edges, to cope with the differential Doppler shifts in the different
basebands, but this is small (< 1 MHz at Band 6) and is transparent to the OT user.
For 2SB receivers (Bands 3,4,6,7,8), the number of basebands in one sideband can only be
0, 1, 2 or 4 (i.e. not 3). For DSB receivers (Band 9,10), there is no such restriction (thenumber can be 0, 1, 2, 3 or 4).
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 multiple of 62.5
MHz) should be in an allowed region of the baseband. This is in addition to (4). In practicethis means that the required range of the SPW should normally be inside the range ∼2050- 3950 MHz (i.e. >50MHz from the edges of the 2-4GHz second IF) to ensure that the edgeof the anti-alias filter does not significantly affect the IF power. In practice it is possible toextend some part of the SPW to <50MHz of the IF edges; in particular this is necessary
for the Band 6 setup 6b in Table 6.1, where the 12 CO and 13 CO lines are only 70MHz fromthe IF band edges.
The line frequency does not need to be in the center of the SPW in Phase 1 of the OT:
if a line like 12 CO 1-0 is requested, it will generate an SB with the correct TFBLO offset.
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 bandwidth and use
the same correlator resources. 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 all the fractional resources
used within one baseband must be ≤1. The correlator resources are essentially the inherent
number of spectral channels. However, the channel-averaging can be different for different
SPWs.

3.
4.

5.

8.
9.
10.

11.
12.

Table 6.2: Rules for spectral setups.

Chapter 7

Imaging with ALMA
7.1

Introduction

As described in Chapter 3, the van Cittert-Zernike theorem (e.g. Rohls & 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, Swab & Sramek, 1999) that enables the resulting synthesized beam size and thesensitivity to be controlled:W

V (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. Rk is a noise-variance weight derived from the sensitivity of thek th visibility measurement. It accounts for variables such as the integration time, the system temperature, andthe bandwidth. These factors are determined by the instrument, technical set-up, and observing conditions,and are not controlled by the imaging 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, suppressing smallscale sidelobes, and increasing the synthesized beam width and surface brightness sensitivity. Finally, Dk is a(uv) “density” weight that can be used to offset the high concentration of measurements near the center of theuv-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 uv-plane. Uniform weighting allows highest angular resolution at the expense of sensitivity.
As discussed in § 7.4, ALMA imaging typically uses a tunable, intermediate form of density weighting called
Robust or Briggs weighting.

81

82

CHAPTER 7. IMAGING WITH ALMA

Figure 7.1: This is the sharpest image ever taken by ALMA. It shows the protoplanetary disc surrounding theyoung star HL Tauri. These new ALMA observations reveal substructures within the disc that have never been
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 4 Configurations

Cycle 4, 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, point spread function (PSF) or “dirty beam” ’ which results from finite sampling of the uvplane; and if TP Array data exist, gridding them into an image cube and combining this with the de-convolved
interferometer image cube using the feathering technique. We describe in this chapter some of the aspects ofimaging that should be considered in order to obtain the best results from ALMA observations.
During Cycle 4, the 12-m Array, with (at least) 40 antennas, will be arranged in 9 different configurations.
The maximum baselines achievable will be 12.6 km for Bands 3-6, 6.8 km for Band 7 and 3.7 km for Bands 8-10.
The 7-m Array, with (at least) 10 antennas, will be available in only one configuration. Starting in Cycle 4,
the three most extended configurations, C40-7, C40-8 and C40-9, will be offered in combination with otherconfigurations. 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 configurations) and hence the numbers derived for them,
are representative of the actual configurations that will be in use due to a variety of factors including
hybrid arrays that exist during antenna reconfiguration periods, precise antenna pad availability, etc... From
the user’s point of view configurations are not directly selected, instead the required angular resolution (θres )and the largest angular scale (θLAS ) that needs to be recovered are entered in the OT. Projects will then be
observed using array configurations chosen to achieve the specified goals. More details about array combination
are provided in Section 7.8.

83

7.2. CYCLE 4 CONFIGURATIONS

Configuration
7-m
C40-1
C40-2
C40-3
C40-4
C40-5
C40-6
C40-7
C40-8
C40-9

Band
Frequency (GHz)

3
100

4
150

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)

12.5
66.7
3.7
29.0
2.4
22.1
1.5
13.7
0.93
8.9
0.54
6.0
0.35
3.1
0.21
1.8
0.12
1.3
0.066
0.78

8.4
44.5
2.5
19.4
1.6
14.8
0.97
9.1
0.62
5.9
0.36
4.0
0.23
2.1
0.14
1.2
0.079
0.87
0.044
0.52

5.4
29.0
1.6
12.6
1.0
9.6
0.63
5.9
0.40
3.9
0.23
2.6
0.15
1.3
0.090
0.77
0.052
0.57
0.029
0.34

3.6
19.3
1.1
8.4
0.69
6.4
0.42
4.0
0.27
2.6
0.16
1.7
0.10
0.90
0.060
0.52
0.034
0.38
-

2.7
14.5
0.80
6.3
0.52
4.8
0.32
3.0
0.20
1.9
0.12
1.3
0.076
0.67
0.045
0.39
-

1.9
10.3
0.57
4.5
0.37
3.4
0.22
2.1
0.14
1.4
0.083
0.93
0.054
0.48
0.032
0.27
-

1.4
7.7
0.42
3.3
0.27
2.5
0.17
1.6
0.11
1.0
0.062
0.69
0.040
0.36
0.024
0.20
-

Table 7.1: Resolution (θres ) and maximum recoverable scale (θM RS ) for the 7-m Array and 12-m Array configurations available during Cycle 4 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).

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

7-m
8.9
9.2
30.8
45.0

C40-1
15.1
21.2
97.3
155.6

C40-2
15.1
27.7
141.9
272.6

C40-3
15.1
44.8
233.5
460.0

C40-4
15.1
69.0
369.7
704.1

C40-5
16.7
101.2
632.4
1124.3

C40-6
15.3
198.2
999.9
1813.1

C40-7
81.3
379.0
1748.23696.9

C40-8
168.4
501.8
2989.66855.1

C40-9
270.7
707.0
5446.812644.8

Table 7.2: Basic parameters of the 7-m Array configuration and the nine 12-m Array configurations offeredduring Cycle 4. The baselines are projected for a transiting source (HA = ± 1h) at a declination of −23◦ . Notethat C40-8 will not be available for Bands 8-10, and C40-9 will not be available for Bands 7-10.

84

CHAPTER 7. IMAGING WITH ALMA

C40-1

1000

500
Y (meter)Y (meter)

500

0

500

1000

1000
500

0
X (meter)

500

1000

1000

C40-3

1000

500

0
X (meter)

500

1000

C40-4

1000

500
Y (meter)500
Y (meter)

0

500

1000

0

0

500

500

1000

1000
1000

500

0
X (meter)

500

1000

1000

C40-5

1000

500

0
X (meter)

500

1000

C40-6

1000

500
Y (meter)500
Y (meter)

C40-2

1000

0

0

500

500

1000

1000
1000

500

0
X (meter)

500

1000

1000

500

0
X (meter)

500

Figure 7.2: Representative 12-m Array compact configurations for Cycle 4.

1000

85

7.3. SHADOWING

6000

C40-7

4000

4000

2000

2000
Y (meter)Y (meter)

6000

0

0

2000

2000

4000

4000

60006000

4000

2000

0
X (meter)

2000

4000

C40-8

60006000

6000

4000

2000

0
X (meter)

2000

4000

6000

C40-9

6000
4000

Y (meter)

2000
0
2000
4000
6000
6000

4000

2000

0
X (meter)

2000

4000

6000

Figure 7.3: Representative 12-m Array extended configurations for Cycle 4.

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 4.

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 C40-1, 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

86

CHAPTER 7. IMAGING WITH ALMA

and can be quite severe for sources that are observed at very low elevation. Targets as far North as declination+47◦ , 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”) whensources of various declinations are observed in the most compact ALMA configurations. As it can be seen, theshadowing fraction can be as large as 40% for sources observed with the most compact 12-m Array configuration(C40-1). The imaging capability, as well as the time on source, will necessarily be limited for such northernsources, especially at the higher frequencies. Shadowing depends on the antenna configuration. Given the shortbaselines in the ACA configuration, sources with declinations less than −60◦ or greater than +20◦ are subject
to significant shadowing. For the 12-m Array, shadowing becomes significant (> 5 %) in the most compact
configuration for sources with declination lower than −75◦ or higher than +25◦ .
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.

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

87

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 C40-4 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.
In order to bridge the extremes of natural and uniform weighting, Briggs (1995) defined a continuous schemethat uses 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 C40-3 configuration at 100 GHz using robust between −2 and 2. As canbe seen, the angular resolution varies from 0.900 (robust = −2) to 1.3500 (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. In order to mitigate
this effect, 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 1-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., C40-8 is not available at bands
7-10.
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

88

CHAPTER 7. IMAGING WITH ALMA

Figure 7.7: Beam shape for configuration C40-1 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 C40-1 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 24.9% of the total.

7.4. RESOLUTION AND BEAM SHAPE

89

Figure 7.9: Cycle 4 angular resolutions as a function of source declination. Each color shows, for a particular configuration, the range of the major and minor axes of the synthesized beams expected from a 2-hourobservation at 100 GHz. 12-m configurations are arranged with C40-1 at the top and C40-9 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. 12-m configurations are arranged with
C40-1 at the top and C40-9 at the bottom. The 7-m Array is also shown.

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CHAPTER 7. IMAGING WITH ALMA

determined based on the goals of the scientific case (required angular resolution, sensitivity, etc). In cases wheremore precise information is required, CASA simulations using the representative configurations, actual target
declination, uv-coverage, and clean parameters can be used to predict the resolution and sensitivity for a specificscience use case. You should clean the images carefully, and you should also add noise (and realistic systematic
errors, if possible) to your simulations, to really see what kind of residual sidelobes are expected. (Cleaning
perfect data does not show the limitations that one might obtain with real data.)
As discussed in § 7.9, combining data from compact configurations with those from more extended configurations primarily has the effect of filling in negative sidelobes in the synthesized beam and thereby improving
the interferometer’s response to larger angular structures on the sky. However it does also slightly degrade theresolution. 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 centre. However, given the finite number ofbaselines, 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 andthe smaller the sidelobes. Short integrations are still valuable, particularly when using many of the 50 ALMA
antennas, 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=-23deg.
Configuration
NaturalBriggs (R = 0.5)
Uniform

7-m
43.6%
42.6%
43.8%

C40-1
11.8%
8.8%
9.1%

C40-2
7.5%
6.8%
10.9%

C40-3
10.6%
7.0%
11.3%

C40-4
7.8%
8.1%
11.0%

C40-5
11.9%
8.8%
9.5%

C40-6
11.6%
9.3%
10.6%

C40-7
13.5%
10.5%
11.4%

C40-8
12.0%
7.9%
8.2%

C40-9
11.7%
10.6%
11.3%

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 C40-1. 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)
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 with

7.5. RESPONSE AND SNAPSHOT

91

Figure 7.11: uv-plane sampling distributions of a model ALMA observation with 1-minute integration (left) and1-hour integration (right), using the C40-1 configuration to observe a source at a declination of −23◦ .

Figure 7.12: Images obtained from a model ALMA observation with 1-minute integration (left) and 1-hour
integration (right), using the C40-1 configuration to observe a source at declination of −23◦ . Black contours at
100, 200, 300, 500, 700 and 900 mJy beam−1 are overlaid.

92

CHAPTER 7. IMAGING WITH ALMA

the actual array configuration. This test allows one to estimate the sidelobe fingerprint left by the strong point
sources after deconvolution, although the residuals will likely be higher in practice due to imperfect calibration.
It is worthwhile to use the interactive mode during the deconvolution so that residuals can be monitored.

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 Fourier transform of three uniform disks with sizes of 500 , 1000 and 2000 is shownin 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 most extended disk has large amplitudes only
up to ∼40 m. Therefore, an array with baselines larger than 40 m will not be sensitive to emission on angularscales larger than ∼2000 , and will filter out most of the emission from such an extended disk. An importantconsequence 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 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
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 4 array configurations. Note that these expressions assume
good uv-coverage. This is typically the case for ALMA 12-m Array observations, but may not be for very 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 not in 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 visibility amplitudes vs. uv-distance of an example astronomical source, M51. Thisis taken from an H-α image, but we use it to indicate the flux expected at 100 GHz. The amplitudes of the93

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: Expected visibilities of three model uniform disks (annular averages) at 100 GHz as a function of
uv-distance.
visibilities can be approximated as a power law of uv-distance with a negative index. This indicates that mostof the power is located in larger scale structures and that power decreases rapidly at smaller scales. This resultshows that the flux that would be received by the 7-m Array would be much higher than that received by the
12-m Array with extended configurations (e.g., C34-6). The only case where flux is independent of the samplingin the uv-plane is for point sources, which have the same amplitude for all visibilities (i.e., the Fourier transformof 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 C40-6 (kuv ≈ 200kλ) is only ∼0.9 Jy. Ideally, ALMA users
should use simulations to estimate the distribution of power at different length scales for targets they wish toobserve.

7.7

Mosaicing

The field of view of a single interferometer pointing is determined by the antenna primary beam . A
λuniformly illuminated, circular aperture will have a beam width at half power (HP BW ) of 1.02 D. It will also
have very high side lobes due to the abrupt truncation of the antenna illumination pattern; 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 -10dB to -15dB
response at the edges of the dish. The ALMA feedhorns were designed to illuminate the dish with a -12 dBedge taper in order to provide a nearly Gaussian primary beam with low sidelobes while preserving as muchof the resolution and sensitivity as possible. This is one of the fundamental tradeoffs of radio telescope design.
λ= 5800 at 100 GHz,
The resulting HP BW of the ALMA 12-m antennas is measured to be HP BW = 1.13 D
and it varies inversely with frequency. For example, Figure 7.15 shows a Gaussian profile which approximates
the shape of the primary beam at 112 GHz with HP BW = 5200 . As described in Chapter 3, the primary beam
attenuation can be corrected as the last step of imaging. However, in addition to correcting the signal to its
correct value it also increases the noise (i.e., the signal-to-noise is unchanged). For example at the radius of the
HPBW, the noise will be increased by a factor of two compared to that at the phase center. Moreover, beyonda certain map size, the antenna is not sensitive and it is necessary to observe several adjacent pointings, i.e., amosaic, to recover the sky emission.

94

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).
Observing a mosaic with ALMA is needed if a map size larger than approximately the HP BW of the
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 × HP BW which 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 amosaic. 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) 0.511HP
BW + 1.

2×LY √+
1.
NY = (int) 0.511HP
BW 3
Np≈ (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 OT. Note thatmosaicing with the 7-m Array is more efficient because with its smaller diameter, the HPBW is commensurately
λlarger (HP BW = 1.13 Dalso holds for the 7-m antennas).
Like a single pointing, a mosaic has an analogous “mosaic primary beam response pattern” that is the
convolution of the individual HP BW 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 HP BW/ 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 is a good choice for smaller mosaics and the constant noise hexagonal pattern is most often used forlarger mosaics. The OT can be used to easily set up a mosaic of adjacent pointings with a user-defined √spacing,
though it is not recommended to exceed spacings greater than the constant noise pattern (HP BW/ 2) if awell-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 array. Similarly, the maximum recoverable scales , θM RS , of eacharray depends on the shortest baselines present. In order to achieve the requirements entered by the PI in the7.8. MULTI-ARRAY AND MULTI-CONFIGURATION OBSERVATIONS

95

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

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

96

CHAPTER 7. IMAGING WITH ALMA

OT, θres and θLAS , multiple configurations may be needed. Note that θLAS is a property of the science target,
while θM RS is a property of an array configuration. In particular, the smallest configuration for a project mustensure 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 ALMA Observing Tool will automatically attempt
to choose configurations that will produce a final image with the requested scientific goals. Note however that
there are significant restrictions when doing this. For example, at most two 12-m configurations are allowed andthe three longest-baseline configurations (C40-7, -8 and -9) cannot be combined with any smaller configurations.
If such restrictions result in the requested θLAS not being achievable, the OT will return a validation error andθLAS must be modified. In contrast, a new possibility for Cycle 4 is “stand-alone ACA”, i.e. observations that
use the 7-m array, with the TP array added if required. It is not possible to request observations that only
require the TP array.
In detail, the process of selecting the various arrays required to satisfy the entered constraints is the following:
1. An interferometric array (12- or 7-m) is selected that comes closest to achieving the entered value of θres .
2. If the θM RS of this array is less than the requested θLAS , the largest structures in the source will not bewell imaged and smaller arrays must be added, if possible.
3. If the initial array was a medium-sized 12-m configuration, a smaller 12-m array can be added. If thisarray also has θM RS < θLAS , the 7-m array will then be added. If the initial array was one of the smaller
12-m configurations, it will only be possible to add the 7-m array.
4. If, after adding additional interferometric arrays the requested θLAS has still been achieved, the TP array
will be added. Note that this is not possible for single-continuum observations and for Bands 9 and 10 sothere is a fundamental limit to how large a source that can be reliably imaged in these situations.
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 each array to have similar sensitivity in theregion of the uv plane where they 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-4 implements for the first time configurationdependent time ratios. That is, the time multiplier for e.g. the 7-m array depends on which 12-m configuration
it is being combined with. A trend can be seen whereby the smaller the 12-m configuration, the more 7-m arraytime is required. This is because increasingly compact 12-m configurations contain more sensitivity on baselines
similar to those provided by the 7-m array, which must therefore observe for longer in order to contributesignificantly to the final image. The TP array’s time multiplier is fixed at 1.7 times the 7-m array time.
As the compact arrays do require extra observing time, it is important to give consideration to the requested
value of θLAS and to justify the final choice. An additional consideration when invoking the 7-m Array (with only
10 antennas) is that it provides limited uv coverage for snapshot observations. For Cycle 4, it is recommended
that at least one hour of unique 7-m Array hour-angle coverage is needed to provide sufficient uv-coverage forgood image combination with 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 4(Moriarty-Schieven et al., 2015).
The process whereby the OT chooses 12-m configurations is done assuming the exact antenna positions thatmake up the nine configurations that have been selected for Cycle 4. In reality, the configuration available to thescheduling software at the time of SB execution rarely conforms to this ideal, due to the fact that the array isoften 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 configuration’s properties, θM RS and θres , do not exactly
conform to any of those assumed by the OT. However, providing that the available configuration provides asimilar range of spatial scales to that which was assumed, it can be considered for SB execution providing that97

7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

θres (arcsec)
0.066
0.066
0.066
0.12
0.12
0.12
0.21
0.21
0.21
0.35
0.35
0.35
0.35
0.54
0.54
0.54
0.54
0.93
0.93
0.93
0.93
1.5
1.5
1.5
2.4
2.4
2.4
3.7
3.7
3.7
12.5
12.5

θLAS (arcsec)< 0.780.78-3.1
> 3.1
< 1.3
1.3-6.0> 6.0< 1.8
1.8-8.9> 8.9< 3.1
3.1-13.7
13.7-66.7> 66.7< 6.0
6.0-22.1
22.1-66.7> 66.7< 8.9
8.9-29.0
29.0-66.7> 66.7< 13.7
13.7-66.7> 66.7< 22.1
22.1-66.7> 66.7< 29.029.0-66.7> 66.7< 66.7> 66.7

Array combination
C40-9
C40-9 + C40-6
C40-8
C40-8 + C40-5
C40-7
C40-7 + C40-4
C40-6
C40-6 + C40-3
C40-6 + C40-3 + 7-m
C40-6 + C40-3 + 7-m + TP
C40-5
C40-5 + C40-2
C40-5 + C40-2 + 7-m
C40-5 + C40-2 + 7-m + TP
C40-4
C40-4 + C40-1
C40-4 + C40-1 + 7-m
C40-4 + C40-1 + 7-m + TP
C40-3
C40-3 + 7-m
C40-3 + 7-m + TP
C40-2
C40-2 + 7-m
C40-2 + 7-m + TP
C40-1
C40-1 + 7-m
C40-1 + 7-m + TP
7-m
7-m + TPTime ratios
1
1 : 0.3
1
1 : 0.3
1
1 : 0.3
1
1 : 0.3
1 : 0.3 : 0.4
1 : 0.3 : 0.4 : 0.68
1
1 : 0.3
1 : 0.3 : 1.4
1 : 0.3 : 1.4 : 2.38
1
1 : 0.3
1 : 0.3 : 3
1 : 0.3 : 3 : 5.1
1
1 : 1.4
1 : 1.4 : 2.38
1
1: 5
1 : 5 : 8.5
1
1: 5
1 : 5 : 8.5
1
1 : 1.7

Total Time
1.0 × ∆extended
1.3 × ∆extended
1.0 × ∆extended
1.3 × ∆extended
1.0 × ∆extended
1.3 × ∆extended
1.0 × ∆extended
1.3 × ∆extended
1.7 × ∆extended
1.98 × ∆extended
1.0 × ∆extended
1.3 × ∆extended
2.7 × ∆extended
3.68 × ∆extended
1.0 × ∆extended
1.3 × ∆extended
4.3 × ∆extended
6.4 × ∆extended
1.0 × ∆extended
2.4 × ∆extended
3.38 × ∆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: Array combination 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 one obtainedwith combined configurations can be 50% lower due to different weighting (see text). NOTES: a) for the fullarray combination, the total time is not equal to the sum of the individual times because TP and 7-m Arrayobservations are run in parallel; b) for intermediate values of θres , please see text.
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 in to the second stage of ALMA’s
Quality Assurance process (QA2) such that all observed projects should meet the user’s imaging requirements,
within some threshold. Note that some additional flexibility is provided by the assumption of Briggs’ weighting
during the imaging stage, Fig. 7.6, a scheme which allows a trade off between angular resolution and sensitivity.

7.9

Multi-array and Multi-configuration Imaging

If your project requires observations with different arrays and/or configurations we will process the data foreach of them and deliver it to you if it passes the quality assurance. When all observations are complete, wewill also— on a best-efforts basis— combine them to make and deliver a final image, again if it passes qulity
assurance.

98

CHAPTER 7. IMAGING WITH ALMA

The combination procedure comprises either one or two steps, depending on whether total power data arecollected. First, the interferometric data will be imaged together in a single, “joint” deconvolution. This can bedone in CASA by passing all interferometric measurement sets— 7-m and one or more 12-m arrays— directly
to the CLEAN task1 . All 7-m and 12-m data delivered during Cycle 4 will be directly combinable. Manuallycalibrated 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 data weights on an equal basis; however all ALMA datacalibrated by the ALMA pipeline have correct weights, irrespective of cycle and CASA version. The steps tocorrect data weight issues for manually calibrated data from earlier cycles are described in the “Data Weights
and Combination” CASA guide2 . Using the STATWT method is usually the easiest and most reliable approachassuming sufficient line-free spectrum can be identified.
If total power data are part of your 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 4 this will be done by “feathering” them together. Feathering is a commonly used technique in radio
imaging of combining two images together by forming a weighted sum of their Fourier transforms. The steps
are as follows:
1. The single-dish and interferometer images are Fourier transformed.
2. The beam from the single-dish 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 single dish aperture, corresponding toa wider (single-dish) beam.
3. The Fourier transform of the interferometer image is multiplied by (1 – F T SDB(u, v)). This down-weights
the large spatial scale components of the interferometer map which are poorly measured, if measured atall.
4. The Fourier transform of the single-dish 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).
A 1-hour observation with the C40-1 configuration and 5 hours with the 7-m Array is shown in Figure 7.17
(uv-coverage) and Figure 7.18 (uv-plane sampling distribution). The Cycle 4 7-m Array configuration with ten
7-m antennas provides uv measurements in the range 8-32 m and takes 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 overdifferent length scales (see 7.14), Figure 7.19 shows the images resulting from observing with a C40-compact
configuration (C40-3), a compact and extended configuration (C40-3 + C40-6), and adding the 7-m Array.
Natural weighting was used and deconvolution was performed using the CLEAN algorithm. The recovery oflarger scales is quite noticeable with the use of the 7-m Array. Using only the C40-6 configuration at 100
GHz provides an angular resolution of 0.2700 . Combined with the C40-3 configuration, the angular resolution islowered to 0.3100 . Finally, the angular resolution with the full combination (C40-3 + C40-6 + 7-m) is 0.3200 , very
similar to that of only the two 12-m Array configurations but 17% larger than the angular resolution obtainedwith the extended 12-m Array alone. That difference is due to the respective uv-coverage and weight of thearray configurations in the combined dataset.
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. to uniform, at the expense of sensitivity.
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.
2 https://casaguides.nrao.edu/index.php/DataWeightsAndCombination

7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

99

Figure 7.17: Expected uv-coverage for C40-1 (1 hour) and 7-m observations (5 hours)

Figure 7.18: Radial density of uv-coverage with uv-distance using C40-1 (1 hour) and 7-m observations (5 hours)

100

CHAPTER 7. IMAGING WITH ALMA

Figure 7.19: Images obtained using C40-3 (top left; 1 hour), C40-3 + C40-6 (top right; 1 + 3.3 hours) and C40-3+ C40-6 + 7-m (bottom left; 1 + 3.3 + 1.3 hours) array combinations, and the image model itself (bottom right).

7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

101

References[1] Briggs, D. S. 1995, High Fidelity Deconvolution of Moderately Resolved Sources Ph. D. thesis, New Mexico
Institute of Mining and Technology[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 we described the software
implementation 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). They are the minimum setof instructions that describe an ALMA observation. The SBs are produced by the ALMA Observing Tool
(hereafter OT) which is the tool used during the Phase 11 stage of the project life cycle. The SB may be editedusing the OT in Phase 2 proposal acceptance and before/during proposal execution2 . Projects are broken down
into a set of these fundamental units for flexibility, given the properties of the ALMA site and the continuouslyvarying status of the Observatory as a whole (including the weather), and to encapsulate the scientific objectivesof the proposal into single entities.
An SB contains a large amount of information about what it should be observed, the positions and velocitiesof the 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 of observation
required e.g., single-dish, single field interferometry, etc. The SB has relatively little influence over the order inwhich 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 hour. 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 from the last scan. 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 the required sensitivity. The current maximum time (or end execution) for a particular SB, has
1 For a description of Phase 1 and Phase 2 see the Cycle 4 Proposer’s Guide
2 SBs can also be created in and ad-hoc manner for commissioning purposes

103

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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 an Scheduling Block is executed, CONTROL
creates a new ExecBlock structure (see text).

8.2. PROGRAM EXECUTION

105

been chosen based on statistical measurements about the stability of the system. A system failure will preventthe online software from flushing the data into the archive losing the observed project data. Thus, executing
SBs for more than two hours becomes unsafe from the operational perspective. To optimize this scheme, we
implemented what we call a session, which is the continuous execution of a single SB until a certain goal has
been reached (see detailed description later on). 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 thesmallest unit for data processing.
All SBs that 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 begrouped 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 OUSes . A typical case of Member OUSes 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 OUSes, but in the same Group OUS as one final image will be produced.
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 OUSes which have already beenprocessed. The only other event that triggers data reduction is the end of an observing season, when all
the Member OUSes and potentially Group OUSes 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.
The SB/Member OUS/Group OUS are the smallest structures that hold science observations that need tobe observed/processed/combined together. These data hierarchy therefore maximizes observing flexibility andensures 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. Each Science Goal contains only one Science Goal OUS.

8.2

Program Execution

Once a given SB has been selected for execution (by the Scheduler subsystem or by the Astronomer on Duty,i.e., AoD), it is read 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, anumber of EBs may exist for a given SB. Each EB contains a record of the parameters and conditions underwhich the SB was executed along 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 therequired calibrations and command CONTROL to execute them. Each scan execution is in fact carried out
by breaking it down into a series of subscans, each of which is itself broken into a series of integrations (thecorrelator software only understand subscan sequences). Although commands are issued at the scan/subscan
level, the correlator output corresponds to a particular integration. In general, each calibration observationconsists of a scan containing several subscans (e.g. the 5 points of pointing calibration constitutes a scan withfive subscans). Similarly, the integration time on a single science source between phase calibrations can consistof one scan comprised of a number of subscans. To optimize the execution, scans may be organized in scansequences 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 orless. Integrations tend to be on the order of one to 10 seconds where the final value has to be an integer multipleof the correlator dump time. These values can be specified during Phase 2 SBs construction, particularly in
the SB target parameters section. Calibration results from the Telescope Calibration subsystem (TelCal) andQuickLook (QL) pipeline are usually attached to a scan where one example is an antenna pointing result. The

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SSR and the Control subsystem are responsible for the creation of all the metadata needed downstream for dataprocessing.

8.3

The Observing Process

For a given project, a set of targets are specified in the SB. These targets can correspond to either calibrationor science executions. Targets are organized in observing groups where the first group (group 1) is always theinitial calibration group, with subsequent groups detailing the science observations3 . All Science targets andrelevant calibrators within a group are observed before the next 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. amplitude, bandpass, etc) usually specified in group 1 are performedat the beginning of the observation sequence if appropriate sources are available. The sources are selected at
run-time by the SSR query algorithm using the parameters defined in the SB as input. If sources of sufficientquality for calibration are found the SB will execute.
Pointing, Atmospheric, and Sideband-Ratio calibrations are associated to the main (Bandpass, Amplitude,
Polarization, and Phase) calibrations on a is-needed basis which is determined by the SSR at run-time. However
usually, Pointing is verified before the amplitude and bandpass calibrators are observed, and again before themain observations of the science target and phase calibrator cycle. Within a group, the Science targets are eachobserved in turn until observation of the primary phase calibrator (the calibrator with shortest cycle time in thegroup) is required. A typical cycle time for the phase calibrator may be 7-10 minutes. 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 alternatives 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).

8.3.1

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 we check whether there are flux measurements at the SB representative frequency.
If no flux measurement is present, we extrapolate the flux using a spectral index of -0.7 to the SB
representative frequency.
3 However, this is not strictly correct. Additional calibrations can be added into subsequent groups and they will be interleaved
according their cycle times. One example is the polarization calibration

8.4. SINGLE FIELD INTERFEROMETRY

107• 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 strength,
separation respect to the query center and flux error.
• The final list is sorted based on ranking.
Using these rules we implemented the criteria for all the ALMA calibrations adding specific requirements
based on the nature of the target, such as:• Bandpass calibrator. A signal to noise of 50 given 15 minutes integration is used in the flux estimation.
The smallest spectral window (bandwidth) is used for this calculation. The default search radius is definedto the be 45deg from the query center, but the user can overwrite this default as needed. A minimum
elevation is calculated to avoid antenna shadowing.
• Phase calibrator. A signal to noise of 15 given 2 minutes integration is used in the flux estimation.
The widest spectral window bandwidth (usually 2 GHz) is used for this calculation. A 20 degrees fromthe query center search radius is used as default (smaller cycle times and radii are used for the highest
frequencies and longest baselines, as described in Chapter 10). However, value is taken from the SB andthe closest source to the target, from the selected list, is returned.
• Flux calibrator. A solar system object is searched first, then a grid source. First observable grid source ispicked up. A detailed list of the Solar System objects and grid sources used for flux calibration is available
in Appendix C.

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 thesource 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 (specially at higher frequencies), radiometric observations of atmospheric water lines are done
to correct for these additional phase variations. This corrections can be applied online and offline (see section
10.4.2 for further details).

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8.5

CHAPTER 8. OBSERVING MODES

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) observations 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 due to limitations in the observing script in cycle 4.
Group 2 can contain pointing observations (if a calibrator is attached to that group and none have been carriedout in group 1), and the atmospheric calibrations at regular intervals. another round of pointing calibration,then a sideband ratio measurement. For the higher frequency bands, a focus calibration is executed next. Then
another atmospheric calibration is taken at the reference 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 4, scans are taken either in longitudinal or latitudinal directions as specified in the OT. 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 15 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 (Ta∗ )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1098.7. POLARIZATION

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 flux4 .
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
splitter5 . 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, we would be able to combined the crosscorrelated visibilities and recover the Stokes parameters as,

Vxx + Vyy
2
Vxx − Vyy
Q=
2
Vxy + Vyx
U=2
Vxy − Vyx
V =
2
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 and YY),
and the linear polarization is described by Stokes Q and U ; while circular polarization is described by Stokes
V . However, there are number of issues that prevent us from 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 and theband (cartridge design and external optics). Additionally, this quantity is measured in the frame of theantenna which is an elevation and azimuth frame (Alt/Az) and thus, it rotates with respect to the frame ofthe sky. This rotation introduce an angular dependance into the visibilities as a function of the parallactic
angle (ψ). By design, the instrumental polarization is small (a few percent), but not negligible.
4 It is expected that during Cycle 4, 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.
5 For the ALMA receiver bands offered in polarisation mode in Cycle 4, bands 3 and 6 the polarisation splitter is an OrthoMode-Transducer (OMT), and for band 7 it is a polarized grid

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CHAPTER 8. OBSERVING MODES

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 photonic references 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 4 (see below for a detailed explanation.)

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.
By taking into consideration the instrumental polarization and the parallactic angle dependence, we canre-write the equations for the visibilities 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 few percent at Bands 3, 6, and 7 on axis withsome variations over frequency 6 . Without any D − term calibration, an unpolarized source may appear to bepolarized 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 no signal. However,bright unpolarized sources are rarely found.
ALMA therefore normally uses an unresolved quasar as a polarisation calibration source. These are monitored to ensure they are bright enough, and the exact polarization is determined during data reduction provided
that the source is observed over a wide enough range (> 60◦ ) of parallactic angles to separate the effects of the
6 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 small amount, but still only a few percent

111

8.7. POLARIZATION

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.

source polarisation, 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 favourable 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 polarisation 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 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 4, the off-axis instrumental polarization calibration will not be employed. In Cycle 4, polarisation 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 polarisation. Users mustjustify that their science goals can be met by sources exceeding these lower limits (of 0.1% polarisation for apoint source in the centre 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 the offered Bands (3, 6, and 7). Figure 8.4 shows the D-term solutions of arepresentative antenna (DV22) obtained during commissioning. Figure 8.5 shows a zoomed-in view in frequencyof 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 even in highest frequency resolution mode (30.5 kHz at the rightbottom panel of Figure 8.5). Figures 8.4 and 8.5 clearly demonstrate that the instrumental polarization ismostly spectral resolution independent for these datasets. No mosaic, ACA, circular polarization and TP Arrayobservations are offered. Further, a minimum execution time of 3 hours will be imposed to ensure sufficientparallactic angle coverage for calibration.

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CHAPTER 8. OBSERVING MODES

Figure 8.4: A frequency vs real part the D-terms plot for an antenna (DV22) obtained towards J0522-364. Bluecircles and red crosses are showing the D-term obtained using a setup of FDM with 2GHz bandwidth and using
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).

8.7.1

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), we implemented the concept of a session 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 calibrationâĂŤscience target loop
will be interrupted (preserving phase calibration) when an additional calibration is-needed (e.g. polarization)7 .
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, we
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 thosecases are not offered in session mode for Cycle 4. 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 by CONTROL
software to access a persistent component which we use to store and retrieve this information.
7 The cycle time parameters are user controlled and can be explicitly specified in the OT target parameters section

8.8. MULTIPLE REGION MODES

113

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).

8.8

Multiple Region Modes

In the frequency division modes (FDM) of the correlator (see section 6.3.2), the final spectrum is synthesizedusing 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 disjoint 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 4 separate windows, each with 62.5 MHz width, anywhere within the 2
GHz baseband. In Cycle 4, a maximum of 4 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 Cycle 3. Several wellknown 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 be supplied
as an input. The ephemeris file must be in JPL Horizons format. A typical ephemeris file may consist of thedate (time), Right Ascension, Declination, range and range rate, for example:*******************************************************************************
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

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CHAPTER 8. OBSERVING MODES

2012-Jun-26 13:05
2012-Jun-26 13:06

06 22 58.14 +23 16 10.74 1.01653122901917
06 22 58.30 +23 16 10.66 1.01653122901917-0.2541942-0.2531491

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 but it has not been implemented until now
pending extensive tests to determine appropriate observing modes and calibration strategies. In Cycle 4, solar
observing with ALMA will be supported for the first time, albeit with limitations. In particular, the following
conditions apply to solar observing in Cycle 4:• 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 C40-1, 2,
or 3 (see section 5.3.2 of this Proposers Guide).
• 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 12m and 7m dishes and will beprocessed with the baseline correlator (section 5.1).
• To minimize shadowing of 7m antennas, observations will be carried out between 13:00 UT and 20:00 UT.
• Mosaicking 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 2 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 4.

8.10. SOLAR OBSERVATIONS

115• Single-dish total-power mapping will be “monomode” (double-circle scan pattern) with a 2400arcsecdiameter 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 is designed to scatter the opticaland IR radiation to an extent that the subreflector and other elements in the optical path are not damaged ordegraded. 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 thereceiver input. Since the quiet Sun has a temperature of ∼5000-7000 K at ALMA frequencies, the solar 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 4. These are referred to as solar observing modes MD1 and MD2.
• 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 of order ∼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 the either the 7m or 12m 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116

CHAPTER 8. OBSERVING MODES

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 7m and 12m 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%. We conclude that no explicit correction fordifferential bandpass is needed.
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 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.

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8.11. VLBI OBSERVING MODE

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.

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.
While various types of scan patterns have been developed and tested for ALMA dishes, Cycle 4 supports
the use of a “double circle” pattern, which map 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

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millimeter and submillimeter wavelengths. In Cycle 4, ALMA VLBI mode observing will be offered in Band 3 inconjunction with the the Global Millimeter VLBI Array (GMVA)8 and in Band 6 in conjunction with the Event
Horizon Telescope (EHT) network9 . For details about proposing for these opportunities, see the ALMA Cycle
4 Call for Proposals See https://science.nrao.edu/observing/call-for-proposals/1mm-vlbi-cycle4/ .
For all VOM observations in Cycle 4, ALMA will be operated as a phased array of 12-m antennas (mostlikely containing between 31 and 37 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, we have
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 outputted 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 a common sites(MIT Haystack Observatory and MPIfR Bonn) for correlation with the other VLBI site data before delivery to
the PI (see below). We elaborate on some important details of the VOM 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 requirements of
the individual telescopes that comprise the global array. In practice, for the ALMA VLBI observer there will bevery 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 SCHED10 )for a particular observing campaign. In these schedules, some number of contiguous hours will be devoted toeach 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 4 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 of order several minutes to allow time
for local calibrations (pointing, system temperature measurements, etc.) and antenna slew time sufficient tomeet 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 forstandard interferometric observing, including flux, gain, bandpass, and polarimetric calibrators (see below).
Since all VLBI science targets for Cycle 4 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
8 See http://www3.mpifr-bonn.mpg.de/div/vlbi/globalmm/
9 See http://www.eventhorizontelescope.org/
10 http://www.aoc.nrao.edu/software/sched8.11. VLBI OBSERVING MODE

119

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, DiFX11 , 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 is 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 ensurethat the VLBI data can be correlated with the other stations. The VOM spectral set-ups chosen for each bandin Cycle 4 was 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 betuned 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 and the number of recorded bands
will depend on the capabilities of the EHTC—for Cycle 4, use of the two upper bands is expected at some sites,
and the 227.1 GHz band at all sites.
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 madeavailable to the observer, 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)12 We present some of the detailsof this in the following sections, with particular emphasis on those aspects which are essential either for the
proposer or data analyst to be aware of. We begin with a discussion of the VOM Scheduling block in the next
section. Then Section 8.11.2 discusses the scan sequences used by the VOM. That is followed by a section withsome 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
the scope of this document).
11 http://www.atnf.csiro.au/vlbi/dokuwiki/doku.php/difx/start
12 An NSF MRI/ALMA development fund project.

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CHAPTER 8. OBSERVING MODESVLBI 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 4.
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 ensure that the necessary calibrations
as specified by the OT are performed with the desired repetition rate. However, 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
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 correlator scans
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. the signals of each polarization in eachband 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 to adjust the antenna phases byexactly the computed values so as to bring all signals into phase with those of the reference antenna. Oncethese adjustments have been made, a “residual” phase correction typically needs to be made on the following
correlator scan, and indeed, such corrections continue to be made every scan until the end of the recording. The
phasing loop is closed in the sense that small errors in the phase adjustments may be corrected on subsequentscans. This is the so-called “slow” loop which is illustrated schematically in Figure 8.7.

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8.11. VLBI OBSERVING MODE

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 thethird correlator subscan. These parameters are all programmable, and judicious choices for them are made when
the schedule block is created. For Cycle 4, the subscans are likely to be 16-s long with 4-s (channel average)
integrations; there are then about 30s of observations prior to the start of the recording. Note that the ALMA
correlator does its processing by subscans—each subscan must be dumped and processed by the correlator andultimately archived—with a gap of several seconds between subscans. On the other hand, the signals from theantennas flow continuously to the summation logic and recorders, so there is 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

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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) sothat the visibilities found in the data set have essentially zero delay on each baseline. (I.e. there is no slope in aplot of visibility phase as a function of with frequency on any baseline.) Unfortunately, a (significant) componentof 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, independently phasesthat 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 4 ensures that this is the case.
The activities of the phasing loop are fully documented in an ASDM table as described in Section 8.11.2.
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 document13 . 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, we should point out a few details. The most significant point is that the effective area of of the“ALMA dish” is roughly proportional to the square root of the number of phased antennas. (In Cycle 4 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
relation14 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
13 A VLBI analysis handbook is in preparation.
14 ALMA-05.11.63.03-0001-A-REP.pdf

8.12. HIGH FREQUENCY OBSERVING

123

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 4, 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 thathe 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 lack of calibrators. These techniques,
which are just addenda to standard observing modes, will be progressively 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, we add a brief description of the nomenclature that would be used by Contact Scientists
and the ALMA project in general whenever they are discussed, reported or communicated to PIs:
• 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 for details)
within 10 degrees of the science targets in each SB will be carried out by ALMA staff within 90 days ofthe 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.
• Band-to-Band Transfer (B2B): Whenever suitable calibrators at the observing frequency are unavailable, the B2B technique will be used. B2B consists in phase calibrator observations at a lower frequency,
where many more calibrators are available, straddling the science target observations. In order to properly
scale the phases between the low-frequency band and the high-frequency band observations, a separate
source is observed in both at some point during the SB execution. Such source does not have the requirement of being close to the target, and therefore the probability of finding one at high frequencies issignificantly higher. For more details, please read Section 10.6of this Handbook.
• 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. With this, it will be possible to transfer the phase solutions of the wide-band spectral
window to the rest. Whenever adding an spectral window is not possible (i.e., projects that have occupied
all the spectral windows with narrow-band set-ups), there is also the option to use the Differential Gain
Calibrator approach, which will add some observations with a different spectral set-up (i.e., wider spectral
windows) in the normal cycle of observations. For more details, please read Chapter 10.

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CHAPTER 8. OBSERVING MODES

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, but which is also internally used by the OT to calculate its time estimates based on
the parameters entered into a project’s Science Goals. The GUI version is also available as a Java applet in the
ALMA Science Portal1 .
Although the user may experiment with various sensitivity options (PWV octile, number of antennas, etc.)
in both the Java applet and the OT’s GUI, the final time estimate for a project cannot be influenced to thesame extent. For instance, the OT will always assume a fixed number of antennas for the particular Cycle, andwill always use the PWV octile that it calculates as being appropriate to the frequency of observation.

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 the opacity
and the atmospheric “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 thatthe 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 the
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.

125

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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.
atmosphere, Tatm , to be measured i.e.
Tatm =

Tsky (z = 0).
(1 − e−τ0 )(9.2)

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.


hν/kT
Tn = T ×(9.4)
ehν/kT − 1
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 9.1.1.
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.

9.1.3

Receiver temperatures

For ALMA Bands 4, 5 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, 6, 7,
8 and 9, however, typical values measured in the laboratory are used as these are usually significantly better9.1. CALCULATING THE SYSTEM TEMPERATURE

127

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.

than the specifications. The measured values are somewhat conservative and so are in between what we might
expect at the middle and edges of the bands. The values used in the ASC are given in Table 9.1.3. Note thatsingle 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.

9.1.4

Ambient temperatureThis is essentially spillover from the sidelobes of the antenna beam corresponding to emission from the groundand the telescope itself. This is held constant at 270 K (median value as measured from many years of monitoringdata at the ALMA site). However, the value used by the ASC is converted to a noise temperature according

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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
65
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 we are currently assuming 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).
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
the source contribution 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. This is the case even though no data is being produced from the image sideband! Therefore, it isimportant to avoid areas of bad atmospheric opacity in the image spectral windows and the 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 centred 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).

9.1.6

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
2
×
T
+
η
(T
+
T
)
+
(1
−
η
)
×
(T
+
T
)
(9.5)
Tsys,dsb =
rx
eff
sky,s
sky,i
eff
amb,s
amb,i
ηeff e−τ0 sec z
where• Trx – receiver temperature

129

9.1. CALCULATING THE SYSTEM TEMPERATURE

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).

• 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 we thus divide through by them in order toobtain a measure of the system noise that is relative to the unattenuated source. Note that this is always doneat the signal frequency.
For SSB and 2SB receivers, the equation is the following:
Tsys,ndsb =1ηeffe−τ0 sec z

Trx + ηeff Tsky,s + (1 − ηeff ) × Tamb,s



(9.6)

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

9.1.7

System Temperature (Applet and GUI version)

The equation used for the Java applet and the GUI that is accessible from within the OT is similar, but theseare stand-alone applications that do not know the location of the image sideband and thus cannot perform arigorous calculation of its contribution to the system temperature. In this case, the same equation is used for

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CHAPTER 9. ALMA SENSITIVITY CALCULATOR

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,seff
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 residual pointing and focus error.

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 9.3 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
• 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 Java applet (see below) which therefore
also assumes a value of 0.88
• N – number of antennas. This defaults to 40 for the 12-m and ten 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
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.

131

9.3. USER INTERFACE

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 and7-m antennas respectively.
• 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 usedσTP =2 k Tsysp.
ηq ηc Aeff N np ∆ν tint

This is the similar to Equation 9.8, but there is only a factor of
to take into shadowing into account.

√(9.11)

N in the denominator and there is no need

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.

9.3

User Interface

The main way that a user interacts with the Calculator is through a GUI in the OT or via a Java applet on
a web page – both are essentially identical. By entering various parameters, the time required to achieve aparticular sensitivity (in either Jy or K) can be calculated, or vice versa. The inputs that affect the 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.

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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.

• 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 40 from the
12-m Array, ten from the 7-m Array and three from the TP Array.
• 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

9.4

133

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 Measured Visibility Function

10.1.1

The Data Format and the Correlator Model

The primary 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 (See Chapter 14). andare in the form of the ALMA Science Data Model (ASDM). Details of the flow of the astronomical data fromthe antennas through the correlator to the archive are given in Chapter 14.
Because most observations are associated with celestial objects, their diurnal motion produces up to kilohertz phase rate changes in the visibility phase. For this reason a correlator delay model, associated with anassumed position, σ in the sky, is included in correlator processing in order to remove the approximate a priorisignal delays that are a function of baseline length, observing frequency (see Chapter 5). An important partof the correlator delay model is the estimated atmospheric path delay to each antenna from the radio source.
With this correlator model removed from the correlation of the input signals, the visibility function can thenbe averaged coherently over many seconds and a large bandwidth.

10.1.2The Visibility Function Dependence

The fundamental observational segment is the scan. It is an observation with one field name, associated witha phase center σ (which may be moving), and one frequency band, νb . The observed visibility function, V o ,associated with a scan/band is
V o (σ, νb )i,j [tk , νs,c , pq ]where:
i, j is baseline between antenna i and j.
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 channelization of each SPW (from 1 to 4096).
pq represents up to a maximum of four polarizations products.

135(10.1)

136

CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESThe complex visibility function is often described by its amplitude, Ao and its phase φo components sincevirtually all of the calibrations operate on amplitude and phase, rather than real and imaginary parts of thevisibility function.
The autocorrelation data, where i = j is also contained is the data set. The calibration and use of this data
are given in Section 8.6 and Chapter 13.

10.2

Main Interferometric Calibration Strategies

10.2.1

Phase Referencing

Nearly all ALMA interferometric observations use phase referencing as the major calibration method. Thismethod interleaves scans between the science target and a nearby calibrator source that is usually a quasar of
known position, spectrum and flux density.

10.2.2

Antenna-based Calibrations

Most of the changes to the true visibility function are associated with the signal flow for a given antenna fromthe troposphere above that antenna, through all of the electronic processing along the signal path, up to thecorrelator. Hence, the calibration equation that describes the changes can be written as: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
the normal antenna-based calibration equation. The second line contains the effect of noise and any additional
baseline-calibration, and these will be ignored for the most part. The polarization dependence and more
complicated frequency separation are not included, but discussed below.
The complex antenna gain is also separated into the antenna-based amplitude and phase gains,
Gi (tk , ν) = ai (tk , νc ) eiψ(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 . These are the major calibration quantities that are describedin this chapter.

10.2.3Major Calibrations Affecting Interferometric Data

The modifications of the radio waves from a celestial source occur at many locations along the path from thesource to the data archive. A relatively complete list of signal changes, based on G Moellenbrock’s 2014 Socorro
Summer School Lecture is as follows: 1
I = Ionosphere: Opposite rotation of linear polarization position angle caused by propagation through theionosphere—not significant at the current ALMA frequencies.
T = Troposphere: Absorption of signal and delay of signal caused by several atmospheric components.
P = Antenna Voltage pattern: The relative response of the antenna from the reference (pointing) position,
caused by focus and pointing offset.
1 https://science.nrao.edu/science/meetings/2014/14th-synthesis-imaging-workshop/lectures-files/
MoellenbrockCalibration2014_FINAL.pdf

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137

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 main ALMA calibrations of interest to most users deal with thetemporal gain G and the bandpass response B. The calibration process is significantly simplified because thetemporal dependence (GT ) and frequency dependence (BF ) for nearly all instrumental changes are only lightly
coupled, so their variations can be determined independently, or at least interactively.
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 the array,for example the antenna response patterns, and antenna positions. They are measured periodically by
the ALMA staff using methodologies that best suit the calibration. These calibrations are briefly outlined
below.
Online parameters and calibrations. Measurement of relevant instrumental parameters are made during
the observations to determine calibration values that can be applied as the data are taken. These include
thermal antenna pointing offsets; measurement of Tsys /TRX using the Amplitude Calibration Devices(ACDs); measurement of the water vapor emission of each antenna toward the source in order to determine
the wet path delay variation along the line-of-sight; measurement of the variable delay using a Line-Length
Correction system (LLC).
Offline calibrations. The offline calibrations are those determined after the completion of the experiment.
These calibrations are often associated with special-purpose calibrator observations that are embedded
within the science observing blocks (SB). Two examples are the removal of the frequency dependence
across the measured bandwidth, B, and the removal of the amplitude and phase changes during theexperiment, G. Another important calibration is the conversion of the correlated visibility amplitude to
Jansky flux density units.

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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:
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. This sensitivity correction is needed for large angular source emission, and for multi-pointings observations (mosaicing) withoverlapping fields. The measurements are made by mapping the antenna beam using a bright radio source,
either single dish scanning around a strong source or with interferometric observations at many points
over an area that extends well outside of the main primary beam area. The measurements are processedin special-purpose software that determine 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 are available in the software packages and applied during the image-make step (seeChapters 3 and 7 for more details). There are four different antenna-types (12-m European, Japanese,
American, 7-m Japanese) that have significantly different primary beam shapes.
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, order 100000 ), elevation encoder/collimation offset ("IE" term, few hundred
arcsec), azimuth collimation offset ("CA", few tens of arcsec), tilt in North-South and East-West directions("AN" and "AW" terms, order 1000 ), and elevation sag ("HECE" term, around 1000 ). The full models have
17 to 19 terms, most of which are at the arc-second level. The pointing differences among the receiverbands require only an elevation and azimuth collimation offset with respect to that of a reference frequency(usually Band 3 or 6).
The complete pointing models are checked and adjusted on weekly timescales, primarily by making "allsky pointing runs", which are observations of about 50-100 interferometric pointing measurements on awell-distributed set of bright quasars of accurately known position. The total observing time is about
one hour and each pointing measurement scan consists of a measurement of the quasar amplitude at fivesubscans at different antenna pointing offsets (depending on frequency and antenna diameter) from theassumed pointing direction. From these data, the pointing offset from the assumed position for eachantenna are determined to an accuracy of around 0.100 .
The pointing models are stored in the Telescope Monitor and Configuration Data Base (TMCDB) which
includes a history of all changes. The results of additional pointing measurements made over many weeks
during spot checks, are also used to update the pointing models when appropriate. Currently only nighttime pointing measurements are considered in these static models. During daytime observations, thepointing changes dynamically and the modeling of them is continuing.
When an array element is relocated from one pad to another, such as during array reconfiguration, thechanges 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 measuring the amplitude and phase of the outputs
of inclinometers located above the azimuth bearing. This gravitational tilt is converted to an astronomicaltilt by adding a local gravity vector (which in long-baseline configurations varies significantly across thearray due to 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 these major adjustments, the pointing model is refined as described in theprevious paragraph.
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 made at the target observing
frequency up to Band 8, and in Band 8 for higher frequencies. The choice of pointing tuning will be madeby the observatory in order to maximize available array elements by avoiding bands or frequencies affectedby hardware problems, and minimize pointing error. This residual collimation offsets at typically arcsecond
level are applied in an auxiliary pointing model, which is added to the master static TMCDB pointing

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139

model for each antenna. With this residual offset pointing correction, the pointing accuracy for sciencetarget and calibration scans is intended to be within 0.600 rms. The total pointing model in-use at any
time during an observation (sum of primary and auxiliary models) is stored in a PointingModel table in
the ASDM datasets.
Focus Models (P). The focus of the ALMA antennas is adjusted by moving the subreflectors in threetranslational axes during observations to determine a six parameter model, plus offsets for each receiverband relative to the reference band (Band 7) at elevation 50◦ and temperature 0◦ C. The models contain
an offset for each axis which describes the optimum subreflector position for Band 7 ("XR", "YR","ZR"). In the axial (Z) and elevation-oriented direction (Y ) there is a coefficient of sag with elevation("ZS", "YS"). For the Z axis there is a temperature coefficient ("ZT"). These models are maintainedby long-term compilation of focus measurements in all receiver bands for the antennas, and are impacted
slightly to hardware changes. Focus measurements are traditionally made in a method similar to thatfor interferometric pointing measurements, except the subreflector is offset (in one axis per scan) relative
to the nominal model position. The subreflector position along the axis is changed and that giving the
maximum cross-correlation signal is determined for each antenna. During Cycle-4 a faster technique inwhich the three-axis focus offsets are derived from holographic beam maps (which do not require thesubreflector to move), may be used. These measurements are made by the observatory as needed tomaintain the models. The models are stored in the TMCDB in the same manner as the pointing models.
For frequencies less than 500 GHz during the night, the optimum focus position across the focal plane, X
and Y positions, is described accurately by the temperature-dependent antenna models and are is rarely
checked with observations. Generally when switching to a new receiver band it is a useful cross-checkto make a focus calibration in the Z axis (in-out direction), and can be done during the pointing anddelay offset measurements as by-products. For Bands 9 and 10 where focus accuracy is more critical, theobservations require use of the brightest quasar, and for the atmospheric conditions to be excellent. At
night, errors below 20 microns are achievable.
During the daytime the focus can deviate from the models by several hundred microns, so focus calibration
observations are generally executed between every science execution above 240 GHz in order to track thesevariations, but the poor atmospheric stability produces focus measurement uncertainties. Generally, focus
errors can be larger than 100 microns in daytime, so that observation during the day at Bands 8, 9 and
10 need frequent focal checking. Further daytime modeling and observing strategies are in progress. The
focus model used during an observation is stored in a FocusModel table in the ASDM datasets. As forpointing, modeling and correction of focus during daytime is continuing in progress.
Antenna Delay Offsets (D). Short observations are often made at the beginning of each day’s run in order tocheck the delay offsets of each antenna/SPW/pol signal path. These are made with short interferometricobservations of a strong quasar at the relevant tunings. If the delay offset is more than about 50 ps,
producing a phase change over a 2 GHz bandwidth of 36◦ , the delay offset in the TMCDB entry will
be adjusted. Delay measurement offsets are repeatable to better than 10 ps, but the can vary by a few
tens of ps from a variety of effects. Hence, during calibration and science observations, the online delay
errors are usually below 50 ps, so the use channel-average data over the 2-GHz bandwidth will have little
decorrelation due to the delay errors, and they can be used for continuum analysis, both in PI observations
and for or pointing, focus and beam measurement calibrations without the need for a bandpass calibration.
Antenna Positions (M). The relative location of each antenna (essentially the relative positions of theirfocal points) must be known to within a fraction of the observing wavelength, with a goal of about 50
micron accuracy. The antenna positions are crucial for the determination of the accurate correlator delay
model, M , and the derived phase of an observation.
The baseline runs (as they are called) are executed by the ALMA staff about once per week during good
weather conditions, but also when one or more antennas have changed pads. The antenna positions are
determined from about 50 one-minute interferometric scans at 100 GHz of quasar calibrators that are
unresolved and have milli-arcsec accurate positions. The observations cover a wide range of elevation andazimuth to determine the three coordinate offsets of the antenna position from that referenced in the
TCMBD that is used in the correlator model.

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESThe typical apriori position offset for an antenna that has been placed on a pad is well-above the antenna
location specification of 0.05 mm, so baseline observation runs must be made after any configuration
change. Depending on the weather conditions and other array operation constraints, the position of a
recently moved antenna may not be measured and updated in the TCMBD for up to a week. Thus, thecorrelator delay model will be incorrect and the visibility phase for data associated with this antenna
will have significant phase variations with time and between sources. There are offline procedures in thedata reduction scripts (see below) to correct for the difference between the antenna position used in the
TCMBD and the more accurate values measured after an accurate baseline run. For the longest ALMA
baselines, it is difficult to measure the antenna position accuracy better than 1 mm because of the effectof the variable atmospheric refraction over the array.

10.4

Online Calibrations

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 which is 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 ALMA 12-m antennas are equipped with a Water
Vapor Radiometer (Dicke-type) that measures the emission of the atmospheric 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 Section 5.4. The 7-m (CM) antennas do not have wvr receivers.
There have been tests to use the wvr signals from the four PM antennas that surround the CM array,and interpolating the effective wvr correction for each CM antenna, but are believed to be unnecessary
for this short-baseline data.
The conversion of the water vapor emission into appropriate delay changes (M) is calculated using two
methods and will be discussed in the following section.
System and Receiver Temperature (T). At millimeter and submillimeter wavelengths, the additionalrandom noise associated with a measurement has two major origins: the noise associated with the receiving
system, TRX , and the noise associated with the atmospheric transmission, Tsky which acts like a black
body emitter, as well as attenuating the astronomical signals. These noise contributions, P , are usually
expressed as a temperature, T , where P = kT where k is the Boltzmann’s constant. This sky noise is astrong function of frequency, elevation, the column of wet and dry constituents of the atmosphere, andthe temperature of the atmosphere. The noise from the receivers can also vary for a given tuning withfactors such as cryostat temperature and pointing direction with respect to the local magnetic field (Band
3 receiver characteristic).
To measure these effective temperatures, the ALMA front ends are equipped with an Amplitude Calibration Device (ACD) which can move a hot and ambient blackbody load in front of each receiver feed.
The description of the system temperature electronics is given in Chapter 4. The noise measurementfrom these two loads give the total system temperature, Tsys and the receiver temperature, TRX for each
spectral channel. The combination of these measured temperatures to determine their effect on the observation sensitivity is given in Chapter 9, equation 1.7. The accuracy of these measurements dependon 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 across polarization products)of the Baseline correlator23 . The ACA correlator uses the same spectral configuration (resolution) for
temperature calibration4 .
2 In TDM mode the autocorrelation zero lags can be used to fully compensate for quantization effects on the autocorrelations.
However, in FDM mode which adds a filter bank before the correlations are produced 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-4.
3 At present the online processing time for FDM mode calibrations is also excessively long for large arrays of antennas.
4 In previous Cycles ACA temperature spectrum resolution was arbitrarily limited in the same way as Baseline correlator
observations, although there was not technical reason for this. Opening up the resolution for the ACA in Cycle-4 is intended to ease
the route to processing FDM temperature spectra from the Baseline correlator in future cycles. Note that this includes multiple
spectral windows per baseband.

10.5. OFFLINE CALIBRATIONS141

The temperature measurement include the receiver-weighted contributions from both sidebands, whereas
in the cross-correlation data, LO switching sequences are used to highly suppress the image sideband
cross-correlation. The measured Tsys and TRX must be scaled by a sideband gain factor to produce single
sideband temperatures which can be directly applied to the visibility data to put them in temperatureunits. For cycle 3 scans of 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. For cycle 4 the nominal value of 0.99 for single sideband frequency bands and 0.5 for double side-band frequency bands will be used to convert the systemtemperature.
In principle, every scan could have a system temperature measurement. 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 systematic amplitude offsets between them. The specifications for
Tsys calibrations are to reach 1% correction accuracy.
The online measurements of Tsys and TRX are stored in the CalAtmosphere table in the ASDM datasets,
and are displayed on-line to show measurement problems immediately. The system temperature measurements can also be re-derived offline 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, are applied offline to the correlation data. Assuming that the correlated data
is in units of percentage correlation, multiplication by the Tsys will change the correlated data units to
Kelvin.
Additional Antenna Pointing Checks (P). As discussed in Pointing Models, corrections are made duringobservations in order to reach ALMA’s 0.600 rms pointing accuracy specification. To some extent these
additional pointing calibrations compensate for shortcomings in the antenna metrology systems, anderrors in the static models, for instance due to hardware changes since the last update. These pointing
measurements are automatically included in the observation schedules, with no PI input. At present a
pointing calibration is triggered when moving to a target more than 20 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 offline data flagging of antennas e.g. if a correction
is deemed too large, the measurement uncertainty too high, or the pointing result is missing e.g. because
there was a problem with the antenna or receiver during the measurement.

10.5

Offline Calibrations

The first step in the calibration process is the conversion of the archive ALMA Science Data Model (ASDM)
format (the visibility data in binary form and the meta data in xml form) into a Measurement Set (MS) whichcontains one-dimension tables for all of the data products (Chapter 12). An inspection of the incoming dataat the ALMA site, called QA0, is made as the data are collected to check the data quality, and is discussed in
Chapter 11. Each experiment is then calibrated using the ALMA Pipeline for standard experiments (Chapter13), or more flexible processing is available for non-standard experiments.
On-Line Flagging (F). The online 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 setting is offset morethan a specified amount from the 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. One of the initial offline
calibration steps is to apply these flags.
Calibration-based Flagging (F). During the off-line calibrations, described below, further times and antenna of data flagging are often found. Examples are, noisy edge channels in the spectral windows, lowrelative signal in one antenna compared with the others, phase jumps. In many cases, the characteristics

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESof these bad data can only be seen in the calibrator observations; hence, most flags associated with acalibration scan should be appropriately extended to other sources scans, SPW and baselines.
Bandpass Calibration (B). The response across each SPW will not be flat in amplitude and phase, although
the delay errors that produce a large slope of phase with frequency should have been removed by the apriori and online calibrations. For each SB and tuning, this residual bandpass is determined from a scan ofa bright calibrator source with a known radio spectral index in order to not introduce an amplitude slope
in the bandpass or between SPW’s. After removing any significant phase variations over the bandpass
scan, the casapy task bandpass determines the amplitude and phase the for each antenna/SPW/pol as afunction of frequency, and places the results in a table. The length of the scan and frequency resolution
needed to reach the required bandpass accuracy is discussed in Appendix C. The bandpass with time andwith angle is extremely stable5 so that one bandpass determination per tuning per SB (about an hour)
will not change by more than 0.4%, so that this bandpass can be applied to all of the data in the SB.
Gain Calibration (G). Virtually all ALMA observations use the phase referencing technique to calibrate thetemporal antenna-based variations in amplitude and phase in order to calibrate the target source visibility
data. The larger temporal changes should have been removed with incorporation of the a priori and online
calibrations, discussed above.
The casapy task gaincal is used to determine the antenna-based amplitude and phases for the phasecalibrator scans. If the calibrator is relatively strong, antenna-solutions will be generated for each SPW
and polarization. For a weak phase calibrator, the bandpass observations can be used to align the phasesof all data streams that can then be summed before determining a solution. The combined SPW/pol(often 8 independent data streams) antenna solutions for the phase calibrator is then more sensitive thanthat for each SPW separately.
The plots of the antenna-based amplitudes and phases should be carefully inspected, and some guidelines
are: (1) The antenna-based amplitudes should not vary by more than about 10% over the observation
period, and differ by more than about 20% among the antennas. For antennas with low gain or obvious
drop-outs, check on the data quality: for example, is the Tsys correction anomalous, are there commentsin the observing logs? (2) The 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 is uncertain. This occurs at longer baselines and high frequencies, and flagging
of the target data during these intervals may be useful to improve the image quality. The execution of the
Go/Nogo observations (short observations of a strong source made periodically through the observation
period) to measure the short-term phase variations are used to avoid periods of poor stability.
Absolute Flux Density Calibration(T). The Calibration of the data using the Tsys measurements converts
the raw correlation amplitude into Kelvin. The relationship of the correlation units in Kelvin to Jy iscalled the system equivalent flux density (SEFD), and depends on the antenna diameter and efficiency
that depends on surface accuracy and elevation dependencies. The SEFD is very stable with time andsimilar among the antennas of the same type. For example, the 12-m antennas at Bands 3, 6 and 7 havean SEFD of about 35 K/Jy. This a priori conversion from Kelvin to Jy is accurate to about 5% at Band3, increasing to 15% at Band 9.
In order to derive a more accurate absolute flux calibration scale, a measurement of a source with known
flux density and structure is usually included in the observations. Perhaps, the most reliable Kelvin to Jy
conversion is obtained observing solar system objects of relatively small angular size that have accurate
visibility models versus frequency and baseline length (see Appendix C for the current list used). Also
about 30 bright quasars (grid sources) at Bands 3 and 7 are monitored by ALMA every 10 days, and thederived flux densities (as interpolated in time and frequency) also provide the K to Jy conversion of thevisibility.
Polarization Calibration (p,X). The polarization calibration of the XY and YX correlations is made ona bright quasar that is polarized by at least 3%. The SB observing length needed for the calibration isabout three hours during which the calibrator rotates at least 60◦ in parallactic angle. Two calibration
steps are needed. First, after the XX and YY data are calibrated (bandpass and gaincal), the XY and
5 http://almascience.org/documents-and-tools/alma-technical-notes/ALMATechnicalNotes15_FINAL.pdf

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YX frequency dependence (bandpass and phase offset) for each SPW will not be zero, but reflect theX- and Y-polarization delay and phase difference. This phase frequency dependence is the same for all
antennas, but with opposite phases in the XY and YX data, After these array phase-frequency terms
are then removed, the second calibration step determines the leakage between the X and Y polarizations(called D-terms) for each antenna and SPW. This is a part of the calibration that requires the parallactic
angle change of at least 60◦ during an experiment. There are two leakage terms: one related to thenon-orthogonality between the X and Y feeds and one term related to the ellipticity (X leakage into Y,
and vice-verse) of each feed. Both of the above calibration results are determined from the polarization
calibrator observations alone, but then applied to the entire data set in order to calibrate the polarization
properties for all of the other sources. Another polarization term is related to the average orientation of
the feeds (which is known), but can be measured using a strongly polarized source of known polarization
position.
Investigations are in progress to decrease the three-hour time needed for polarization calibration, regardlessof the time needed for the target integration. One method is to use a quasar of known polarization (manysources must be monitored) in which case only a short observation is needed to determine the D-terms.
Another method is to use the D-term results from previous experiments at the same frequencies since they
do not vary significantly with time. But, these methods will not be available in Cycle 4.
Because the XY,YX response over the primary beam beam is considerably more complicated than thatfor the XX and YY polarizations, only sources with a limited angular extend can be accurately imaged.
It is expected that in cycle 4, the linear polarized imaging will be sufficiently accurate to the the 30% of
the power pattern. For later cycles, full primary beam and mosaicing may be offered.
Circular polarization data is included in the four Stokes parameters that are measured. However, thecalibration accuracy for circular polarization is still uncertain, and the variation of the circular polarization
properties beyond the 80% sensitivity region of the primary beam is significant at the few percent level.
Hence, circular polarization results are not supported. Please contact the ALMA help desk or your local
ARC for more information about circular polarization results from your data.

10.6

Special Calibrations

10.6.1

Phase Referencing, especially above 400 GHz

The quality of a phase-referenced image improves the closer the calibrator is to the target because the systematic
short- and long-term phase differences between the target and calibrator depend roughly on their separation. At
frequencies lower than 400 GHz, calibrators can often be found within 5◦ of any target, and images of dynamic
ranges (peak to rms), if the source is strong enough, can be obtained above 200 with simple phase referencing.
At higher frequencies, calibrators within 10◦ of a random target can be found infrequently for a 12-m arrayobservations and seldom for a 7-m Array observations, and phase-referenced images at these frequencies are ofpoorer quality. In Appendix C, the phase calibrator minimum flux densities needed for detection are given in
Table C.2. The probability of finding a calibrator within a specific distance from a target is given in Figure C.2
for different frequencies and arrays.
The ALMA catalog (see Appendix C) contains over ten thousand sources, mostly found in cm-wave radio
surveys. In order to determine which of these calibrators are sufficiently strong at ALMA bands, special-purpose
ALMA observations, called cone searches, measure their flux density in bands at 100 GHz and 300 GHz. Often
the observing list contains candidate calibrators that are within about ten degrees from upcoming sciencetargets. Most calibrators are quasars that have a radio spectral index, α, in the mm-wave region between -0.5
and -0.8; hence, their extrapolation to 900 GHz from the measurements at 100 and 300 are accurate to about
30%. Also, quasars are variable. If the most recent measurement is more than 90 days from the approximate
experiment date, then a current flux density will be remeasured in an upcoming cone search experiment. The
minimum flux density of a calibrator that can be detected depends on the frequency and total bandwidth ofthe experiment.
Two methods are available to use calibrators that are as close as possible to a target:

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESSPW/Pol averaging. The temporal amplitude and phase variations over a period of several hours amongst
the spectral windows and two polarization are small (1% and 2◦ ) for all ALMA bands. This amplitude
scale and phase offset between streams can be accurately determined from the observations of the bandpass
calibrator scan, and is then applied to the entire experiment of a few hours. The Gain Calibration (G),described in the previous section, can be then be measured for this averaged data stream, with a typicalincrease in the antenna-solution SNR per time by a factor 2.8 (from 8 original data streams). This allows
finding detectable calibrators closer to a target. This technique is called low SNR calibration.
Band-to-Band Calibration. For phase referencing calibration at the higher frequencies (> 400 GHz),
finding a calibrator closer than 5◦ to the target is relatively rare, whereas a closer calibrator at lower
frequencies will be available, and potentially improve the phase referencing accuracy. Thus, the techniqueof band-to-band phase transfer using observations of a calibrator in a lower ALMA Band (3, 6 or 7), andthen scaling the antenna-based phase solutions (G) to the higher frequency band (8, 9, 10) of the target
has been tested.
This inter-frequency calibration is possible because of the excellent instrumental phase stability of ALMA.
Once the phase difference is measured between two ALMA data streams (different SPW, pol and bands),
nearly all remaining phase change are non-dispersive (delay-like) and scale with frequency. The majordelay changes are those in the troposphere and changes in the path length in the antenna system, including
those associated with antenna position errors.
The band-to-band phase scaling requires three short scans to be made at any time during the experiment,t0 : An observation of a bright source, called the diff-gain-source (DGC), at the low frequency, an observation of the DGC at the high frequencies, plus an observation of the low frequency phase calibrator (LF)at the low frequency. The phase difference between the DGC observations gives its instrumental phasedifference at t0 . The phase difference between the DGC low frequency and LF low frequency gives thecorrection to this phase difference for the LF. After removal of this LF phase difference, any further phasechanges over time will scale precisely with frequency.
Since ALMA can observe only one frequency and source at a time, the needed phase differences are
estimated by alternating observations of the DGC at the two frequencies and the LF at the low frequencies.
The temporal phase variation in the troposphere thus introduce errors in the phase difference which add
significant errors in the band-to-band phase scaling from low to high frequencies.
Experimentation with the Band-to-band technique is continuing. However, with the success of the conesearches in finding high frequency calibrators, usually with 10◦ of a target, and the phase offset uncertaintyof the band-to-band calibrations, band-to-band will not be offered in Cycle 4.

10.6.2Phase Calibration with Narrow Bandwidths

When observing a target within narrow SPW bandwidths, a suitable phase calibrator, especially at the higher
frequencies, may not be detectable with a 2-min 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 theexperiment has a bandwidth > 1 GHz (usually because one of the SPW is wide-band), then there will be
sufficient sensitivity to detect in a 2-minute scan to obtain antenna-based solution of a phase calibrator
that is reasonably close to the target. In this case, only one spectral set-up is needed for the entire
experiment.
The calibration method is identical to that described in the SPW/Pol averaging section where: 1) The
amplitude ratio and phase offsets between the SPW’s are determined from the observation of the bandpass
calibrator scan; 2) The phase calibrator phase is determined from the one wideband SPW (or the aggregate)
and then transferred to the narrow band SPW’s. An alternative observing strategy, where all of the target
spectral windows are narrow-band, is described next. But, this requires constant switching between the
narrow-band and wide band configurations over the experiment.

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Band-Width-Switching. If all of the SPW’s are narrow bandwidth, it is likely that a suitably nearby phasecalibrator cannot be detected within a 2-min scan. The strategy for calibrating this set-up is to observe
the phase calibrator with wide-band spectral windows and the target in the desired narrow bandwidths.
This requires the switching of the spectral setup between scans.
The amplitude ratio and phase difference between the wide band SPW and its associated narrow band
SPW is measured by observing a strong calibrator (DGC) in three consecutive scans: wide band, narrow
band, wide band. The calibrations of two wide band scans can be interpolated to the time of the narrow
band scan, removing most of the temporal variations. The amplitude and phase difference between thewide and narrow bands can then be determined.
The advantage of this strategy is that all of the target SPW’s can be used for narrow-band spectroscopy,
whereas the previous strategy must use one wide band SPW for calibration purposes, and is simpler toschedule and easier to calibrate.

10.6.3Astrometry

The absolute positional accuracy of an ALMA image made with normal phase referencing depends on the
resolution and the quality of the phase calibration. In general, the closer the calibrator is to the target, thebetter will be the image registration in the sky. With reasonable phase stability, the registration accuracy of an
ALMA image will be about 1/20 of the resolution, with a minimum of about 5 mas before other instrumental
and atmospheric problems become dominant. This accuracy assumes that all calibrator and target positions
are in the ICRF system and the position accuracy of the calibrator (see the ALMA on-line catalog) is less thanabout 3 mas.
For an experiment in which the target absolute position (or target motion between several experiments)
is the main concern, more precise knowledge of the expected errors, and a suggested observation strategy issuggested. The simplest calculation is the theoretical astrometric accuracy, limited only by the image by thesignal-to-noise (SNR), which is the ratio of radio source peak on the image. This 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 configuration baseline 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 configuration (C40-5), for SN R = 20 and BSL = 1 km,
the theoretical astrometric accuracy is 8.5 mas. However, this SNR calculation alone rarely indicates the true
astrometric accuracy because: (1) beyond a SNR of 100, further accuracy is not likely because of imaging andcalibration uncertainties at the level of 0.01 of the resolution; (2) short-term and medium-term atmosphericphase variations degrade and distort the image and the astrometric accuracy; and (3) large-scale atmosphericstructure over the array and array parameter errors (antenna position offsets) produce astrometric errors thatare > 5 mas or even for the largest ALMA configuration.
Most ALMA long baseline observations and all high-frequency observations will include observations of acheck source. It is a quasar of known position, about the same distance from the calibrator as the target, butobserved less frequently. After the same data reduction as that for the target, the offset of the check source image
position (peak or centroid) from its a priori position is a measure of the astrometric accuracy of the experiment.
The check source offset cannot be used directly as a correction to the target position (more complicated scheme
given below), but provides an estimate of the astrometric error expected for the target. Also, the check source
image coherence (peak / total flux density) is also a good indication of the quality of the calibration. If thecheck source image is badly distorted, then more serious problems are occurring with the data and reductions.

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Virtually all astrometric phase errors are delay-like; that is, scale with frequency. Hence, simply changing
an observation from a low frequency to a higher frequency, other things being equal, will not produce higher
astrometric accuracy with the higher resolution since the phase errors will also increase with the same frequency
ratio.
The scaling of the delay errors with baseline length b, however, is more complicated and consists of threemajor components: (1) short-term (30-sec) variations, mostly from the water vapor cloud-lets; (2) longer-term(3-30 min) variations, from a combination of larger-scale (km-size) water vapor and dry air component over thearray; (3) systematic errors (antenna position errors) and 10-40 km sized atmospheric features over the ALMA
site. Component (1) delay errors scale as b0.3 beyond about 300 km baselines. Component (2) scales roughly
as b0.5 . Component (3) scales as b0.8 . Hence, the gain in astrometric accuracy at the longer baselines is only as
b0.2 .
Recommendations for astrometric accuracy, based on the above phase properties of the ALMA environment/array are:
1. Choose the closest calibrator with an accurate position. The use of the low SNR calibration by combining
polarization and the SPW’s (continuum source) to detect a close calibrator should be considered
2. Make sure a check source is included in the experiment.
3. Choose a frequency for which the SNR at the peak of the target is maximum. Thus, for a thermal object,
Band 7 is a good compromise between flux density strength and system sensitivity. For non-thermal
objects, a lower frequency may be more optimum.
4. Choose as high a resolution as needed to separate any blending of the desired component with othernearby emission. However, do not choose a resolution for which the target is too resolved, so that thepeak flux density decreases faster than the increased resolution.
5. Request better than average weather (low pwv and low phase fluctuations) since the astrometric accuracy
is directly dependent on the phase fluctuation level. For example, the normal Go/noGO criterion of < 30◦phase fluctuations for observations should be reduced to 15◦ . Also request observations at as high anelevation as possible. Astrometric accuracy degrades very quickly for elevations lower than about 50◦ .
For astrometric accuracy better than about 10 mas rms, multi-calibrator observations should be considered.
But, before asking for a more complicated observing strategy, check the following: First determine the optimum
frequency and baseline-length (resolution) suitable for the target. Secondly, make sure that the observations
are sufficiently long so that the estimated target image SNR is > 15; otherwise, multi-calibrator observations
will not be warranted, although a check source should always be included. Finally, make a strong argument for
observations in very good weather, perhaps that is required for the next higher observing band.
The astrometric accuracy can be increased by a factor of two to four by observing the target with two
to four quasars with accurate positions that are near and surround the target. The main phase reference
calibrator should be the quasar that is closest to the target. The other (secondary) calibrators should surroundthe target within a 10◦ radius. These other calibrators need only be observed once every three or four phasecalibrator/target cycles. The analysis essentially determines the positions of the secondary calibrator images
during the experiment (they will change and be offset from their known position my many mas), fits a linear
function of the secondary position offsets versus separation from the phase cal (deriving a linear refraction wedge
over the array), and then corrects the target position for the effects of this refraction wedge.
The normal calibration of these data should be standard in Cycle 4 since the observations and calibrations are
no different than the standard interferometric experiment, except for the use of several check sources. Further
multi-source astrometric analysis of the resulting images or antenna-based gains are the responsibility of thePI.
Please discuss the several observational options and solicit further advice from the help desk at your ARC.
Since there is some restrictions in the cycling of source observations that can be scheduled, the observation
strategy should be discussed.

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10.6.4

147

Long Baseline Observations with Baselines > 2 km

The calibration of long baseline observations is similar to that at the shorter spacings. However, several considerations are:
1. Does the source have sufficiently small-scale structure for long baseline observations? For example, atBand 7 with a 5-km array, the rms image noise in a 600 sec observation over a bandwidth of 7.6 GHz
is 0.1 mJy. For this resolution of 0.0600 , the rms brightness temperature will be 0.3K. For line emission
within a 10 km/s velocity, the brightness sensitivity rms limit is about 50K. This requires an object withmore than 500K temperature in order to obtain sufficient SNR in the line image.
2. If the target is known to have significant emission at the longer spacings, then self-calibration of the target
may be possible. This is more important for long baselines, because the phase variations will be larger,
and the image quality with phase referencing alone may not reach the intended signal-to-noise and image
fidelity. To determine if self-calibration is possible, the correlated flux density of the target at the longer
spacings must be comparable to that needed to detect a phase calibrator, given in phase sensitivity tablein Appendix C, Table 1. For example at Band 7, with 7.5-GHz bandwidth, the correlated flux density ofthe target must be > 125 mJy at the longer baselines. Such precise knowledge about the target may not
be known, but the PI should have some indication of small-scale structure, otherwise the observational
results may be disappointing.
3. The choice of a close calibrator to the target is important in order to removed systematic phase errors at
the longer baselines. If a calibrator is not available within about 4◦ of the target, cone-search observationsor the weak calibrator survey program may be used to find a more optimum calibrator. Also, fast-switchingBand 3 to Band 6 and 7 observations are now being tested for the long baselines.
4. If the source is extended more than 200 at Band 3 (scaling inversely with frequency), then the long baseline
configuration image will not be able to include all of the emission. For Cycle 4, an additional more compact
configuration must be proposed as a second science goal in the proposal.

10.6.5

Total-Power Calibrations

For sources that are significantly more extended than the 7-m primary beam size, twelve-meter antennas (often
the PM antenna) are used to make on-the-fly raster observations that cover the specified source area. The
observing modes are discussed in Chapter 8 and the imaging in Chapter 7.
1. Tsys Calibration: The data are calibrated into brightness temperature in units of Kelvin using the equation
T a∗ = T sysON − T sysOF F /T sysOF F . where T sys is the system temperature and ON and OFF are,respectively, the data on-source (i.e. during the raster scanning) and off-source (observations towards a
defined reference position which should contain only background emission). For very extended sources. it
is important that the reference position is free from target emission and for this reason the off position
may need to be up to several degrees away.
2. Baseline Subtraction: After apply the TsysON-OFF calibration, the off-source regions within the onthe-fly area should be zero for all spectral channels. However, due to the changing and turbulent wet
atmosphere in the primary beam, low-order spectral changes will be present across the spectrum. These
are removed by determining the average spectrum for the off-source positions, and removing them fromall raster positions. Be aware, that this technique will remove large-scale continuum emission. Further
baseline correction can be made after imaging
3. Flux Calibration: In order to calibrate the single-dish data from units of Kelvin to units of Jy/beam, aconversion factor is applied. This Jy/K conversion factor is obtained from periodic calibration measurements (beam maps) of strong sources of known continuum flux density (planets or quasars). The beam
size is also measured.

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Acknowledgments

I thank Satoko Takahashi for contributions to the high frequency sections, Neil Phillips for contributions to
the on-line a priori calibration section, and Catherine Vlahakis contributions to the total power section and byimproving the readability and accuracy of the text.

Chapter 11

Quality Assurance
The goal of ALMA Quality Assurance (QA) is to ensure that a reliable final data product is delivered to thePI, that is, the product has reached the desired control parameters outlined in the science goals, it is calibrated
to the desired accuracy and it is free of calibration or imaging artefacts. The QA analysis will be based on acalibration plan that specifies which observations must be acquired and at which intervals to monitor system
performance and environmental factors as they evolve with time. Furthermore, it will tackle issues related tothe merging of data within each science goal taken with 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 incorrectsource 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 information or 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 Group) that summarizes all the relevant QA information for each of
the different QA stages up to, and including, the final imaging. This report will be included in the data package
delivered to the PI. The QA3 stage will be handled separately, by the ARCs, via JIRA1 tickets created by the
ARC personnel (see below). A more detailed description of the different stages of QA is given below.

11.1

Cycle 4 "Best Efforts"

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 4 projects are completed (specially those with grades B and C), or that specific criteria like sensitivity
1 JIRA is a proprietary issue tracking product, commonly used for bug tracking, issue tracking, and project management

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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 (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 SB observation or sequence of SB repeats. 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). It is expected that during Cycle
4, an upgrade of the AQUA tool will be carried out, allowing the complete computation of the contents of theCalibration Summary files within the AQUA environment using the i formation available in the ASDM files foreach Executionblock.
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 4).
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 value. 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.
For operational purposes, individual SB executions during Cycle 4 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 4 (i.e., forty 12-m antennas on the main array, ten 7-m antennas on the Morita

11.3. QA1

151

Array, and three TP 12-m antennas), and the average system temperatures expected at the frequency of theobservations. Executions with higher rms noise levels than the reference will have fractional execution weights
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, be measured at predefined periods during
the month as “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 productis a set of parameters with errors that are ingested into the TMCDB (up-to-date view of the parameters usedin any observation), so that they can then be used during observations.
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 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).
During Cycle 4, 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 the second half of Cycle 4, so that it can be
included into the overall quality assurance reports. 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 ExecBlocks and joint imaging) are:
Calibration Issues:• 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.

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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).
• 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.
• 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 PI will also receive any modifications to 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, have beenachieved within the specifications listed in section 11.7. QA2_SEMIPASS refers to those datasets that fall shortof meeting the PI requested science goals, but are otherwise of good quality. QA2_FAIL is a temporary stateused during an observing cycle when an observation fails to meet the PIs goals by a significant margin (30%worse) and needs to be scheduled for additional observations. If these data fail to obtain enough additional
observations to pass QA2 by the end of an observing season and they are not grade A proposals, their QA2state 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 thedata 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 PI, the contact scientist ofother 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
the Helpdesk 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 will communicate their findings to the observatory, which will work on solving the problem incollaboration with the ARCs. The result will be communicated back to the reporting investigator. An extensionof the proprietary period of delivered datasets with QA3 issues will be granted based on the policies in the Cycle
4 User Policies document.

11.6

The Quality Assurance Report

During Cycle 4 the Quality Assurance Reports of QA0, QA1 basic QA2 will be accessible to the PIs using
Snoopi. These reports will be generated using the AQUA tool. For the additional QA2 reports, for Pipeline
calibrated datasets, the PI will receive, as part of the data delivery, the Weblogs. For non-standard observing
modes that require manual data reduction, script-generated QA2 reports will be delivered instead.

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153

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 ObsUnitSet 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 4, 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 ExecBlocks that failed
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 in exceptional
circumstances, such as projects with very tight weather or time constraints. If the available 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 to be"significant" in terms of the fractional execution (i.e., more than 0.2) or in terms of sensitivity (i.e., more than
50% of expected Cycle 4 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 through the
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 4 are based on thefollowing:- Antennas: QA0_SEMIPASS for fewer than 19 antennas available in the 12-m Array or fewer than 5antennas in the 7-m Array or fewer than 2 Total Power Array antennas. Situations that will be considered
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 19 antennas in the 12-m Array, or more than
3 antennas in the 7-m Array, or more than 1 Total Power antenna have Tsys values > 50% of the others,
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

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CHAPTER 11. QUALITY ASSURANCE- 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.
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 3/4/6, 7/8, and 9/10, in flux units per beam, respectively), thesynthesized beam shape (i.e., for some of the ALMA cycle 4 configurations2 , the differences with the requested
angular resolution could be as high as 30% in linear dimensions or 69% in area of the synthesised beam on thesky) and the calibration quality (phase RMS of 5 degrees after calibration, and absolute flux scales within the
ALMA specifications). For the individual MOUS that must be combined at the GOUS level, the RMS values
quoted above should be scaled by the relative sensitivities of the configurations, using the most compact 12-m
Array configuration as reference.

2 During Cycle 4, 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.

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. This is done in several
cycles to solve interdependencies between the different software components. Once all the components areready, the Executive also handles asynchronous events from several of the subsystems and responds to themaccordingly. Among the events, the Executive also publishes a list of error conditions to the attention of theoperator and the requests for display of the Control, Telescope Calibration and QuickLook subsystems.
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 LanguageÕÕ 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 Early Science, 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.

155

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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, it is dispatched to the Control subsystem.
Control parses the SB XML document into python objects (with the help of the SSR scripts1 for a given observing
mode, which interpret the XML metadata in the SB), and executes the observing script selected in the SB,
which reside in the Science Observing Scripts module. The observing script uses the information from the
SB as input to determine the necessary execution sequence, which is commanded to Control as sequences ofscans and subscans. The scan and subscan specifications specify for each subscan the tuning, phase center andantenna pointing, calibration device position, intent metadata (to convey the purpose of the scan/subscan), andother 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. TelCalpublishes results from calibration scans it reduces, which are sent to the archive as calibration tables, andreceived 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 charge of synchronization of
the actions of all antennas (scanning, source acquisition, etc) and the correlator to within 48ms (Timing Event(TE)). Control is also in charge of storage of data from all monitor points set in the hardware of the ALMA
1 SSR stands for “Software Science RequirementsÕÕ. It is a collection of Python scripts that read relevant parameters from the
XML metadata of SBs, and pass all the relevant information to the CONTROL software to execute the needed observations. SSR
scripts also define the cadence of all the calibration observations during the execution of the SB.

12.2. THE ALMA SCIENCE DATA MODEL

157

array.
Each run of an SB produces an Execution Block (EB) that is stored into the archive through two parallelpaths 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 is directly stored into the archive. Furthermore, it also provides calibration data to
the TelCal and QuickLook subsystems for calibration reduction and 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 isclear from the list of roles above that Data Capture is a very complex module; it has to handle Correlator andbackend data in addition to supporting (source information, spectral set-up, etc), and monitoring data which
are needed for data reduction (weather, pointing, etc). All this information originates in different hardware andsoftware elements, each of which can be sampling at different rates and with limited view of the behavior andstate 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.

12.2

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 in
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.

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tables. 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. The list of these associated tables is being upgradedas 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.

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.

Chapter 13

Pipeline Processing
13.1

Introduction

The ALMA Science Pipeline is used for the automated processing of ALMA interferometric and single-dish data.
It is released as part of CASA, where the current Pipeline tasks are denoted by the prefixes: h, hif, hifa, hifv,
and hsd (see Table 13.1). The Pipeline is data-driven, such that different Pipeline processing can automaticallyoccur for different ALMA Observing Modes and different data quality. The algorithms employed to influence
how automated data processing proceeds are referred to as the Pipeline Heuristics, and the outcomes of theheuristics (e.g. whether to apply a calibration table or not) are stored in the Pipeline Context. At any given
point during Pipeline processing, the Pipeline State is therefore recorded and known by the Context. The
Pipeline has been designed to be highly flexible. It has been developed such that Pipeline tasks can be removed,
added or rearranged from the processing. It is possible to override the calibration tables created by the Pipeline
and introduce self-made calibration tables into the processing, by editing the Pipeline State/Context at theappropriate processing point. This enables "mix and match" of standard CASA tasks and Pipeline tasks.
The ALMA Pipeline has been used in Science Operations since October 2014, during Cycle 2, and continues
to evolve to include new capabilities and improved methods. At present, the Pipeline can be used in theprocessing of ALMA interferometric 7-m and 12-m Arrays. Processing of single-dish (total-power) data isalso commissioned for use on Cycle 3 data onwards. Standard Pipeline processing recipes are used in Science
Operations. In the future the Pipeline will also have the capability to combine the data taken using multiple
ALMA arrays.

13.2

Pipeline In ALMA Operations

13.2.1

Pipeline Triggering

The Observing Unit Set (OUS) structure of an ALMA Project determines the number of times, when and how
the Pipeline is triggered for that project and which data products are output. The Pipeline triggers at thecompletion of each ALMA OUS. Figures 13.1, 13.2 and 13.3 indicate the different number and types of Pipeline
processing needed for 3 different Science Goals. The Pipeline is not commissioned to have more than one SB inan OUS.

13.2.2

Pipeline Execution

The Pipeline is executed in ALMA Operations via the Pipeline Processing Request (PPR). The PPR is an xml
file generated by executing the pipeline infrastructure command pipelineMakeRequest. The pipeline infrastruc-

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task

task typedescriptionh_Common tasks

hif_Interferometrycommontasks
Interferometry
ALMA
tasks
Interferometry
EVLA
tasks
Single-dishtasks

Pipeline tasks used in the calibration andimaging of both interferometry and single-dishdatasets
Pipeline tasks used in the calibration and imaging
of both ALMA and EVLA interferometry datasets

hifa_
hifv_
hsd_

Pipeline tasks used in the calibration and imagingof ALMA interferometry datasets only
Pipeline tasks used in the calibration and imaging
of EVLA interferometry datasets only
Pipeline tasks used in the calibration and imagingof single-dish datasets only

Table 13.1: Pipeline Task Types
ture is a set of commands for the automated running of the pipeline within the Observatory. As it is only
needed for this internal purpose, the pipeline infrastructure is not part of publicly-released software. In the
Observatory, the PPR is executed within CASA and by default it will process a completed ALMA OUS. During
the execution of the Pipeline, a python script of Pipeline tasks, which is equivalent to the PPR, is written. This
script can be used to perform Pipeline calibration of that dataset, and it is provided with each ALMA deliveryof Pipeline processed data.

13.2.3

Pipeline Runtime Database-querying

The ALMA Pipeline can query the ALMA Calibrator Catalog at runtime to obtain the fluxes of regularly
monitored quasars used as flux calibrators.

13.2.4

Pipeline and the ALMA Quality Assurance Process

Only data labeled QA0_PASS are processed by the ALMA Pipeline during ALMA Operations. The Pipeline
infrastructure command pipelineMakeRequest by default picks up all the QA0_PASS data for a given OUS to
include in the processing, but QA0_FAIL and QA0_SEMIPASS data will not be processed. This is because
the Pipeline has a certain minimum requirement on the calibrators available to it during an Execution Block or
an Observing Session and on the data quality. ALMA Execution Blocks and Sessions that do not meet thesecriteria are given QA0 labels such that these data do not enter the Pipeline.
The Pipeline performs the data processing needed to perform ALMA Quality Assurance 2 (QA2), i.e. itcalibrates the data and performs imaging. This results in data products that can be delivered to the PI andstored in the archive. However, these products will only be delivered and ingested into the Archive if they
pass QA2. In order to determine whether a Pipeline-processed ALMA OUS passes QA2 or not, the Pipeline
produces Quality Assessment (QA) scores which reflect the data quality and how well Pipeline processing has
proceeded. The details of how these QA scores are determined are described in the ALMA Pipeline Quickstart
Guide. The Pipeline QA scores, and the algorithms used to determine them, will be made available to the
ALMA Quality Assurance tool (AQUA) for to aid in assessment of QA2 status. The Pipeline QA scores are
additionally displayed to staff and users via the Pipeline Weblog, a set of html pages that provides plots andinformation on the Pipeline processing of each OUS.

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13.2. PIPELINE IN ALMA OPERATIONS

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 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 13.2: Pipeline processing of a Science Goal containing multiple ALMA configurations or arrays (e.g.
12-m, 7-m or TP). The data from the different configurations/arrays is processed independently in two separate
Member OUSes, with science products created for each MOUS. Once the processing of the MOUSes is complete,then they will be processed together to form a combined science product from the two arrays (since they arepart of the same Group OUS). Therefore this Science Goal would result in 3 Pipeline processings, with 3 sets ofscience products delivered to PI. (Note that the Pipeline is not yet commissioned for Group processing/arraycombination).

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13.2. PIPELINE IN ALMA OPERATIONS

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 13.3: 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 2 Pipeline processings, with 2 sets of science products delivered to PI.

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CHAPTER 13. PIPELINE PROCESSING

Standard and Non-standard Observing Modes

One of the definitions of whether an ALMA Observing Mode is labeled as a standard or a non-standard mode
is whether the ALMA Pipeline has been commissioned to calibrate that Observing Mode in ALMA Operations
or not. The standard and non-standard modes at Cycle 4 are listed in the Cycle 4 Call for Proposals.

13.3

Pipeline Processing of an ALMA OUS

13.3.1

Overview

An ALMA OUS may contain a number of different ALMA Execution Blocks. During data calibration, each
execution block is calibrated independently unless the execution blocks form part of the same Observing Session.
In this case only, one or more aspects of the calibration from one execution block may be applied to another. In
the calibration processing, the Pipeline runs Execution Blocks sequentially through Pipeline tasks. For example,
the Pipeline first imports the data from each Execution Block, it then performs deterministic flagging on each
Execution Block, it then moves onto the next task etc. This proceeds until all the calibration steps have been
performed for each Execution Block. At this point, all the calibration tables stored in the Context for each
Execution Block are applied to each one using the Pipeline task hif_applycal. The calibration tables are only
applied at the end point of the calibration, prior to that they have always been applied "on the fly" during
Pipeline tasks. For imaging of the calibrators and science target(s) observed in an OUS, the data from all
Execution Blocks is now imaged together for each target. During Cycle 4, some proportion of ALMA OUSes
may be calibrated using the Pipeline but imaged manually. In other cases the pipeline will be used to perform
both calibration and science target imaging. It is also possible that manually-calibrated data will be imaged
using the Pipeline.

13.3.2

Pause after Data Import

In current practice, the ALMA Pipeline does not necessarily run straight through after triggering. The firsttime that the Pipeline is triggered, it will perform the import of each Execution Block of ALMA data only, withno calibration. The reason for this is multi-fold. Firstly, it is useful to check at this point the flux calibrator
fluxes that have been obtained for any quasar flux calibrator. These values can be overridden if desired at thispause. Secondly, any fixes needed to the ALMA data prior to calibration can also be performed at this time.
Thirdly, if the Pipeline has previously been run and it was noticed that the addition of extra manual flagging
would improve the data reduction, the manual flagging can be added at this point.

13.3.3

Output of the Pipeline Processing

The main output of the ALMA Pipeline is calibrated visibility data and associated imaging products. Anotherimportant output is the Pipeline WebLog. Current lists of Pipeline products and a detailed description of
Pipeline products at Cycle 4 are given in the document ALMA QA2 Products.

13.4

Pipeline Initialisation & Calibration Table Editing

The pipeline can be initialised in one of two ways: by creating a new pipeline state (h_init) or by loading a
saved pipeline state (h_resume). h_init creates an empty pipeline context but does not load visibility data
into the context (for e.g. interferometry datasets hifa_importdata can be used to load interferometry data).
The Pipeline State is saved at any point with h_save. To view and edit the pipeline state/context then e.g.
for interferometric processing hif_show_calstate, hif_export_calstate and hif_import_calstate can be used, see
the Pipeline Reference Manual. It is these tasks that should be used in the case where it is wanted to replacea Pipeline-generated calibration table with a self-generated table.

13.5. GENERAL INTERFEROMETRIC ALMA DATA PROCESSING

13.5

General Interferometric ALMA Data Processing

13.5.1

Data Import & Calibrator Flux Retrieval

165

The Pipeline task hifa_importdata imports data into the interferometry pipeline employing the CASA task
importasdm. It loads the specified visibility data into the Pipeline Context, unpacking and/or converting it asnecessary. The visibility files may be ASDMs, tar files of ASDMs, measurement sets (MSs), or tar files of MSs,
If ASDM files are specified, they will be converted to MS format.
The import is set to apply binary data file flags. The data import stage also performs several checks on
the data. One of these checks is which scan intents are present in the dataset. Scan intents (e.g. BANDPASS,
PHASE) indicate to Pipeline throughout the processing the purpose of each scan observed in the dataset. Notethat an incomplete set of calibration intents will not cause Pipeline to exit at this point. It will affect the QA
score for this stage of the Pipeline however. See the Cycle 4 Pipeline Quickstart Guide for a description of how
the Cycle 4 QA scores are calculated.
Several files are created during the data import stage. For each ALMA execution block/ASDM a file ofthe flags provided by the online system will be created. The Pipeline will also create files to which additional
manual flagging can be added to the Pipeline run. If the manual flag files are already present, then Pipeline will
not overwrite them by default but will use the existing files in the directory. Own-named flag files can also beused, see the Pipeline Reference Manual information for hifa_flagdata. Whatever manual flagging needs to be
added must be in place before hifa_flagdata is run. In ALMA Science Operations, this is run directly after the
Pipeline "Pause After Import". In ALMA Operations, the Pipeline is run once without manual flagging added.
The results of that run are examined by an ALMA Data Analyst, and if it is needed to add manual flagging,then the Pipeline is re-run with the manual flagging added before hifa_flagdata e.g. at the Pause after Import.
Note that, although the Pipeline can be started from MSes, it is always best practice to import data thatis planned for Pipeline processing from ASDMs. This ensures that all the information needed by the Pipeline,
such as which Session different ASDMs have been acquired from, has been correctly input into the Context.

13.5.2

Deterministic & Manual Flagging

The Pipeline applies several different types of flagging at this stage by default. These are:• autocorrelations• flags listed in the online flag files• flags to data which have been affected by shadowing• flagging to strip the dataset of data labelled with un-needed scan intents, such as POINTING, FOCUS,
ATMOSPHERE, SIDEBAND RATIO• flagging the edge channels of low-spectral resolution (TDM) data
• the manual flagging

13.5.3

Flagging lines in Solar System Object Flux Calibrators

The Pipeline contains a dictionary of the frequency ranges of lines that are commonly seen in Solar System
Objects (SSO). It is possible to add lines to this dictionary via text file. If Pipeline detects these frequencies in
an SSO flux calibrator, then it flags the lines unless the line frequency range exceeds a threshold fraction of thespectral window. If the threshold is exceeded, the Pipeline does not flag the line for technical reasons. Instead,it sets the parameter refspwmap such that this window will not be used in the later flux scale transfer to thebandpass and phase calibrator.

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CHAPTER 13. PIPELINE PROCESSING

Raw Data Flagging

The task hif_rawflagchans task flags deviant baseline/channels in the raw data. Data from the bandpass, phaseand flux calibrators are examined and, where bad frequency ranges are determined on a per baseline basis, thesedata are flagged throughout the dataset. For more information on the parameter settings for this task, see thePipeline Reference Manual.

13.5.5

Reference Antenna Selection

The Pipeline creates a ranked list of reference antennas based on proximity to the centre of the array and degreeof flagging.

13.5.6

System Temperature Calibration & Flagging

The system temperature (Tsys ) calibration table is generated by the Pipeline task hifa_tsyscal, which employs
the CASA task gencal. This table is then flagged by the task hifa_tsysflag. Flagging of Tsys spectra takes placebecause of high median values, high median derivative (ringing), edge channels, field shape (Tsys spectra whose
shape differs from those associated with measurements made for the bandpass calibrator), and on the basis of
spikes/birdies.

13.5.7

Antenna Position Corrections

The Pipeline task hifa_antpos can correct antenna positions via the antennapos.csv file.

13.5.8Offline WVR Calibration for 12m Array Data

The Pipeline generates a gain table based on the Water Vapour Radiometer data in each ALMA Execution Block.
It then applies the wvr calibration to the data specified by ’flag_intent’, and calculates flagging views showing
the ratio phase-rms with wvr/phase-rms without wvr. Thirdly, it searches the flagging views for antennas withanomalous high values. If any are found, then it recalculates the wvr calibration with the wvrflag parameter set
to ignore their data and interpolate results from other antennas according to maxdist and minnumants. Fourth,
if the overall QA score for the final wvr correction of a visibility file is greater than the value in accept_thresholdthen it makes available the wvr calibration file for merging into the context and for use in the subsequent
reduction.

13.5.9Gain Flagging

Antennas with low or high relative amplitude gains are flagged by the Pipeline. The parameter thresholdsettings that determine which solutions are flagged are given in the Cycle 4 Pipeline Reference Manual. The
CASA tasks employed during the heuristics for this step are bandpass and gaincal. The amplitude gain solutions
are also flagged on the basis of deviant rms.

13.5.10

Bandpass Calibration

The Pipeline task hifa_bandpass includes use of the CASA tasks gaincal and bandpass. Firstly a phase-only
gaincal is run on a timescale shorter than the scan timescale (the scan timescale is the time spent on a source
before switching to a different source). The solution interval is determined by the expected signal-to-noise ratio(SNR) on the bandpass calibrator. While it is common practice to perform this using a narrow frequency rangeof each spectral window only, in case of delays (slopes in phase vs frequency), at ALMA it is generally fine to13.5. GENERAL INTERFEROMETRIC ALMA DATA PROCESSING

167

include up to the whole frequency range in this gaincal. The solution table created here will only be appliedon the fly when creating the bandpass solutions, other than that it is discarded. The reason to perform this“phase-up” of the bandpass calibrator is to fix any phase de-correlation. The CASA task bandpass is then run tocreate the bandpass solutions. Pre-averaging across several frequency channels can take place via the bandpass
solint parameter; the amount of pre-averaging is calculated depending on the expected SNR of the bandpass
calibrator (see low S/N heuristics section below).

13.5.11

Mapping Phase Gain Solutions

Phase gain solutions derived from broad spectral windows can be applied to the data in narrow spectral windows
by the Pipeline, in order to improve calibration results. The hifa_spwphaseup task computes the mapping needed
and also creates a calibration table that removes bulk phase offsets between the different spectral windows using
the bandpass calibrator (i.e. it "phases them up").

13.5.12

Setting the Fluxscale

To set the absolute fluxscale, either a solar system object or a regularly-monitored quasar will have been used.
For a solar system object, the Butler-Horizons-JPL models are used, whereas the flux of a quasar flux calibrator
will have been obtained already. The CASA task setjy is then used by the Pipeline to set the fluxes of the model
visibilities for the flux calibrator.

13.5.13

Deriving the Fluxes of the Phase and Bandpass Calibrators

If the absolute flux calibrator is quite resolved, then only a subset of the ALMA array will be used to determine
the fluxscale. In addition a limited uvrange is used. This is because the model is more trusted for the shorter
baselines. This is performed by using the CASA tasks gaincal and fluxscale.

13.5.14

Time Gain Calibration

The complex gains are derived from the data column (raw data) divided by the model column (usually set with
hif_setjy). The gains are obtained for the specified solution intervals, SPW combination and field combination.
One gain solution is computed for the science targets and one for the calibrator targets. Good candidatereference antennas can be determined using the hif_refant task. Previous calibrations that have been stored in
the pipeline context are applied on the fly.

13.5.15

Applying the Calibration

The Pipeline uses the CASA task applycal to apply the calibration tables to the dataset. A strict setting of
applycal is used by default in the Pipeline (any data without full calibration available is flagged. This conservative
approach is taken in order to prevent any non-properly calibrated data getting through the Pipeline. For phasesolutions, the mapping determined by hifa_spwphaseup is used.

13.5.16

Imaging

At minimum, the Pipeline images the bandpass and phase calibrators as a diagnostic check, producing an image
per spectral window. The Pipeline can also perform imaging of the science target(s), either in the same Pipeline
run as the data calibration or starting from measurement sets that have already been calibrated. Data thatwere not calibrated by the Pipeline can therefore be run through the imaging stage only. In some cases, Pipeline
calibrated datasets may be manually imaged by ALMA staff however.

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Both for calibrator and science target imaging, the Pipeline uses the task hif_makeimlist to determine whichsources need to be imaged. This task also determines, the phase centre, cell size and image size (imsize) to be
used.
The imaging is then performed using the Pipeline task hif_makeimages. This task employs the CASA task
tclean to perform imaging, and the tclean commands used, including parameter settings, can be found in the
Pipeline casa_commands.log. The task hif_findcont identifies line-free frequency ranges of the dataset withwhich to form the Pipeline continuum products. The Pipeline additionally creates images of the continuumsubtracted dataset. Note that the Pipeline image cubes always use a frequency, rather than velocity, axis.

13.5.17

Exporting the Products

The hif_exportdata task exports the data defined in the pipeline context and exports it to the data products
directory, converting and or packing it as necessary. The current version of the task exports the following
products• an XML file containing the pipeline processing request• a tar file per ASDM / MS containing the final flags version• a text file per ASDM / MS containing the final calibration apply list
• a FITS image for each selected calibrator source image• a FITS image for each selected science target source image• a tar file per session containing the caltables for that session• a tar file containing the web log• a text file containing the final list of CASA commands• a python script that can be used to calibrate the data
• a python script that can be used to restore raw data directly to calibrated measurement set(s)13.6

Low SNR Heuristics in Interferometric Pipeline Processing

If there is a low signal to noise ratio on one or more calibrators then the Pipeline can currently mitigate this inseveral ways.

13.6.1

Mapping the Gain Solutions from Broad Spectral Windows to Narrow
Ones

In datasets containing one or more narrow spectral windows and a weak phase calibrator, then the gain solutions
derived for the narrow spectral window(s) may be significantly lower quality than those determined for any
broader spectral windows in the dataset. The Pipeline can therefore apply the gain solutions determined forbroad windows to narrower ones. However, care must be taken when performing this as there may be a phaseoffset between the solutions for different windows, particularly when these windows are not within the same
ALMA baseband. Therefore, the observation of the usually stronger and higher SNR bandpass calibrator isused to determine the phase offset between the windows enabling correction for this.

13.7. TOTAL POWER DATA PROCESSING

13.6.2

169

Using the Gain Solutions Obtained from the Aggregate of all Spectral
Windows

In some datasets, there is low SNR on the phase calibrator and all of the spectral windows used were narrow. For
cases including this then the aggregate gain solution obtained from using all spectral windows to determine thesolutions can be applied. Again the Pipeline ensures that phase offsets between the gain solutions for individual
spectral windows and the aggregate solution is corrected for by determining this using the bandpass calibrator.

13.6.3

Additional Bandpass Pre-averaging

For low SNR on the bandpass calibrator, the frequency pre-averaging can be performed using a larger frequency
averaging interval. The solution interval in the pre-bandpass gaincal can be lengthened.

13.7

Total Power Data Processing

In Cycle 4, there will be a maximum of one single dish (Total Power) Science SB per Member OUS. The Science
SB will have one or multiple science targets, each with a corresponding rectangular observing field. Once allof the required number of Execution Blocks (EBs) for the Science SB are completed and the status changes to“FullyObserved”, the Single Dish Pipeline is triggered.
In Cycle 4 spectral line observations in Bands 3 to 7 are offered as a standard observation mode1 , the Pipeline
always performs Tsys and blank-sky calibration, Kelvin-to-Jansky conversion, baseline subtraction, subsequent
flagging, and imaging, to process data for science targets. The Kelvin-to-Jansky factors, which are obtained by
the Observatory, are applied per antenna per spectral window during calibration inside the Pipeline processing.
The Observatory has compiled amplitude calibrator (planets and bright quasars) observations with 12m
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. The Kelvin-to-Jansky
conversion factor is then derived from these trends. The Observatory stores the derived factors in an internal
database containing the relevant parameters which include observational information such as temperature andelevation of the calibrators when observed. Note that no amplitude calibrator image will be included in thedata products. Instead, a list of the applied Kelvin-to-Jansky factors will be added to the delivered package for
the PIs.

13.7.1

Data Import

The Pipeline first loads the ASDM into the pipeline context, unpacking and/or converting to measurement set(MS), the same as for the data import in Interferometric Pipeline processing. At the same time as importing
the data, the binary data file flags are applied to the imported MSes, and a flag file containing online flagging
information and a flag file template for manual flagging per MS, are generated.

13.7.2

Deterministic & Manual Flagging

The Single Dish Pipeline applies several different types of flagging at this stage by default. These are:• flags listed in the online flag files• flags of data which have been affected by shadowing• flags of un-needed intents such as POINTING, FOCUS, SIDEBAND, and ATMOSPHERE.
1 The standard and non-standard modes in Cycle 4 are listed in the Cycle 4 Call for Proposals.

170

CHAPTER 13. PIPELINE PROCESSING• flags of edge of channels of low-spectral resolution (TDM) data
It is also possible to insert manual flagging if further flagging is needed for the Pipeline-processed data.

13.7.3Tsys and Sky Calibration Tables

The Pipeline creates Tsys calibration tables after heuristic flagging is applied. Each of spectral windows for thescience targets is automatically mapped to the corresponding frequency-matched Tsys spectral window.
The Pipeline also generates the blank-sky calibration tables (so-called sky calibration tables) that contain acollection of spectra of the ‘OFF’ (i.e. reference) positions, linking to each ‘ON’ (i.e. on-source) spectrum.

13.7.4

Kelvin-to-Jansky Calibration Table

The Kelvin-to-Jansky factors are derived by the observatory (i.e., independently from the Pipeline Operation)and inserted in a file which will serve as input to the Single Dish Pipeline. The Pipeline generates Kelvinto-Jansky calibration tables using that input file. The users can notice that the WebLog gives a list of the
Kelvin-to-Jansky factors applied to the data in the the summary page.

13.7.5

Applying the Calibration

The Single Dish Pipeline applies the Tsys , sky and Kelvin-to-Jansky calibration tables to the dataset: i.e., thePipeline calculates (ON −OF F )/OF F ∗Tsys ∗αJy/K , where ON and OF F are spectra of ON and OFF positions,
respectively. Tsys is system temperature, and αJy/K is a Kelvin-to-Jansky factor. At the completion of thisstep, the resulting data have intensity units of Jy. Note that in case that no Kelvin-to-Jansky factor is provided
to the Pipeline, the Pipeline just interprets αJy/K = 1.0, and the units appearing in the WebLog and in the
Pipeline products will be in Jy.

13.7.6

Automated Line Identification and Baseline Subtraction

The Single Dish Pipeline generates baseline fitting tables and subtracts low-order baseline from the spectra.
The Pipeline employs an automated line-identification algorithm using clustering analysis. Line identificationis performed on the integrated data of all EBs (per spectral window). The algorithm searches for emission(or absorption) line candidates having a brightness above a certain threshold (based on the median absolutedeviation) on the integrated spectrum per space-domain grid cell per time-domain group. The candidate
emission (absorption) lines are first screened by whether those lines are identified also in neighbouring grids anddifferent time-domain group. The clustering analysis is performed on the central frequency and line-width for
all candidate emission, to determine the emission lines to be masked. Then the central frequency and line-width
for each emission lines are estimated by taking into account the spatial distribution of the two parameters.
The corresponding channel ranges are masked in the spectrum. The Pipeline analyzes each emission-masked
spectrum though Fast Fourier Transform to obtain the power spectra, which is used to determine the numberof segments for cubic spline fitting. Finally Pipeline performs baseline fitting using a cubic spline. See “ALMA
Science Pipeline Reference Manual” for more detailed explanation on the line identification algorithm. This
step (line finding and baseline subtraction) and the subsequent flagging step are executed twice in the standard
procedure to improve accuracy of the line finding algorithm.
The derived baseline information such as parameters for line finding, fitting function, and fitted baseline are
filed in the baseline calibration tables.

13.7. TOTAL POWER DATA PROCESSING

13.7.7

171

Baseline Flagging

The Pipeline examines spectra before and after baseline subtraction based on baseline rms and Tsys , andgenerates flag tables containing a collection of flagged data to apply them just before the imaging step. The
baseline rms is calculated using emission-free channels (excluding masked channel of emission line by line finding
algorithm). The flagging is done per spectrum (per dump), according to the following criteria:• abnormally large Tsys
• remarkably large baseline rms compared to other spectrum• rapid increase of baseline rms over time, based on deviation from the moving average of baseline rms• significantly large baseline rms relative to the expectation computed for the observed Tsys
The threshold for each criteria are determined by Pipeline heuristic. See “ALMA Science Pipeline Reference
Manual” for more detailed explanation on the criteria.

13.7.8

Imaging

At the imaging step, for the science target, the Pipeline produces a data cube with the native frequency
resolution for each spectral window per field. Note that all imaging parameters are set to a cell size of 1/9 oftheoretical beam size, and a grid function of Spheroidal Function.

13.7.9

Exporting the products

The final step of the Pipeline processing is to export the image cube defined in the pipeline context to thedata products directory, converting and or packing it if necessary. The current version of the task exports thefollowing products:• an XML file containing the pipeline processing request• a tar file for each ASDM / MS containing the final version of flags• a text file for each ASDM / MS containing commands to apply calibration tables• a FITS image for each science target source for each spectral window• a tar file containing all calibration (Tsys , sky, and baseline) tables for each MS to be applied• a tar file containing the WebLog files• a text file containing the final list of CASA commands• a python script containing the final list of Pipeline tasks can be used to calibrate the data
• a text file containing the Kelvin-to-Jansky factors

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CHAPTER 13. PIPELINE PROCESSING

Chapter 14

Data Archiving
14.1

Introduction

The ALMA archive is at the centre 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 (hereafter AFA), which provides
the core persistence functionality and into the ALMA Science Archive (hereafter ASA). The latter holds asmall subset of metadata of the AFA in a relational database and provides access to external interfaces like theArchive Query interface and in the future Virtual Observatory (VO) tools. The storage architecture is basedon 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 (http://almascience.org/documentsand-tools).

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 capturing 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 200TB of data. The OT will
issue a warning message when the data rate exceeds six times the average data rate. In such cases, PIs may get
contacted in Phase 2 in order to see whether a reduction of the data-rate is possible.
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

173

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CHAPTER 14. DATA ARCHIVING

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.

Figure 14.1: The ALMA archive is in the centre of the ALMA data flow.
As soon as data is taken and has passed 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 information needed to describe
the observations, including date and time, source coordinates, frequency settings for each spectral window, andspectral 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 users’ 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
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 data

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14.4. ARCHIVE QUERY

delegation 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 public raw data, although
they can choose to also see the metadata per project. On the results page, users can sort and subfilter the results
and add or remove columns from the result table to narrow their search.
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 . Modifications of the URL used
for the exporting of 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. Both tools mentioned
are developed externally and are not part of the official ALMA software.

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 to
1 http://www.star.bris.ac.uk/~mbt/topcat/
2 https://astroquery.readthedocs.org/en/latest/alma/alma.html

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CHAPTER 14. DATA ARCHIVING

Figure 14.3: The ALMA Science Archive Request Handler
check 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.
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.
• 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 to select individual files for download. Only the data deliveries that users havepermission to download can be selected. If they are not authorized 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.

Appendix A

Antennas
A.1

Design and Properties

At the end of the construction period ALMA will have in total 66 antennas, 54 with a diameter of 12 m and12 with a diameter of 7 m. Four of the 12 m antennas will be equipped with a nutating subreflector total
power observations. The four antennas used for total power observations and the twelve 7 m antennas will
together form the Atacama Compact Array (ACA). The ALMA antennas are manufactured by three different
contractors. These are VertexRSI (North America) which will provide 25 12 m antennas, Alcatel Alenia Space
European Industrial Engineering MT Aerospace (AEM, Europe), which will provide 25 12 m antennas and
Mitsubishi Electric Corporation (MELCO; East Asia), which will provide the four 12 m total power antennas
and the twelve 7 m antennas (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.

177

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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 4 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 panell 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).

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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 the antennas when they are pointed to the viewer. 2
A gear drive consists of a main motor driving a series of connected reduction gears (i.e., gearbox) that do theactual precision work. A direct drive system does not require of such gears and takes the power directly. The
direct drives used in ALMA antennas are magnetically supported. 3 Jointly used to correct in semi-real time
the pointing of the antennas, under a wide range of environmental 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 Plastic (CFRP) andInvar to achieve the best compromise between stiffness, robustness, smoothness, and low thermal expansion (seeTable A.1 for a summary of properties). Common to all antennas is that they have a steel pedestal.
All antennas have builtin 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

180

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/mstiffness includes the inserts, the concrete pad and the soil. This does neither include the kinematic mountlower part nor it includes 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 antenna is 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

181

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 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 10 cm) to achieve the required antenna positioning accuracy. The antennas can be positioned
to within a few millimeters, ensuring accurate placement on the antenna foundation pads. More informationon the transporters can be found on the ALMA EPO pages1 .

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

A.4

Cryostat

The ALMA frontend consists of a large closed-cycle 4 K cryostatt 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/about-alma/how-does-alma-work/technology/transporters

182

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 frontend, and is
described in Section A.5. Figure A.4 and A.5 show overviews of the front-end unit, with the cylindrical cryostat
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 frontend, showing WCAs.

A.4. CRYOSTAT

183

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

184

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 frontend (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 (solar observations are not available during Cycle
4). The arm is designed to allow the two loads to be placed in the path of any of the receiver beams (FigureA.8). Typically it takes 2 seconds to move the arm from the park position to the position where one of theloads 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 frontends.
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.).

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A.5. AMPLITUDE CALIBRATION DEVICE

Figure A.8: Top view of an ALMA frontend showing the robotic arm of the ACD retracted during normal
observations or on top of one of the frontend 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 τs −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)

186

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 4.

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 1Hz. 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”

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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., PWV). 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 sometechniques are being currently studied to try to measure them (including thermal sounders of the atmospherethat use the profiles of the emission of the oxygen molecules). The brightness temperature variations of the skythat 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 to allow corrections of thepath fluctuations (in µm):

δLcorrected ≤ 1 +w 
10µm + 0.02δLraw .
1mm

(A.5)

where w is the total water vapor content along the line of sight, and Lraw the total fluctuations observedat any given time. Therefore, this formula includes the expected error of about 2% in measuring 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-topeak 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 shownin 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

188

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 product sent to the ALMA Control system are time-stamped, calibrated measurements ofthe 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. It is envisioned that corrections
at the scales of the sampling rates of the WVRs will be possible at the correlator and that refinements for longer
timescales will be done offline in CASA using the wvrgcal tool.

Appendix B

The LO and IF System
In this Appendix we describe the signal path and LO chain used between the frontends and correlators, andhow these are used to define spectral setups for the user. To the system, a spectral setup effectively consists ofthe settings of the local oscillators and 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 just in terms of the observing frequencies and spectral resolutions, and there is no need toworry about the details of each LO setting. For full details of the OT and how to use it, see the OT User andReference Manuals, available from the 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 jump to Chapter 6.

B.1

Functions of the LO & IF system

In the signal path from Frontend to correlator, ALMA uses three frequency conversions, and the associated LO
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. Suppression of the image sideband or, 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 Walsh patterns.
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.
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 Correla1 http://almascience.org/documents-and-tools/

189

190

APPENDIX B. THE LO AND IF SYSTEM

tor2 . Section 6 shows how to setup the system to observe spectral lines (particularly multiple spectral lines) andcontinuum. We then discuss some other aspects of frequency setups, 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 B.2, and in Section B.3, we describe the hardware and how the LO frequencies are synthesised
and distributed around ALMA.

B.2

Summary of Operation

Figure B.1: Overview of ALMA frequency downconversion, LO mixing and delay corrections. This takes placein the Frontend, Backend, 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 an 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
3, 4, 7 and 8 have an output IF of 4-8 GHz, Band 6 a range of 5-10 GHz and Band 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 or
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

191

lower sideband; although at the edges of the tuning band, only one sideband is possible. LO1 consists ofa common component for all antennas, plus a smaller offset component generated in the FLOOG (FirstLO Offset Generator) which is different for each antenna (see LO1 Section B.3.4). The FLOOG is used
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 (by 180 or 90
degrees) in conjunction with a Walsh switching pattern on the antennas to remove DC systematic errors,
for sideband suppression and, in the future, for the DSB receivers (Band 9 & 10) for sideband separation.
2. In the “backend" (BE), the IF processor (IFP) splits the IF into basebands, each with frequency rangeof 2-4 GHz, via a set of filters and tunable second LOs (LO2) (see IFS/IFP section in 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 20.0-42.5MHz (marked as “fts” in Figure B.1). The limited fts
range and the 125MHz quantization means that LO2 setting is not fully contiguous; consequently there
can be up to ∼30MHz difference between the desired and the set value. With a single baseband, thiscan be 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
from the SPW center by up to 30MHz. However, the remaining differences in the different SPWs arecompensated by applying an opposite offset to the TFBLOs (LO4 - see below.)3 . An algorithm used by
the OT and the realtime system generates the best LO tuning “solution" for LO1, LO2 and LO4 which
minimizes the offset of the requested observing frequencies from the centers of the SPWs. Other uses of
LO2 are that the finely-tunable fts is used for fine fringe tracking and LO2 can also be used to offset thefrequencies in conjunction with LO1 to suppress interference and select the sideband.
3. The 2-4GHz 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 fibre-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 these
are required in each antenna, shown in the upper part of Figure B.2. In the following subsections, we describe
some of these components.
3 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

192

APPENDIX B. THE LO AND IF SYSTEM

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.

B.3. FREQUENCY GENERATION AND DISTRIBUTION IN ALMA

B.3.1

193

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) 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 inthe observatory. The modulated 1532 nm signal is sent to an optical distributor (with 80 outputs), the Low
Frequency Reference Distributor (LFRD ), that feeds it into the Sub Array Switch (SAS) modules, where it ismerged 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 fibre-optic distribution system (see Section B.3.3).

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 description of acronyms, see text.

B.3.2

LO1 signal generation and distribution

LO1 is distributed through fibre-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 6 Slave Lasers(Laser Synthesizers, LSs) that can produce 6 different LO1 frequencies which allow 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 (eg band-to-band transfer orspectral 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 6 Laser Synthesisers (LS). The LSs controls the frequency of 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194

APPENDIX B. THE LO AND IF SYSTEM

offsets between the ML and SL signals provides the beat note which is used to generate the LO1 frequency
in the photomixers (LPRs) 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 6 LSs it is possible to generate 6
separate LO1 frequencies.
• The Photonic Reference Distribution (PRD) feeds the optical signals to the Sub Array Switch (SAS) which
can distribute the signals to the different sub-arrays.
Figure B.4 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 toeach of the antennas. The fibres are distributed in buried trenches, and fed into the Cassegrain cabin on eachantenna through Az and El fibre wraps. All are fed through Line Length Correctors (LLCs), which are used tocorrect for changes in the optical fibres. The LLCs are described in B.3.3 below.

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

B.3. FREQUENCY GENERATION AND DISTRIBUTION IN ALMA

195

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.
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 1kHz) 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 of
two infrared lasers, the Master and Slave lasers. The Master Laser (ML) has a fixed wavelength of 1556 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 – 122 GHz. The beat note from the two lasers constitutes
the Photonic LO Reference; the LO1 reference signal is generated from this by photomixers located in theWarm Cartridge Assembly (WCA) of each receiver. This reference signal is used to drive a YIG (Yttrium
Iron Garnet) oscillator operating at frequencies around 10–30GHz (the exact range depending on the band),via a Phase Locked Loop (PLL) circuit. This produces LO1 for the SIS mixers via two sets of multipliers(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.

196

B.3.5

APPENDIX B. THE LO AND IF SYSTEM

LO2 and the IF processor units and IF switch

The output of each front-end cartridge is connected to a IF Switch unit (IFS) situated in the frontend, 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 Band 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 a IF bandwidth of up to 4 GHz. For
Band 9 & 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, a 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
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 8-14GHz. LO2 is generated from a harmonicof 125MHz, plus a fine-tuned synthesiser (fts) of range 20-42.5MHz, 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.

B.4. OTHER FUNCTIONS OF THE LO/IF197

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 IF 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 modules (DTS), that include
digitizers and formatters to convert the signals to optical wavelengths for transmission via optical fibers. There
are four DTS 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 then transferred to theformatter part that packages the data in frames of equal size. The output of each DTS 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 DTS modules are fed with reference/timing signals from an associated Digital Clock(DGCK), which is also used to do the fine delay tracking.
The outputs of the DTS are sent, via the optical fibers, to the AOS Technical Building where the process
is inverted (conversion from optical to digital signal) at the DRXs (Data Receiver units), before the signals
are sent to the correlator. Delay corrections due to changes in the length of the optical fibers are done using
metadata information to realign the frames sent from the transmitting side at the antenna (DTX) and thereceiving side at the Technical Building (DRX). Figure B.8 shows a block diagram of a single DTS module.

B.4

Other functions of the LO/IF

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

198

APPENDIX B. THE LO AND IF SYSTEM

Figure B.8: The DTX Signal Digitization and Transmission system, as used in each antenna.

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.4.2

Sideband suppression - LO offsetting

Some of the ALMA receivers (e.g. Band 3, 4, 6, 7, & 8) are inherently single sideband (SSB), either throughhaving a mixer or quasioptic design which rejects the unwanted sideband5 . 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 (Band 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
5 Although they have mixers to allow both sidebands to be observed separately and simultaneouslyB.4. OTHER FUNCTIONS OF THE LO/IF

199

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

Sideband separation - 90 degree Walsh switching

For future Cycles, it will be possible to apply a 90 deg phase switch in the FLOOG and in the correlator
processing, allowing correlation of the upper and lower sidebands separately. For Band 9 & 10 (DSB) it will
effectively double the bandwidth from 8 GHz to 16 GHz per polarization from the DSB receivers. This is underdevelopment and will not be available for Cycle 4.

B.4.4

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 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

200

APPENDIX B. THE LO AND IF SYSTEM

Appendix C

Calibration Sources
C.1

ALMA Catalog Description

The ALMA catalog of sources contains information for over 10,000 calibrators south of δ = 45◦ . The indicatedreference1 brings up a query page from which 1) information on any particular calibrator or 2) a cone search forcalibrators near any position, can be listed. An example of a cone search is shown in Figure C.1. The left-handside shows the typical query inputs needed. The right hand side side shows the results of the query. Plots and ahard copy of the source lists can also be obtained. Additional information, such as polarization, can be obtainedwith the listing.

Figure C.1: ALMA catalog example: Left: Search form for calibrators within 7◦ of target at 18:24:00 -29:40:00.
Right: List of calibrators near target.
The ALMA catalog is a compilation from many major catalogs (mostly at lower frequency) that have been
generated over the last 20 years. The catalogs include Crates 8.4 GHz2 , VLA calibrator catalog3 at20g catalog4 ,vlbi (Petrov) catalog5 , and SMA catalog6 . No blind ALMA surveys have been made to find new sources since
the above catalogs go sufficiently deep to include all sources that would be useful as ALMA calibrators. Since
most of the catalogs are based on observations at lower frequencies, the flux density of the sources must be
observed with ALMA in order to determine if their flux densities between Bands 3 and 10 are sufficiently strong(see below), and if they have extended structure. Many Observatory calibrations been developed to measure
the flux density of thousands of sources in the catalog (weak calibrator survey) and to check the flux densityof calibrators that are near targets (cone-search) that will be observed in the near future. These efforts will
1 https://www.almascience.org/sc
2 ApJS, 171, 61, 2007
3 http://www.aoc.nrao.edu/∼gtaylor/csource.html
4 Murphy et al, 2010, MNRAS, 402, 2403
5 http://astrogeo.org/vlbi/solutions/rfc_2016a/rfc_2016a_cat.txt
6 http://sma1.sma.hawaii.edu/callist/callist.html

201

202

APPENDIX C. CALIBRATION SOURCES

continue into Cycle 4.
About 2000 sources have been observed with VLBI techniques (Petrov catalog) and have positions that are
accurate to at least 0.00200 . These are the sources that should be used as phase calibrators, and they are used for
all ALMA system calibrations, for example, the baseline measurements. All calibrator positions are measured
on the ICRF/ICRS astrometric system and it is strongly recommended that all targets that are observed with
ALMA have positions on this quasar reference system. Most quasars in the ALMA frequency range have spectral
index, α, (S ∝ ν α ) that are between -0.5 and -0.8; hence with a measurement at Band 3 and 7, the flux density
at Band 9 can be inferred to an accuracy of about 25%. On the average, the separation between a target anda good quality calibrator in the catalog is about 3◦ at Band 3, and about 8◦ at Band 9.
The flux density for a set of strong quasars that cover the sky is monitored every 10 days with ALMA
observations at Bands 3 and also at Band 6 or 7, depending on the phase conditions. These grid sources areused as secondary amplitude calibrators and tied to the solar system objects with known brightness models.
The flux density of quasars vary but with their frequent monitoring their flux densities at any time are accurate
to about 5% at Bands 3, 6, 7, and 10% at Bands 8, 9 and 10. Most quasars are stable to 20% over months, butthere are a few highly varying quasars that periodically change by a factor of three in a month or less.

C.2

Phase Calibrator Selection

The proper selection of a satisfactory phase calibrator is critical for the image quality of the target source. The
major criterion is that its flux density is sufficiently strong in order to obtain an SNR greater than 15 for anantenna-based solution for each scan. The secondary consideration is that the closer the calibrator is to thetarget, subject to the sensitivity limit, the more effective it will be in reducing the phase variations in the target.
For two potential calibrators that are well above the sensitivity limit, the one closer to the target should beselected.
With the addition of many recent ALMA observations of the flux density of many sources in many cases the
optimum calibrator can be determined using an automatic query system as the SB is being prepared. However,cone-searches around targets will still be made for long baseline and high frequency projects where the closenessof the calibrator to the target is more important. If a selected calibrator does not have a measured flux density
more recently than 90 days, and is less than about two times the detection limit needed for an experiment, ashort ALMA observation (perhaps part of a cone search) will be made well to determine its current flux density.
An observation at any band is sufficient since the quasar flux density spectral indices lie in a narrow range.
The lower flux density limits for a phase calibrator for all of the observing bands are given in Table 10.1
below. The flux limits can be scaled by (Nant /40)−0.5 (Tsys ) [(tscan /120) (νBW /7.5GHz)]−0.5 . Figure C.2
shows the probability of finding a detectable calibrator (40 antennas, 7.5 GHz bandwidth) in the ALMA catalog
within a specified angular separation. For example at 492 GHz, there is an 80% chance of finding a calibrator
within 4.0◦ of a random target.

C.3

Bandpass Calibrator Selection

The bandpass calibrator must be stronger than the phase calibrator since accurate calibrations will be obtained
for relatively narrow frequency ranges. However, the ALMA bandpass shape changes by less than 1% overtens of degrees in the sky and several hours of time so the bandpass calibrator need not be close to the target(within < 45◦ ) and a sufficiently bright source should be available for most experiments. Also, a concern is
obtaining sufficient SNR for FDM (narrow-band) channels. Testing has shown that for bandwidths < 128 MHz,the bandpass is flat to 1%; so calibration over narrower bandwidths are not needed7 .
The bandpass calibration limit of 50 SNR for each antenna/SPW/polarization gain determination, giving a
1% rms error in amplitude and 2◦ in phase for each of the SPW/polarization channels. The flux density low
limits for suitable bandpass sources with an observation of 15 min and a bandwidth of 128 MHz are given in the
7 https://wikis.alma.cl/twiki/pub/AIV/EOCMemos/EOC_Memo27_Dec17_FINAL.pdf

203

C.3. BANDPASS CALIBRATOR SELECTION

Flux Density Limit for Phase Calibrator with 40 12-m antennas
Band Frequency Assumed Tsys Assumed PWV Flux Density
(GHz)
(K)
(mm)
(mJy)
3
86.243
83
5.186
4.4
3
115.271
173
5.186
9.3
4
146.969
86
1.796
4.7
6
230.538
102
1.262
5.7
7
345.796
151
0.658
9.0
8
461.041
431
0.472
28.5
8
492.161
638
0.472
43.7
9
624.208
4302
0.472
346.0
9
658.007
1721
0.472
145.2
9
691.473
1231
0.472
109.5
10
806.652
2405
0.472
257.7

Cal-target separation
1.1
1.5
1.3
1.5
1.8
2.1
2.5
9.0
5.0
4.7
7.8

Table C.1: The minimum phase calibrator flux density in mJy needed for an antenna-based phase determination
with 4 deg rms (15 SNR) with a 120 seconds integration time, assuming 40 antennas and elevation of 50 degrees.
The total bandwidth in both polarizations of 7.5 GHz is assumed.

Table 2, below. The flux limits should be scaled by (Nant /40)−0.5 (Tsys ) [(tscan /900) (νBW /128M Hz)]−0.5 . The
above antenna-based specifications for 40 antennas produce an image channel to image channel rms variationsof about 0.2%. For nearly all projects, the target SNR may give much larger variations in the spectral propertiesof the source than the bandpass calibration inaccuracy.
However, for the longer baselines in TDM mode, changes in delay caused by the atmosphere and baseline
errors can produce phase slopes over the 2 GHz bandpass of up to 10 deg between the bandpass calibrator andthe phase cal/target. If the phase cal is sufficiently strong, then its residual delay can be removed from itself
and the target.
Band
3
3
4
6
7
8
8
9
9
9
10
10

Flux Density Limit for Bandpass Calibrator
Frequency Assumed Tsys Assumed PWV Flux Density
(GHz)
(K)
(mm)
(mJy)
86.243
66
5.186
58
115.271
173
5.186
121
146.96986
1.796
61
230.538
102
1.262
74
345.796
151
0.658
119
461.041
431
0.472
375
492.161
638
0.472
574
624.208
4302
0.472
4551
658.007
1721
0.472
1909
691.473
1231
0.472
1435
806.652
2405
0.472
3390
850.000
1817
0.472
2771

Table C.2: The minimum bandpass calibrator flux density in mJy needed for an antenna based gain solution
with SNR of 50, assuming integration time of 900 seconds, 40 antennas, and elevation of 50 degrees. The
sensitivity assumes a bandwidth of 128 MHz, regardless of the number of spectral channels within this width.
The present list of bandpass sources that are frequently monitored is shown in Table C.3. Some changes
will be made for extremely variable sources or with the addition of sources that have become strong at Bands
7 and 9. Each source has several aliases so that J1229+0203 is also recognized as 3C273 or 3c273.

204

APPENDIX C. CALIBRATION SOURCES

Angular separation to the nearest QSO usable as a phase calibrator for 12m array (D=12 [m], N=36)

1.0

Cumulative Fraction of sky

0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2

115 GHz, limit=0.019 Jy (t =30 [s])492 GHz, limit=0.046 Jy (t =120 [s])660 GHz, limit=0.15 Jy (t =120 [s])806 GHz, limit=0.27 Jy (t =120 [s])
int
int

0.1
0.0

int
int

0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20

Angular separation [degrees]

Figure C.2: The probability of finding a phase calibrator within an angular separation of a random target.
The y-axis is the probability, the x-axis is the target-calibrator angular separation. The plot is given for four
different ALMA frequencies using the 12-m array with 40-antennas and 7.5 GHz bandwidth.

C.4

Other Calibrator Types

C.4.1

Absolute and Relative Flux density Calibration

In order to determine the absolute flux density scale of an experiment, the experiment should contain a solar
system object with a known brightness model; Mars, Uranus, Neptune, Ceres, Pallas, Juno, Vesta, Ganymede,
Callisto, Titan. Their accuracy varies with resolution and frequency, from 3% to 10%. If a solar system object
is not available, the bandpass sources chosen is usually a grid sources (Table C.3. These sources are monitoredwith ALMA every two weeks at Band 3 and Band 7, so that their estimated flux density at any time andfrequency can be estimated to about 5% accuracy below 400 GHz and about 10% to 15% accuracy above thisfrequency.

J0106−4034
J0334−4008
J0538−4405
J1037−2934
J1147−6753
J1426+3625
J1642+3948
J2025+3343
J2353+1608

J0132−1654
J0423−0120
J0635−7516
J1058+0133
J1159+2914
J1427−4206
J1733−1304
J2056−4714
J2258−2758

J0237+2848
J0510+1800
J0750+1231
J1107−4449
J1229+0203
J1517−2422
J1751+0939
J2148+0657
J2357−5311

J0238+1636
J0519−4546
J0854+2006
J1130−1449
J1256−0547
J1550+0527
J1800+3884
J2202+4216

J0319+4130
J0522−3627
J0927+3902
J1146+3958
J1337−1256
J1617−5848
J1924−2914
J2232+1143

Table C.3: ALMA bandpass calibrator (grid) sources

C.4. OTHER CALIBRATOR TYPES

205

The ALMA system antenna noise properties are stable and well-known so that the apriori absolute flux
density scale can be determined from the measured antenna SEFD (Source Equivalent Flux Density), and varyby less than 10% over the array elements. For example, the SEFD at Band 3 for most antennas is about 35. After
multiplying the raw visibility amplitude (units of correlation with a typical value of 10−4 ) and correcting by thesystem temperature, the visibility units are converted to antenna temperature in Kelvin. Then multiplicationby the SEFD will produce visibility units in Jy. For example, with a system temperature of 100K, a 10−4
uncalibrated correlation amplitude would correspond to a correlated flux density of 0.35 Jy.
Thus, obtaining absolute amplitude accuracy better than 3% is challenging even at the lower frequencies, and
10% at the higher frequencies. Specialized ALMA observations of all of the solar system objects and quasars aredone periodically in order to check the relative values of the brightness models, in collaboration with planetarymodel builders.
The relative flux density of a target source with respect to the assumed phase reference flux density is
obtained by the normal phase referencing technique to an accuracy of about 1% over an experiment of one
hours. Since most quasars vary less than a few percent over a few days, target variations over hours to days canbe accurately measured as long as the same calibrator is used. For longer periods, an accurate absolute flux
density of the calibrator must also be determined.

C.4.2

Polarization Calibrators

The measurement of the linear polarization of sufficiently strong calibrators (many are grid sources) are listed
in the ALMA catalog. Additional ALMA observations are made in order to monitor the strongest, polarized,
sources. The calibration methods are discussion in Section ().

C.4.3

Astrometric Calibrators

The discussion of the astrometric methods and observations for ALMA are discussed in Section 10.6.3. A good
astrometric calibrator should have a position error of less than about 2 mas in order not introduce astrometricand phase errors into the calibration measurements. This precision is only available from VLBI observations
at cm wavelengths, but are currently known for over 2000 quasars. The use of a calibrator with less accurate
radio positions should be avoided under most circumstances.

C.4.4

Check Sources

The quality of ALMA observations can be checked if a point source of known position and flux density is
included in the SB, and observed and reduced in a similar manner as the target. This source is called a checksource and is described in Section 10.6.3. A check source will be included when the observation resolution is< 0.2500 (longer spacings at Bands 3, 4, 6, and 7) and for all observations at Bands 8 and above. It will beselected from the ALMA catalog and should have the same properties as that of a suitable phase calibrator,
but can be appreciably fainter.

206

APPENDIX C. CALIBRATION SOURCES

Appendix D

Acronym Dictionary
ACA
ACD
ACS
ALMA
AoD
AOS
APDM
AQUA
ARC
ASA
ASC
ASDM
AZ
BB
BE
BL
BLC
BWFN
CASA
CCA
CCC
CDP
CFRP
CLO
CLT
CORBA
CRD
CRG
CSV
CW
DC
DEC
DGCK
DMG
DRX
DSB
DSO
DTS

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 Quality Assurance software
ALMA Regional Center
ALMA Science Archive
ALMA Sensitivity Calculator
ALMA Science Data Model
AzimuthBasebandBackendBaseline
BaseLine Correlator
Beam Width between First Nulls
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
Digital Clock
Data Management Group within DSO
Data Receiver module
Double Sideband
Division of Science Operations
Data Transmission System

207

208

APPENDIX D. ACRONYM DICTIONARY

DTX
EB
EL
EM
EPO
ES
ESO
FDM
FE
FITS
FLOOG
FOM
FOV
FPGA
FT
FWHM
FWHP
FWBN
FXF
GPS
HA
HEMT
HPBW
IF
IFP
IRAM
JCMT
JPL
LFRD
LLC
LO
LO1
LO2
LO3
LO4
LORR
LS
LSB
LTA
MFS
ML
MLD
NGAS
NRAO
OMC
OMT
OSF
OST
OT
OTF
OUS
PBS
PDM

Data Transmitter module
Execution BlockElevation
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 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
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
Long Term Accumulator
Master Frequency Standard
Master Laser
Master Laser Distributor
New Generation Archive System
National Radio Astronomy Observatory
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

209

PI
PLL
PMG
PRD
PWV
QA
QA0
QA1
QA2
QA3
QL
RA
RF
RMS
SAS
SB
SCO
SD
SED
SIS
SL
SNR
SPW
SRON
SSB
2SB
SSR
STE
STI
TA
TDM
TE
TelCalTFB
TFB LO
TMCDB
TP
Tsys
Trx
USB
VLA
VO
WCA
WVR
XF
YIG

Principal Investigator
Phase Lock Loop
Program Management Group within DSO
Photonic Reference Distributor
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
Sideband separating Mixer
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
Receiver Temperature
Upper Sideband
Very Large Array
Virtual Observatory
Warm Cartridge Assembly
Water Vapor Radiometer
Correlation-Fourier Transform Type Correlator
Yttrium-Iron Garnet Oscillator

Indexuv-coverage, 86
uv-plane, 22
uv-taper, 90
12-m Array, 9, 12
64-input Correlator, 9, 12, 57, 58
7-m Array, 9, 11, 13, 62

performance specifications, 12, 177
PM, 12
power response, 19
response, 16
specifications, 177
surface, 177transportation, 181
ACA Correlator, 9, 60
transporters, 11
Airy function, 19
types, 178
Alcatel Alenia Space European Industrial Engineering AOS Technical Building, 191
MT Aerospace (AEM), 177
Aperture, 17
Aliasing, 28, 59
synthesis, 19
ALMA
Application Specific Integrated Circuit, 62
Archive, 173
Array
Common Software (ACS), 155
performance, 152
Frontend Archive (AFA), 173
Array Operations Site (AOS), 11
location, 11
Astronomer on Duty, 103, 150
Science Archive (ASA), 173
Atacama Compact Array, 9, 11
Science Data Model (ASDM), 157
Atacama Large Millimeter/Submillimeter Array, 9
ALMA Common Software (ACS), 11
Atmosphere
ALMA Project Data Model (APDM), 103
opacity, 125
ALMA Regional Centre (ARC), 173
Atmospheric calibration (ATM), 185
ALMA Science Data Model, 135
Atmospheric transmission, 31
ALMA subsystem, 155
Auto-correlation, 20
Control, 155
Autocorrelation
Executive, 155data, 136
QuickLook, 155
Scheduler, 155Barlett weighting, 66
Telescope Calibration, 155, 156
Baseband(s), 12, 14, 57, 71
Amplitude, 15, 22
desired center, 73
Amplitude Calibration Device, 140
Baseline, 20
Amplitude Calibration Device, 137
Baseline Correlator, 57
Amplitude Calibration Device (ACD), 31, 184
Beam shape, 86
Angular resolution, 82, 86
Bessel function, 19
Antenna
Binary Data Format, 67
delay offset, 139
Brightness, 16
position, 139
temperature, 28
power response, 19
Brightness temperature, 28
Antenna beam, 138
Bulk binary data, 157
Antenna(s)Calibration
beam size, 17
amplitude, 109
CM, 12antenna pointing, 141
design and properties, 177
atmospheric, 108
foundations, 11, 179
bandpass, 107pads, 179
baseband, 142
panels, 178

210

211

INDEX

flux, 107
flux density, 142
gain, 142
phase, 107plan, 151
polarization, 142receiver temperature, 140
summary, 150
system temperature, 140
system-defined, 106
user-defined, 106
water vapor radiometer, 140
Calibration observation, 105
Calibrations
a priori, 137
offline, 137
online, 137
Cartridge assembly, 31
Cassegrain focus, 178
Chajnantor, 11
Chajnantor Plateau, 10
Check source, 145
Cittert-Zernike theorem, 22
Clock rate, 60Complex visibility
function, 135
Complex visibility, 22
distribution, 22
Configurations, 82
Contact scientist, 152
Correlator
64-input, 12
ACA, 12, 57
capabilities, 64
dump time, 67
FX, 13, 60
XF, 12
Correlator and Integration Processor, 60
Correlator Data Processor, 60
Correlator delay model, 135
Correlator mode
FDM, 191
Cosmic Microwave Background, 126
Cross-correlation, 20
Cryostat, 181
Cycle 0, 9
Datadelegation, 175delivery, 174
download, 176
replication, 174
Data and Control Flow, 155
Data Capture module, 157

Data Management Group, 149
Data rate, 12
average, 173
peak, 173
Data receivers, 64
Data Reducers Team, 151
Deconvolution techniques, 24
Delay
artificial, 20
geometrical, 20
Digital Transmission System Receiver, 60
Digital Transmitter, 64
Digitizers, 64
Director’s Discretionary Time, 174
Dirty
beam, 24
image, 24
Dirty beam, 82
Doppler correction, 72
Doppler shift, 189
Doppler tracking, 79
DTS and FFT processor, 60
Dump rates, 13
Early Science
Operations, 9Primer, 9Earth rotation, 23
Electromagnetic power, 16
Ephemeris file, 79, 113
Execution Block (EB), 105
Feathering, 98
Field of view, 23, 93
Field programmable gate array, 59
FITS format, 176
Flux density, 16, 28
Focus model, 139
Fourier transform, 15
Fraunhofer approximation, 19
Frequency
center offset, 73
definitions, 73
generation, 191
rest, 73sky, 73
synthesizer, 72
Frequency and phase standard, 193
Frequency Division Mode (FDM), 58, 65
Frequency Profile Synthesis, 60
Fringe, 22
rotation, 189
spacing, 23
tracking, 191
Frontend, 31, 181

212

Full Width Between Nulls, 18
Full Width Between the Nulls, 18
FXF, 58
Gibbs phenomenon, 90
Grid source, 107
Group Observing Unit Set (GOUS), 105
Half Power Beam Width, 17Hanning function, 65
Helpdesk, 152
Image fidelity, 24
Imagingsimultaneous, 73
Integration time, 96Interferometer
resolution, 26
two-antenna, 20Interferometry
single field, 107
Intermediate frequency, 33, 71
Jansky, 16
Joint ALMA Observatory (JAO), 11
JPL Horizon format, 113
Koh-ichiro Morita, 14
Lasers, 193
LO and IF systems, 189
operations, 190
Local Oscillator, 33, 57, 71
offsetting, 34, 77
Local Oscillator (LO), 12
Long Term Accumulator, 60
Lower sideband, 71
Maximum data rate, 67
Maximum recoverable scale, 13, 26, 92, 94
Measurement Set, 141
Member Observing Unit Set (MOUS), 105
Metadata, 157
Metrology, 179
Mitsubishi Electric Corporation (MELCO), 177
Morita Array, 9Mosaicing, 23, 93, 108
Multiple pointings, 108
Multiple Region Modes, 113
NED, 175
Next Generation Archive System, 173
Nutator, 14
Observations
on-the-Fly Mapping, 108

INDEX

total power, 108
Observingproject, 103
proposal, 103
script, 103, 106
session, 105
Observing mode(s), 9
Observing session, 155
Observing Unit Set, 153
Observing Unit Set (OUS), 105
On-the-fly scan (OTF), 13
Operation Support Facility (OSF), 11
Otho mode transducer, 35
Output radiance, 125
Pampa la Bola, 11
Parallactic angle, 112
Phase, 15, 22
Phase 1, 71, 103
Phase 2, 71, 103
Phase calibration, 76
Phase center, 21
Phase switching, 79
Pipeline, 10Plateau de Bure, 16
Pointing model, 138
Polarization, 16, 78, 109
instrumental, 109
leakage, 143
off-axis, 110
Position switching, 13
Precipitable water vapor, 64
octiles, 125
Precipitable water vapourt
octiles, 126
Primary beam, 17, 93
correction, 23
Primary focus, 178
Primer for Early Science, 11Program Management Group, 149
Proposer’s Guide, 9, 105
Proprietary period, 174
Quality Assurance, 149categories, 150
classification, 149
report, 152
Quantization, 57, 68
efficiency, 68Radiometer
Dicky-switching, 187
Rayleigh resolution, 18
Rayleigh-Jeans limit, 28
Receiver(s)

213

INDEX

2 sideband, 128
double sideband, 128
heterodyne, 128
Rectangular field, 108
Reflector
nutating, 177
secondary, 19
Robustness, 87
San Pedro de Atacama, 11
Scan, 105, 135, 156
Scheduling Block, 150
Scheduling Block (SB), 103
Sciencegoal, 103, 108
parameter(s), 103
Science Archive Content Manager, 150
Science Pipeline, 151
Science Software Requirements, 105
Sensitivity, 74, 125
point-source, 130
surface brightness, 131
Shadowing, 26, 85
Shutter, 179
Sidebanddouble, 32, 77
double (DSB), 12
dual, 12, 32
single, 32
Sidelobes, 18, 24, 81, 90
Simbad, 175
Sky brightness distribution, 15, 22
Sky frequency, 71
Snapshot, 90
Solar observations, 115
Solar system objects, 113
Spatialfiltering, 24, 92
frequency, 15, 21
Spatial coherence function, 107
Specific intensity, 16, 28
Spectral setup, 71, 73
Spectral window (SPW), 59, 71
Standard observing modes, 151
Standard Test Environment, 155
Stokes parameters, 109
Sub-arrays, 12
Submillimeter Array (SMA), 16
Subreflector, 14, 178
Subscan, 156
Subsystems
QuickLook, 105
Control, 106
Scheduler, 105

Telescope Calibration, 105
Surface characteristics, 138
Synthesized beam, 24
Technical Handbook, 9
Telescope
filled-aperture, 20
Telescope Monitor and Configuration Data Base, 138
Telescope operator, 155
Temperaturesky, 125
system, 125
Tiltmeters, 179
Time Division Mode (TDM), 58, 65
time resolution, 66
Tools
AQUA, 150, 152
JIRA, 149
Monitor and Control, 150
Project Tracker, 150
QuickLook, 150
TelCal, 150
Total Power Array (TP Array), 9, 11, 13, 14, 62
Transporter, 181
Tunable Filter Bank (TFB), 12, 58, 189
Tuning range, 76
Upper sideband, 71User Policies, 152
Van Vleck relationship, 68
Velocity definition
Optical, 79Radio, 79
Relativistic, 79
Velocity reference, 79
Barycentric, 79
LSRK, 79
Topocentric, 79
VertexRS, 177
Virtual Observatory, 175
Visibility, 15
Visibility function
weighted, 81
Vizier, 175
Voltage response, 19
VOTables, 175
Walsh-switching, 57, 79
Water Vapour Radiometer (WVR), 12, 64, 186
Weblog page, 151
Weighting
Briggs, 87
natural, 81, 86
uniform, 81, 87

214

WVR Correction, 64
WVR correction, 57
XML tables, 157
Zero spacing, 108
Zero-point fluctuations, 127
Zero-spacing problem, 13, 26

INDEX