Doc 3.3, ver. 1.0 | March 20, 2015

ALMA Cycle 3 Technical Handbook

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2

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Version

Date

Editors

1.0

2015-03-20

A. Remijan, M. Adams, R. Warmels

Mark Adams, Eiji Akiyama, Paola Andreani, Yiping Ao, Shin’ichiro Asayama, Denis Barkats, Andy Biggs,
James Braatz, Crystal Brogan, James Chibueze, Stuartt Corder, Juan Cortes, Paulo Cortes, Carlos De Breuck,
Itziar De Gregorio, Bill Dent, James Di Francesco, Jennifer Donovan Meyer, Darrel Emerson, Daniel Espada,
Ed Fomalont, Roberto Galvan-Madrid, Antonio Hales, Bunyo Hatsukade, Cinthya Herrera, John Hibbard, Akihiko Hirota, Elizabeth Humphreys, 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, Erik Müller, 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, Felix Stoehr, Kenichi Tatematsu, Ignacio
Toledo, Baltasar Vila-Vilaro, Eric Villard, Rein Warmels, Al Wootten, Jorge F. García Yus, Martin Zwaan.

In publications, please refer to this document as:
A. Remijan et al., 2015, ALMA Cycle 3 Technical Handbook Version 1.0, ALMA
ISBN 978-3-923524-66-2

Contents
1 Introduction

5

2 Array Components
7
2.1 The ALMA Telescope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 The 12-m Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3 The Atacama Compact Array (The Morita Array) . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.1 The 7-m Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.2 The TP Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

11
11
12
15
18
19
19
22
24

4 Receivers
4.1 Local Oscillators and IF Ranges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 The Cycle 3 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27
29
29
30
33
36
39
42
45
48

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 7-m Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.2 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

51
52
52
53
54
54
56
58
58
58
58
58
59

3

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CONTENTS

5.5.3 Time Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Practical Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.1 Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.2 Linearity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.3 Integration time intervals, channel-average and spectral data . . . . . . . . . . . . . . . .
5.6.4 Online WVR correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.5 Correlator speed and data rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.6.6 Final data product - the ASDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

61
62
62
63
63
64
64
65

6 Spectral Setups
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2 Frequency Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3 Spectral Setup: Multiple lines and Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.1 Observing Frequencies for Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3.2 Multiple Spectral Windows in the Same Baseband . . . . . . . . . . . . . . . . . . . . . .
6.4 Spectral Setups for Lines near the Edge of the Bands . . . . . . . . . . . . . . . . . . . . . . . . .
6.5 Spectral Setup in Band 9 & 10 and DSB Considerations . . . . . . . . . . . . . . . . . . . . . . .
6.5.1 Usable Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.5.2 Spurious Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.5.3 Doppler Setting and Velocity Reference Frames . . . . . . . . . . . . . . . . . . . . . . . .
6.6 Limitations and Rules for Spectral Setups in Cycle 3 . . . . . . . . . . . . . . . . . . . . . . . . .

67
67
68
69
69
71
72
73
73
74
74
74

7 Imaging with ALMA
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2 Cycle 3 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

77
77
77
78
82
83
87
89
90
93

5.6

8 Observing Modes97
8.1 Observing Project Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
8.2 Program Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
8.3 The Observing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
8.3.1 The source selection algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
8.4 Single Field Interferometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
8.5 Pointed Mosaic Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
8.6 Single Dish Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
8.7 Polarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
8.7.1 Sessions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
8.8 Multiple Region Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
8.9 Observations of Ephemeris Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
9 ALMA Sensitivity Calculator
109
9.1 Calculating the System Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
9.1.1 Sky temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
9.1.2 CMB temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
9.1.3 Receiver temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
9.1.4 Ambient temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
9.1.5 DSB receivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
9.1.6 System temperature (OT version) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
9.1.7 System Temperature (Applet and GUI version) . . . . . . . . . . . . . . . . . . . . . . . . 113

CONTENTS

9.2
9.3
9.4

5

The Sensitivity Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
9.2.1 12-m and 7-m Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
9.2.2 Total Power Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
User Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Total Time Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

10 Calibration and Calibration Strategies
117
10.1 The Measured Visibility Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
10.1.1 The Data Format and the Correlator Model . . . . . . . . . . . . . . . . . . . . . . . . . . 117
10.1.2 The Visibility Function Dependence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
10.2 Main Interferometric Calibration Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
10.2.1 Antenna-based Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
10.2.2 Calibration Flow through ALMA system . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
10.2.3 A priori, Online and Offline Calibration Methods . . . . . . . . . . . . . . . . . . . . . . . 119
10.3 ALMA-Supplied a priori Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
10.4 Online Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
10.5 Offline Calibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
10.6 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
10.6.1 ALMA Catalog Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
10.6.2 Phase Calibrator Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
10.6.3 Bandpass Calibrator Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
10.6.4 Band-to-Band Phase Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
10.6.5 Bandwidth Phase Transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
10.6.6 Astrometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
10.6.7 Long Baseline Observations with Baselines > 3 km . . . . . . . . . . . . . . . . . . . . . . 127
11 Quality Assurance
129
11.1 Cycle 3 "Best Efforts" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
11.2 QA0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
11.3 QA1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
11.4 QA2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
11.5 QA3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
11.6 The Quality Assurance Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
11.7 QA Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
12 Logical Data Structure and Data Flow
135
12.1 Data and Control Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
12.2 The ALMA Science Data Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
13 Pipeline Processing
139
13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
13.2 Pipeline In ALMA Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
13.2.1 Pipeline Triggering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
13.2.2 Pipeline Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
13.2.3 Pipeline Runtime Database-querying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
13.2.4 Pipeline and the ALMA Quality Assurance Process . . . . . . . . . . . . . . . . . . . . . 140
13.2.5 Standard and non-standard Observing Modes . . . . . . . . . . . . . . . . . . . . . . . . . 144
13.3 Pipeline Processing of an ALMA OUS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
13.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
13.3.2 Pause after Data Import . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
13.3.3 Output of the Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
13.4 Pipeline Initialisation & Calibration Table Editing . . . . . . . . . . . . . . . . . . . . . . . . . . 144
13.5 General Interferometric ALMA Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
13.5.1 Data Import & Calibrator Flux Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
13.5.2 Deterministic & Manual Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145

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CONTENTS

13.5.3 Flagging lines in Solar System Object Flux Calibrators . . . . . . . . . . . . . . . . . . . 145
13.5.4 Reference Antenna Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
13.5.5 Offline WVR Calibration for 12m Array Data . . . . . . . . . . . . . . . . . . . . . . . . . 146
13.5.6 Low gain flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
13.5.7 Bandpass calibration & flagging bandpass solutions . . . . . . . . . . . . . . . . . . . . . . 146
13.5.8 Setting the fluxscale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
13.5.9 Deriving the fluxes of the phase and bandpass calibrators . . . . . . . . . . . . . . . . . . 146
13.5.10 Time Gain Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
13.5.11 Applying the calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
13.5.12 Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
13.5.13 Exporting the products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
13.6 Low SNR Heuristics in Interferometric Pipeline Processing . . . . . . . . . . . . . . . . . . . . . . 147
13.6.1 Mapping the gain solutions from broad spectral windows to narrow ones . . . . . . . . . . 148
13.6.2 Using the gain solutions obtained from the aggregate of all spectral windows . . . . . . . 148
13.6.3 Additional Bandpass Pre-averaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
13.7 Total Power Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
13.7.1 Data Import . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
13.7.2 Deterministic & Manual Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
13.7.3 Tsys & Sky Calibration Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
13.7.4 Applying the calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
13.7.5 Automated line identification and Baseline subtraction . . . . . . . . . . . . . . . . . . . . 149
13.7.6 RMS Flagging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
13.7.7 Applying Kelvin-to-Jansky factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
13.7.8 Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
13.7.9 Exporting the products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
14 Data Archiving
151
14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
14.2 Data Flow and Archive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
14.3 PI Data Delivery and Data Delegation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
14.4 Archive Query . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
14.5 Request Handler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
A Antennas
155
A.1 Design and Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
A.2 Antenna Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
A.3 Antenna Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
A.4 Cryostat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
A.5 Amplitude Calibration Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
A.5.1 Atmospheric Calibration Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
A.6 Water Vapor Radiometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
B The LO and IF System
167
B.1 Functions of the LO & IF system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
B.2 Summary of Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
B.3 Frequency Generation and Distribution in ALMA . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
B.3.1 Reference and LO signal generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
B.3.2 LO1 signal generation and distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
B.3.3 Line length corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
B.3.4 The First Local Oscillator (LO1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
B.3.5 LO2 and the IF processor units and IF switch . . . . . . . . . . . . . . . . . . . . . . . . . 174
B.3.6 Digitization and signal transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
B.4 Other functions of the LO/IF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
B.4.1 Delay corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
B.4.2 Sideband suppression - LO offsetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

CONTENTS

7

B.4.3 Sideband separation - 90 degree Walsh switching . . . . . . . . . . . . . . . . . . . . . . . 177
B.4.4 Interference rejection - 180 degree phase switching . . . . . . . . . . . . . . . . . . . . . . 177
C Calibration Source Selection
179
C.1 Antenna-based Sensitivity Determinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
C.1.1 ALMA Sensitivities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
C.1.2 Calibration Parameters and Derived Antenna-based RMS . . . . . . . . . . . . . . . . . . 179
C.2 Choosing the Calibrators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
C.2.1 The Phase Calibrator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
C.2.2 The Bandpass Calibrator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
C.2.3 Other Calibrator Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
D Acronym Dictionary

185

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 3 is still within the ALMA Early Science
period, in the sense that a reduced number of antennas, frequency bands, array configurations and observing
modes will be available. Cycle 3 operations will include standard and non-standard modes, with non-standard
mode observations being conducted on a best effort basis, similar to projects in previous Cycles. Users shouldrefer to Appendix A (Capabilities) in the ALMA Cycle 3 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
3 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 3. 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 3 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.
Chapter 8 describes the observing modes offered for Cycle 3 and how projects are observed. Single field in-

910

CHAPTER 1. INTRODUCTION

terferometry, mosaics, single-dish observations, polarization, multiple region modes, 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. Note that not all capabilities may be available during the Early
Science observing period.

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 Array1 , composed of twelve closely spaced 7-m antennas (the 7-m
Array), and four 12-m antennas for single-dish (or Total Power) observations (the TP Array), to enhance wide
field imaging of extended structures. In Cycle 3, 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 from 10 to
0.32 mm (31-950 GHz).
The array is located on the Chajnantor plain of the Chilean Andes (latitude = −23.022917◦ ,longitude = −67.754649◦ ), a site that normally offers the exceptionally dry and clear sky conditions required
to observe at millimeter and submillimeter wavelengths2 . The ALMA antennas, weather stations, the twocorrelators and their computer interfaces, Local Oscillator generation hardware, timekeeping hardware, and therelated array Real-Time Machine computer are all located at the 5000 meter altitude site referred to as theArray Operations Site (AOS). This site is connected via Gigabit fiber links to the Operation Support Facility(OSF), located at an altitude of 2900 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 Joint ALMA
Observatory (JAO) Central office in Santiago.
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
power and digital connectivity to the main AOS building (See Appendix A.2). The antennas can be moved into
the different array configurations (Chapter 7) using the two special purpose ALMA antenna transporters (seeAppendix A.3).
The number of antennas in each array component (12-m, 7-m and TP Arrays), and the specific configurations
available for an observing season (e.g. Cycle 3) will be published in Appendix A (ALMA Cycle 3 Capabilities) of
the document ALMA Proposer’s Guide (Appendix A). Complementary background information on ALMA andits capabilities for Early Science can be found in the document A Primer for Early Science. Both documents
1 Dedicated to the honour of Koh-ichiro Morita, Figure 2.2)2 http://almascience.edu/about-alma/weather

11

12

CHAPTER 2. ARRAY COMPONENTS

can be found at: http://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 and 4 PM antennas are distributed in the right hand side of the image (circled). A few unoccupied
stations can be seen, to which antennas of the 12-m Array can be moved by the transporter as the array is being
reconfigured. At its most extended configuration, antenna baselines in the 12-m Array will reach a maximum
extent of about 16 km.

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 switched on
simultaneously, and rapid switching between those bands is possible. Each receiver band (Chapter 4) detects
two orthogonal linear polarizations and down converts the signals to an intermediate frequency with eight GHzof bandwidth per polarization. Bands 3-8 are dual sideband (2SB) and Bands 9 and 10 are double sideband(DSB).
The Local Oscillator (LO) signals (see Section B.2) are transmitted to the antennas on optical fibers witha round trip measurement to correct for changes in the fiber length. There are four independent LO reference
systems so that the 7-m Array, the TP array and two subsections of the 12-m Array (e.g., two ‘sub-arrays’) canmake simultaneous independent observations. 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 fibers (Section B.3.6). Total data rates
are therefore 96 Gbits/s per antenna. With formatting, the bit rate is 120 Gbits/s.
On arrival at the central building, the data are recovered and processed in one of the two correlators: the64-input Correlator and the ACA Correlator (see Chapter 5). All antennas can feed either correlators. The
64-input Correlator (Section 5.1) is normally used for the 12-m Array, but it can also take inputs from the 7-m
Array or TP antennas. It is an XF correlator (cross-correlates first, then Fourier transforms), but the correlator
is preceded by Tunable Filter Banks, which makes it a digital hybrid XF correlator or FXF. These can select2.3. THE ATACAMA COMPACT ARRAY (THE MORITA ARRAY)

13

subbands from the 2 GHz-wide basebands in a very flexible manner. From each of these, the correlator thengenerates 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 the transforms and carry out
integration and data compression.
Both correlators have minimum dump rates of 16 ms for cross-correlation and 1 ms for auto-correlation,although these dump rates can only be achieved using a reduced number of channels to prevent exceeding the
maximum transmission and storage rates. The systems are designed for a maximum data rate of 64 MB/s,
although the mean data rate will be considerably less.
The 12-m Array configurations have been designed so that in the most extended configurations the spatial
angular resolution will be as small as 5 milliarcseconds at 950 GHz. The specific 12-m Array configurations
available for Cycle 3 as well as the configuration schedule will be published in the "Capabilities" Appendix of
the ALMA Proposer’s Guide and described in more detail in Chapter 7.

2.3

The Atacama Compact Array (The Morita Array)

Using an interferometer to obtain images of extended or large-scale structures leads to the well-known “zerospacing” problem (See Chapter 3). This problem arises from the constraint that, to avoid collisions, it is notpossible to pack antennas closer than their diameter, leaving a hole in the distribution of baselines at shortand zero baseline separations (corresponding to large angular structure). As a result, spatial information frombaselines shorter than the closed packing ratio is not recovered3 . This problem has considerable impact onobservations of extended 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 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 12-m 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 arrayelements available is published for each observing cycle.
The ACA is operated in a similar fashion to the 12-m Array. To achieve this unified operation, the ACA
system is as compatible with the 12-m Array as possible at the level of hardware, interface, data collection,and observing modes. When ALMA is complete, the standard observing modes for the TP Array will include
spectral line and continuum observations with raster or Lissajous on-the-fly (OTF) scans, position switching andfrequency switching. The raw time series signals from the ACA antennas are processed in the ACA Correlator(see Section 5.2) to produce the cross-correlated and auto-correlated data.

2.3.1

The 7-m Array

The 7-m Array is composed of twelve 7-m diameter antennas designed and built by East Asia to the ALMA
specifications (See Appendix A). Similar to 12-m Array antennas, each antenna contains one front-end, including
a cryostat, amplitude calibration devices, and one 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 originate from and are identical to the ones sent to the 12-m Array(i.e., from the AOS building).
3 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

The ACA Correlator is normally used for the ACA, and can work with two sub-arrays. It is an FX correlator(Fourier transform first, then cross-correlate) with 3-bit input and 4 bits in the correlation. The correlator
generates 120 cross-correlations and 16 auto-correlations for each baseband. These are passed to a (special
purpose) 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
9 m to ∼30 m (Chapter 7).

2.3.2

The TP Array

The TP Array can fill in baseline coverage from 0 m to about 12 m, complementing the 7-m and 12-m Array’s
baseline coverage. It consists of four 12-m diameter antennas built by East Asia (See Appendix A). The
specifications of the TP antennas are almost identical to the 12-m Array elements. The TP antennas arelocated on stations surrounding the 7-m Array. The TP antennas will eventually be fitted with a nutating
subreflector (also known as wobbler or chopper) in full operations. 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.

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

Chapter 3

Principles and Concepts of Interferometry
3.1

Introduction

Interferometry is the technique ALMA uses to obtain very high angular resolution observations of astronomical
phenomena. In this Chapter, 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)

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.
We first provide a very basic picture of the core concepts behind how interferometry works. Interferometry

15

16

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

involves the combination of signals received from the sky by two physically separated antennas. The signals
are interfered, allowing a sky brightness distribution to be sampled on an angular scale smaller than possible
with a single antenna. The interference modifies the angular sensitivity of the antennas to include a sinusoidof constructive and destructive nodes. In this sense, the only emission measured by the interferometer is thatfrom 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., the amplitude of
the sinusoid, and the relative position of that brightness on the sky, i.e., the phase of the sinusoid.
A range of discrete angular scales can be sampled by including many pairs of antennas in an array. Importantly, by tracking a source across the sky, the rotation of the Earth can be used to change the projected
separations of the antenna pairs, allowing more angular scales to be sampled. An ensemble of the data, i.e.,
sinusoids of various amplitude and phase, can be then “summed” via the Fourier transform to produce an imageof the sky brightness distribution. How well this image reflects the actual sky brightness distribution depends
on how completely angular scales have been sampled. Interferometry, however, works extraordinarily well forobserving 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.

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. (The ALMA receivers have been designed to detect both modes, however.) As with alltelescopes, antennas bring incident EM power to a focus after reflecting it off a primary surface. The antenna
response, i.e., its sensitivity, is a summation of all EM power brought to the focus.
Antenna response is actually dependent on angle from the on-axis pointing direction of the antenna, due
to self-diffraction. To demonstrate the angular dependence, Figure 3.2 shows in the top panel the case for EM
power of wavelength λ arriving along the axis of an unobstructed antenna of diameter D. Since the source of the
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 as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.
constructively. 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
1.22λ/D radians, the path difference across the antenna diameter, the aperture, will equal one wavelength of
the incident emission. The combination of such emission at the focus leads to destructive interference at thatangle.
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)

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.

18

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

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 Beam Width between First Nulls (BWFN), and is given by:
BWFN 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 angleof the first null, i.e., its resolution, is ∼1.22 λ/D. Note that the HPBW measured from actual 12 m ALMA
antennas is ∼1.13 λ/D.
Up until now, we have described an idealized antenna. Actual antenna power response can be altered byvarious 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19

3.3. VISIBILITIES AND APERTURE SYNTHESIS

designed (via an illumination pattern with a -12 dB taper) 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).

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

(3.9)

20

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

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 large filled-aperture telescope with N elements has
N (N −1)/2 pairs of elements, and these could be observed sequentially to “synthesize” a measurement by a large
filled-aperture telescope. Alternatively, numerous pairs of antennas, with each antenna considered an element,
can be 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 a single 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.,with cables) 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 theposition 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)

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.
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 are incoherent, the time averagesof the correlation of those signals will be zero. Thus, the product of the integrals in Equation 3.13 can be
simplified to:ZZ
hV1 V2 i = h
V1 (l, m)V2 (l, m)dldmi
ZZ
hV1 V2 i =

hV1 (l, m)V2 (l, m)idldm(3.14)(3.15)

22

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRYZZ
hV1 V2 i =

hV1 (l, m)2 ie2πi(ul+vm) dldm

ZZ
hV1 V2 i ∝I(l, m)e2πi(ul+vm) dldm

(3.16)(3.17)

The correlator therefore measures a quantity known as the complex visibility, V, which is formally the Fouriertransform 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 phase φcontains information about the location of brightness with spatial frequencies u and v relative to the phasecenter.

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 complex conjugates of each other, and each contains
the same amount 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 thefringe 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23

3.5. FIELDS-OF-VIEW AND MOSAICS

actually Hermetian complex numbers, 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, knowledge of the distributionof visibilities across the uv-plane is needed. Improving coverage of visibilities over the uv-plane can be donein several ways. First, multiple antennas can be incorporated into an array, with each at a different distancefrom 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 be observed repeatedly
by the array as it appears to move across the sky due to the Earth’s rotation. Though the physical distances
between the antennas do not change, their projected distances do change depending on the altitude and azimuthof the target. Hence, repeated observations by all the pairs in an array can sample many visibilities across theuv-plane. Finally, antennas in the array may be arrangeable in several configurations so that pairs of antennas
have different distances and can sample different parts of the uv-plane. The combination of these schemes canreasonably 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 in the preceding section, such antennas have their own power responseon the sky PN (i.e., the Airy function = A(l, m)). 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 interferometric image. 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√
can have uniform sensitivity if the observed positions are spaced by λ/( 3D), where D is the diameter of
the antenna. In this case, Nyquist sampling is achieved and 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 theedge of the mosaic. Mosaics can be made with adjacent positions that are spaced either closer or more distant
than the Nyquist spacing, 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.

3.6

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

24

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY(i.e., lower than those sampled by the smallest baselines) results in an intrinsic lack of sensitivity to large-scale
emission. It is important 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 the antenna
power response with the point spread function, b(l, m) = F T −1 {B(u, v)}, the Fourier transform of the uv-plane
sampling distribution. The point spread function is sometimes called the synthesized beam or the dirty beam.
Again, the central feature of the antenna power response is called the primary beam. In addition, the image
resulting from the Fourier transform of a finite number of visibilities, I D (l, m), is sometimes referred to as thedirty image.
The measure of how similar an image is to the true sky distribution is sometimes referred to as image
fidelity. Formally, image fidelity is the ratio of the maximum brightness of an image to its 1 σ rms noise level.
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 thatof the dirty beam. Moreover, the complex visibilities of the point source have the same amplitudes on all
observed angular scales. Of course, sources may appear point-like at low resolutions but may appear extended
in higher-resolution observations.
Figure 3.5 illustrates the concepts of dirty beam and dirty image and their impact on the recovered image.
Panels a and b (upper pair) show respectively the dirty beam and the related ensemble of locations observedin the uv-plane, i.e., the uv-coverage. Note in panel a the positive feature in the center of the dirty beam
distribution and the surrounding positive and negative features of lower amplitude. These latter features arise
from the incomplete sampling of the uv-plane seen in panel b. As an aside, note that two sets of uv-plane samples

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.)

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
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 an

26

CHAPTER 3. PRINCIPLES AND CONCEPTS OF INTERFEROMETRY

interferometer 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 7.5) 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 sources incompact configurations, the antenna in front blocks the reception by the antenna in the rear, causing the latterto have reduced sensitivity. This situation is called shadowing and affected data are typically removed from theensemble 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, thesame source can be observed in different configurations of the 12-m Array, with more extended configurations
providing higher angular resolutions. For sensitivity to extended structures, the more compact 12-m Arrayconfigurations or the more tightly clustered 7-m Array can be used. Finally, the individual Total Power (TP)Array antennas of the ACA can be used to map the largest angular scales and address the zero-spacing problem.
During proposal preparation, ALMA users should take note of the maximum recoverable scale needed to ensurethat the proposed observations will be able to recover the scales needed to address the science in question.

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 skybrightness distribution for the simulations. The frequency of the emission has been changed to 100 GHz, andits 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 in total. The resulting dirty images
were CLEANed. Panel b (upper right): The high-resolution image of the galaxy obtained when observed in
an ALMA configuration with minimum and maximum baselines of 40.6 m and 1091.0 m, respectively (C326). The resulting synthesized beam is ∼0.5500 and the maximum recoverable scale is 6.600 . Panel c (lowerleft): Medium-resolution image of the galaxy when observed in an ALMA configuration with minimum andmaximum 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 whenobserved 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

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. Assuming the SNR of the individual datasets is high, combination is best done in thevisibility 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), where2kν 2Sν = 2c

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)

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

3.8. UNITS AND CONVERSIONS

29

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 3, 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 3 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
6.5.1) 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 6.5.1). 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 6.5 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 6.5.1).

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

4.2

The Cycle 3 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 3, 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.

4.2.1

Band 3 receiverBand 3 is the lowest frequency band available in Cycle 3, 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 4.3). A single feedhorn feeds an ortho-mode-transducer (OMT) which splits the two linear
polarizations and feeds the SIS mixers.

Figure 4.3: 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 shown4.2. THE CYCLE 3 RECEIVERS

35

in Figure 4.4. 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.

Figure 4.4: 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.

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 4.5) 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 4.6).

36

CHAPTER 4. RECEIVERS

Figure 4.5: Band 3 zenith transmission for 1, 5 and 15 mm of PWV. Frequency is in GHz.

Figure 4.6: 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.)

4.2. THE CYCLE 3 RECEIVERS

4.2.2

37

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 4.7). A single
feedhorn feeds an ortho-mode-transducer (OMT) which splits the two linear polarizations and feeds the 2SB
SIS mixers.

Figure 4.7: 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 4.8. 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 4.9 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 4.10.

38

CHAPTER 4. RECEIVERS

Figure 4.8: 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).

4.2. THE CYCLE 3 RECEIVERS

39

Figure 4.9: Band 4 zenith transmission for 0.5, 1 and 5 mm of PWV. Frequency is in GHz.

Figure 4.10: 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.)

40

4.2.3

CHAPTER 4. RECEIVERS

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 4.11). 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 4.12.

Figure 4.11: 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 4.13 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 4.14.

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

4.2. THE CYCLE 3 RECEIVERS

41

Figure 4.12: 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).

42

CHAPTER 4. RECEIVERS

Figure 4.13: 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 4.14: 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.)4.2. THE CYCLE 3 RECEIVERS

4.2.4

43

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 4.15).
A block diagram of the Band 7 receiver, including the cold cartridge and warm cartridge assembly, is shown in
Figure 4.16.

Figure 4.15: 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 4.17 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 4.18. 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.

44

CHAPTER 4. RECEIVERS

Figure 4.16: 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.

4.2. THE CYCLE 3 RECEIVERS

45

Figure 4.17: 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 4.18: 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.)

46

4.2.5

CHAPTER 4. RECEIVERS

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 4.19).

Figure 4.19: 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 4.20. 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 4.21 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 4.22.

4.2. THE CYCLE 3 RECEIVERS

47

Figure 4.20: 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).

48

CHAPTER 4. RECEIVERS

Figure 4.21: 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 4.22: 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.)

4.2. THE CYCLE 3 RECEIVERS

4.2.6

49

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 4.23).

Figure 4.23: 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 3, 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 6.5.1), covering 4-12 GHz. A block diagram of the Band 9 receiver, including the cold cartridge andwarm cartridge assembly, is shown in Figure 4.24.
The Band 9 atmospheric transmission is significantly dependent on the PWV, as illustrated in Figure 4.25
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 4.26 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.

50

CHAPTER 4. RECEIVERS

Figure 4.24: 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.

4.2. THE CYCLE 3 RECEIVERS

51

Figure 4.25: Band 9 zenith transmission for PWV = 0.2, 0.5 and 1 mm. Frequency is in GHz.

Figure 4.26: 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.)

52

4.2.7

CHAPTER 4. RECEIVERS

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 4.27). The mixers are double sideband (DSB), and therefore LO offsetting is used to reject oneof 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 6.5.1), covering 4-12 GHz. A block diagram of the Band 10 receiver,including the cold cartridge and warm cartridge assembly, is shown in Figure 4.28.

Figure 4.27: 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 4.29
for 3 low values of PWV. Figure 4.30 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.

4.2. THE CYCLE 3 RECEIVERS

53

Figure 4.28: 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).

54

CHAPTER 4. RECEIVERS

Figure 4.29: Band 10 zenith transmission for PWV = 0.2, 0.5 and 1 mm. Frequency is in GHz.

Figure 4.30: 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.)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-correlation and auto-correlations of them for each pair of antennas, and producescomplex visibilities that users will receive 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 are processed in one of two correlators: the 64-input Correlator (also known
as the Baseline Correlator) and the ACA Correlator. The 64-input64-input Correlator is used primarily for themain 12-m Array, while the ACA Correlator is used for the ACA 7-m Array and the Total Power Array (i.e.
single-dish) observations, respectively2 . Both correlators run simultaneously and independently. Thus, whilethe 12-m Array observes an object using the 64-input Correlator, the ACA Correlator can be used with the 7-m
Array or the Total Power Array observing either the same or a different object.
The received celestial signals 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 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 using the 12-m
Array and the ACA 7-m Array, and also pointing and focus calibrations for all Arrays.
This chapter addresses capabilities of the correlators to be offered for Cycle 3 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.

55

56

CHAPTER 5. THE CORRELATORS

5.1

The 64-input Correlator

The 64-input Correlator employs hybrid design, also known as the FXF3 system (Escoffier et al. 2007, A&A
462, 801), that brings a 32× spectral resolution of the traditional lag correlators (XF). 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 3. 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 ×2 polarizations.

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 datastream. The correlator array (lower half) produce auto-correlations on the matrix diagonal
and cross-correlations elsewhere. 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 (seeSection 5.3).
The TDM mode provides a SPectral Window (SPW)5 that consists of up to 256/Npol channels per BB,
3 F, X and F stand for filtering, correlation and Fourier transform, respectively.

Nant (Nant − 1)
= 2016 baselines and 64 auto-correlations for Nant = 64.
2
5 An SPW is a contiguous spectrum whose frequency channels are uniformly spaced. See also Chapter 6 about the relation
45.1. THE 64-INPUT CORRELATOR

57

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
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 6.5.1.

5.1.2

FDM mode

FDM is used for spectral-line observations that require a higher spectral resolution than of TDM.
Each 2-GHz BB is split into 32 62.5-MHz sub bands via the TFBs that employ digital filtering with Field
Programmable Gate Arrays (FPGAs). A TFB outputs digital 2-bit (4-level) re-quantized7 digital signals with
the Nyquist sample rate of 125 MHz. The sub bands are trimmed by 15/16 to avoid aliasing and band-edge filter
responses, and are set at intervals of 58.59375 MHz. The correlator stitches up multiple sub bands to output a15
seamless 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 sub bands to form an
SPW 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 different SPWs, multiple SPWs in the same BB must have the same channel spacing.
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 TFB is capable at 2-, 3-, or 4-bit re-quantization, the cross-correlation processor accepts only 2 bits in Cycle 3. See
also Section 5.3.

58

CHAPTER 5. THE CORRELATORSThe center frequency of each SPW can be tuned over the 2 GHz-wide BB using a digitally-synthesized LO(the TFBLO, or LO4), with some constraints. For examples, the edges of the full bandwidth of the sub-bands
cannot fall outside the 2 GHz BB range. The tuning must be at a 30.5-kHz step (see LO Appendix B in the
Appendix). See also Section 5.5.2 for detail about spectral setting.

5.1.3

Correlation and realtime processing

The correlation module performs the multiply-and-add operations to produce correlation functions at a clock
rate of 125 MHz (4 GHz samples demultiplexed by 32). Four quadrants handle four BBs. A quadrant of thecorrelator consists of 32 planes of 64 × 64 256-lag correlator circuits, and it yields auto-correlations and crosscorrelations of 64 antennas8 with 8192 lags for a BB with a dual polarization. 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 detail spectral setups, see Chapter chap:spectral-setup. 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 about the processing of the data in thecorrelator.

5.2

The ACA Correlator

The ACA Correlator is dedicated for 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 four 12-m
antennas9 . The ACA Correlator employs the FX10 design, whereby the incoming time-domain data stream
is converted into frequency-domain spectrum via Fast Fourier Transform (FFT) before cross multiplication toform power spectrum. The FFT part always accepts a full 2-GHz bandwidth and outputs 524288-ch spectrawith a frequency resolution of 3.815 kHz. This design allows us 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, Frequency Profile
Synthesis (FPS) is performed in the Correlator Data Processor (ACA-CDP) computer so that the outputs ofboth correlators are matched (Kamazaki et al. 2008, ALMA Memo 580).
A detailed diagram of 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 spectrum11 (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 corresponds 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 designatedbefore output to the ACA-CDP computers in the Computing subsystem through optical fibers.

8 2016 cross-correlations (real and imaginary) and 64 auto-correlations (real) totals 4096 real correlations.
9 Since the sub-array function will not be available in Cycle 3, the 7-m and the TP array observations cannot be operated
simultaneously.
10 F and X stand for Fourier transform and correlation, respectively.
11 220 -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

59

Figure 5.3: Block diagram of ACA Correlator. Time-series data from each antenna are divided in the time
domain and processed in an 8-way parallel stream. FFT is performed using FPGA, resulting in signals in the
spectral domain which are then be correlated. The auto and cross-correlation data are then accumulated intime, 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 and processing.

60

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
The ACA-CDP performs further spectral processing such as FPS and temporal integration, before data issent 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

7-m Array

The 7-m Array consists of twelve 7-m antennas whose correlation is dedicated in the ACA Correlator. The
purpose of the 7-m Array is to cover low spatial frequencies in the (u, v) coverage and to enhance 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. THE ACA CORRELATOR

61

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.

62

5.2.2

CHAPTER 5. THE CORRELATORS

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 3. Single-dish dedicatedobserving modes such as position switching, raster scan, and OTF will be employed for the TP Array. Fast
switching (∼ 10 Hz) using the nutating subreflector will not be capable in Cycle 3.

5.3

Digitizers

A digitizer is a device to convert continuous waveforms (analog) into digital form sampled at discrete timings
and quantized voltage levels. 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
cover the analog BB signals at the frequency band of 2–4 GHz, the digitizer samples at the Nyquist frequencyof 4 GHz with the voltage quantization of 8 levels (3 bit per sample). However, the 64-input Correlator reduces
the quantization levels to 2-bit per sample at the station card. The ACA Correlator handles 3-bit digital formin FFT and the spectrum is re-quantized in 4-bit before cross multiplication. These quantization processes
affect sensitivity and linearity in power spectra. The quantizations in the 64-input and the ACA Correlators
yield sensitivity loss of 12% (TDM) or 16% (FDM) and 4.8%, respectively, if input power of analog signals isadjusted at the optimal level. See also Section 5.6.1 for detail.

5.4

Online WVR Correction

Water Vapor Radiometer (WVR; see Appendix A.6 for technical description) is a device to measure the amountof Precipitable Water Vapor (PWV) in order to correct pathlength fluctuations in the troposphere. The CDPof the 64-input Correlator applies a correction of the pathlength fluctuation, for each dump duration, basedon the measurements of WVRs equipped on 12-m antennas. The online WVR correction reduces variancein visibility phases and enables longer-time integration of the visibilities (thus slower output rate) keeping
coherence. Although the time integration is a irreversible process, the WVR data are recorded together withthe visibilities.
The WVR correction will not be applied in the ACA Correlator because the array is so compact that PWVfluctuation doesn’t matter.

5.5

Capabilities of the Correlators

5.5.1

Polarization

Both correlators are capable of polarimetry by producing correlations of hXX ∗ i, hXY ∗ i, hY X ∗ i, and hY Y ∗ i.
These correlations relate to the Stokes visibilities of I, Q, U , and V as

 


I
1
0
0
1
hXX ∗ i /(GX G∗X ) Q   cos 2ψ − sin 2ψ − sin 2ψ − cos 2ψ   hXY ∗ i /(GX G∗ ) 
Y

 

,
(5.1)
 U  =  sin 2ψ
cos 2ψ
cos 2ψ
− sin 2ψ   hY X ∗ i /(GY G∗X ) 
∗
∗
V
0
−i
i
0
hY Y i /(GY GY )where GX and GY stand for complex antenna-based gains in X and Y polarizations and ψ is the parallactic
angle. This formula doesn’t include cross-talk, also known as ‘D-terms’, whose calibration will be discussed in63

5.5. CAPABILITIES OF THE CORRELATORS

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 3.

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/FPS
ACA/FPS
ACA
ACA
ACA
ACA
ACA

Bandwidth(MHz)

Number of Ch.

Ch. spacing
(MHz)

2000a
1875
938
469
234
117
58.6
2000/1937.5b
2000/1992.2b
1000
500
250
125
62.5

128
3840
3840
3840
3840
3840
3840
128/124
4096/4080
4096
4096
4096
4096
4096

15.625
0.488
0.244
0.122
0.061
0.03050.015315.625
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. TDM and FDM
stand for the Time Division Mode and Frequency Division Mode of the 64-input Correlator. For the ACA
Correlator, spectral performances with/without FPS (Frequency Profile Synthesis) are described. FPS doesn’t
reduce available bandwidths in narrower bandwidth modes. NOTE: The channel spacing is not the same as
the spectral resolution because of the applied weighting function; for calculating spectral resolution. a: Usablebandwidth except band edges is ∼ 1875 MHz. b: Application of FPS trims both band edges for the case of
2-GHz bandwidth but other narrower cases.
The spectral profile which the correlators output is a convolution of the true spectrum with the spectral
resolution function shown in the figure of Table 5.2. The spectral resolution function is given by Fouriertransform of the weighting function applied to the correlation function in the lag domain. The spectral resolution
is often characterized by the FWHM (full width at half maximum) of the spectral resolution function.
The uniform weighting in the lag domain results in the sinc function with the FWHM of 1.21× the channel
spacing and yields spectral sidelobes that causes ‘ringing’ in the spectra when a narrow line, interference spike,or strong edge channels are present. Alternative weighting functions12 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 wherea line profile spreads over several spectral channels. The choice of a weighting function is a trade off between
resolutions and sidelobes. The default weighting function is the Hanning function, which gives the spectral
resolution of 2.0 × 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, and select the
setup in the Phase 2 SB.
Channel averaging is available to bin or average spectral channels on the CDP. Channels can be averaged
12 For a full description, see http://mathworld.wolfram.com/ApodizationFunction.html.

64

0.6

−0.217−0.026+0.007+0.047+0.001−0.086half maximum
0.4

1.21
2.00
1.82
1.77
2.30
1.59

-0.2

Uniform
Hanning (default)
Hamming
Bartlett
Blackmann
Welch

Spectral Response

Max sidelobe

0.2

FWHM (ch)Uniform
Hanning
Hamming
Bartlett
Blackmann
Welch

0.0

Weighting

0.8

1.0

CHAPTER 5. THE CORRELATORS

Table 5.2: Spectral resolutions (FWHM) and the maximum sidelobe levels for different weighting functions. Corresponding spectral resolution functions are illustrated in the right plot.

-3

-2

-1

0

1

2

3

Frequency [channel]

together in factors of N=2, 4, 8, or 16. The main purpose is to reduce the data rate to the archive and thetotal 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 that 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 ofN, 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)
1875
937.5
468.8
234.4
117.2
58.6

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

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

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

Table 5.3: Spectral resolution and channel spacing (in brackets) in kHz for different correlator bandwidth modes(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 (for N=16). 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, then the number ofchannels be reduced 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. The FPS
In the case of the ACA Correlator, the spectral resolution function in voltage spectrum is given by a sincfunction, so that of the (cross) power spectrum is a sinc2 function, without additional weighting. FPS is usedin the CDP in order to match the spectral resolution function to that of the 64-input Correlator. Since FPS isa convolution process with an artificial spectral profile with a limited-length support, this process reduces the
bandwidth at both band edges, in the case of 2-GHz SPW, as listed in Table 5.1.

5.5. CAPABILITIES OF THE CORRELATORS

5.5.3

65

Time Resolution

As shown in Figure 5.7 the correlated data are processed in the CDP and accumulators before archived. The
time resolution 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)

must be lower than the acceptable data rates described below. Here, Nant , NBB , Nch are number of antennas,
BBs, and spectral channels (sum of polarization products), respectively. Nbyte (bytes/visibility) is the byte sizeof a real or imaginary part of visibility. Tint is the integration time in the correlator. For typical instance, aconfiguration of Nant = 32, NBB = 4, Nch = 3840 × 2 polarization products (XX and Y Y ), Nbyte = 2 andTint = 6 sec yields 10.5 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
trade off between time resolution, spectral resolution, polarization, number of BBs, and number of antennas.

Figure 5.7: 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.

66

CHAPTER 5. THE CORRELATORS• 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, the verified data rate is 26 Mbytes/sec to date. As in
Cycle 2, in Cycle 3 the maximum data rate is presumed to be regulated at 17 Mbytes/sec. The 64-input
Correlator employs Nbyte = 2 or 4, depending on a required dynamic range of visibilities.
• Integration duration of spectral data with the ACA Correlator
The ACA Correlator employs Nbyte = 4 and the dump time of 1 ms and 16 ms for auto-correlation andcross-correlation, respectively. The maximum data rate from the ACA Correlator is 3.6 MB/s, independentof the number of antennas. However, the average data rate to the archive will be lower during typicalobserving, because of overheads and the use of TDM modes during some observing.
• Integration duration of online WVR Correction
When online 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 3, 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 of digital signals involves reduction of information and causes sensitivity loss. The ALMA digitizer
employs 3-bit (8-level) quantization13 , and additional re-quantization processes are applied in the correlators.
In Cycle 3, TDM of the 64-input Correlator makes use of 2-bit that yields the quantization efficiency of ηQ =0.88. For the case of FDM, digital filtering is applied to 3-bit quantized signals followed by 2-bit re-quantization.
The two stages if quantization would cause the multiplied quantization efficiency of ηQ = 0.96 × 0.88 = 0.85
if they were independent (Escoffier et al., ALMA Memo 556), nevertheless, the real efficiency can be slightly
better than the multiplication (Iguchi et al. 2005, PASJ 57, 259)14 .
The ACA Correlator feeds 3-bit quantized signals into the FFT processors where butterfly arithmetic is taken
in 16-bit precision. The spectrum of FFT output is re-quantized in 4-bit (16 levels) before cross multiplication.
The combination of these quantizations results in loss of 4.8% (i.e. ηQ = 0.952; Kamazaki et al. 2012, PASJ64, 29).
The quantization efficiencies above are theoretical values under optimal conditions of the input signal level
and threshold voltages. Although level adjustment is taken for every scan sequence, significant variation of power
level (e.g. observation of strong sources, unstable weather, or frequency band near atmospheric absorption lines)
can violate the condition to reduce the quantization efficiency.
13 The quantization efficiency would be η = 0.96 if optimal signal levels, threshold voltages, and perfect signal processing wereQ
performed (Thompson 1998, MMA Memo 220).
14 It is reported that the combination of 2-bit quantization, digital filtering, and 2-bit re-quantization yields η
Q = 0.81, better
than 0.88 × 0.88.

67

5.6. PRACTICAL PERFORMANCE

5.6.2

Linearity

Digital quantization also causes non-linearity in visibility measurements. The correlation coefficient of quantized signals is a function the analog response (i.e. infinite quantization levels), also known as the Van Vleck
relationship, is used for the non-linearity correction.
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 5.8: Van Vleck relationship of 2-, 3-, and 4-bit quantizations at the optimal signal power level andthreshold voltages. (Right): Correlation coefficient of digitized signals as a function of analog correlation
coefficients, ρ. (Left): Departures of the Van Vleck relationship from linear relation employing single factor ofη4 = 0.881, η8 = 0.963, and η16 = 0.988 for 2-, 3-, and 4-bit quantizations, respectively.
Figure 5.8 shows the Van Vleck relationships in 2-, 3-, and 4-bit quantizations. The correlation coefficientsof quantized signals keep adequate linearity for small correlation coefficients15 . This indicates that for mostsources the cross-correlation response is effectively linear.
However, auto-correlations are affected by the non-linearity because the correlation coefficient at zero lagmust be unity by definition. The non-linearity in auto-correlation power spectra influences system temperature
measurements and the TP Array observations. In the case of 64-input Correlator, the 2-bit Van Vleck correction
will be applied in the CDP or every integration period. For TP Array observations, a single constant correction
factor is applied to the spectra to mediate the non-linearity. This subtle difference from the Van Vleck correction
and the simple correction yields up to ±5% systematic error in amplitude of spectral lines.

5.6.3

Integration time intervals, channel-average and spectral data

The correlators produce two datasets: the spectral data, and the channel-averaged data. These are written to
the archive from the CDP at different rates (see Figure 5.7). The channel-averaged data is a single complex
number for each SPW. In the case of FDM, the data is truncated in the CDP before averaging (only the central
15/16 are used). For TDM no truncation is applied. The primary purpose of the channel-averaged data is toprovide a smaller dataset for TELCAL, the ALMA online processing software, to compute real-time telescopecalibration corrections. It is stored in the ALMA Science Data Model (ASDM) dataset as a separate SPW (see5.6.6). Note that this should not be used as science continuum data in normal observing, but the continuum
should be constructed offline in Common Astronomy Software Applications (CASA) using the appropriate
portions of the spectral data. The spectral data contains the requested number of channels for each polarization
product. The time intervals involved at this stage of the observing and data acquisition are also shown in Figure5.7. In detail, they are:15 The departure from linear relation is δρ/ρ < 10−3 for ρ < 0.2

68

CHAPTER 5. THE CORRELATORS

Dump duration: The internal time period inside the correlator (16 ms for cross-correlations and multiples
of 1 ms for auto-correlations) over which data is accumulated before sending to the CDP. Data can becorrected for atmospheric phase fluctuations using the WVR correction once every dump duration in the
CDP, or offline in CASA once every Spectral Integration Time (see below). During observations with the
64-input Correlator in Cycle 3, the dump time should be a multiple of 48 ms in FDM and 32ms in TDM.
A dump duration of 480 or 960 ms is typically used, and it should not be more than the dump time of
the WVR system. It is always 16ms on the ACA Correlator.
Channel-average duration: This is the time interval between channel average data being written to the
ASDM. The channel average time must be a multiple of the dump duration. This should be also kept
small (i.e. ≤ 1 second), because this is the dumptime of the WVR system.
Spectral integration duration: The spectral integration duration is the shortest integration time before thefull-resolution spectral data is written to the ASDM. It is also the shortest time interval that can beselected (and potentially self-calibrated) in CASA. The spectral integration time must be a multiple ofthe channel average time. For Cycle 3 observations using FDM, a Spectral Integration time of several
seconds is used to avoid data rate problems (see 5.6.5). For TDM observations, which have fewer channels,
a faster rate can be used.
Subscan duration: A further time interval, not shown in Figure 5.7, is the subscan duration or time. Inan observation, this will effectively be the shortest time interval where no parameter is changed in thesystem. For example, this could be a single integration on a source, one point of a mosaic, one scanof a raster, integration at one frequency, or on one of the loads, etc. The subscan duration must be amultiple of the spectral integration time. Typically a subscan might be 30 or 60 seconds; the ASDM
might therefore contain 5-10 spectral integration times per subscan, resulting in 5-10 rows of data perbaseline/polarization/BB product.
Scan time: Total time per scan. Must be a multiple of the subscan duration. This might be as long as 5
minutes or more in the case of an on-source integration in a single field of mosaicing observations.

5.6.4

Online WVR correction

Semi-realtime correction of pathlength fluctuations are done in the CDP using the WVR data from each antenna.
The advantage of doing WVR correction in realtime is that it can be performed relatively rapidly (up to thelargest value of the dump duration or the WVR chopper wheel rotation and readout period, approximately 1
second), thus enabling corrections to be made for faster variations in atmospheric transmission. At the sametime, corrected data can be integrated in the CDP, allowing data to be transferred from the correlator to thearchive at a slower rate. Note that once the data are combined, the online WVR correction is non-reversible.
For some time during Cycle 3, it is expected that both the online corrected and the uncorrected data will
be written to ASDM once every Spectral Integration Time (although note that this will double the overall data
rate; see Section 5.6.5). So, as in previous cycles, it will be possible to do the WVR correction offline on theslower uncorrected data (or even not to do any WVR corrections). But it is expected that the online WVR
corrections will track the sky more accurately, and this data will eventually be used directly. The optimal
method of WVR correction, potentially including a combination of online and offline corrections, is still underinvestigation.
7m-antennas do not have WVRs and the intention is to use the WVR correction derived from the TP
antennas, although more testing is required before this is fully operational.

5.6.5

Correlator speed and data rates

Although the specification (correct the spelling - specificaiton) of the maximum data rate from the 64-input
Correlator is 62.5 Mbytes/s, it has been verified up to 26 Mbytes/sec to date. In Cycle 3 it will again be
regulated to about 17 Mbytes/sec; the same as as what was offered in Cycle 2. For the ACA Correlator the5.6. PRACTICAL PERFORMANCE

69

maximum data rate is 3.6 Mbytes/s. These rates set limitations on the shortest value of the spectral integration
time in the correlator, particularly in FDM mode, where the number of channels without spectral averaging is
32 times larger than TDM mode. The FDM raw data rate (in Mbytes/sec) is approximately
NA (NA − 1)/2 × Nbb × 8192 channels × (4/106 )M bytes/IT(5.3)

where NA is the number of antennas, Nbb is the number of BBs (normally 4) and IT the spectral integration
time. Note that this rate will double if both WVR online-corrected and uncorrected data is required from thecorrelator. As in Cycle 1, the usual FDM spectral integration times set in the SBs are typically expected to be
6 seconds; this may be increased if the on-line WVR correction proves to give accurate and reliable path-length
corrections. So under most circumstances the maximum data rate limitations should not have any impact on
the science that can be done in Cycle 3, as it is expected that these high values will seldom be reached.
Note that the average data rate to the archive will be considerably lower than the maximum correlator data
rate, because of observing overheads and the fact that some data taking within an SB will be in TDM rather
than FDM mode (eg pointing and atmospheric calibration). The maximum average data rate to the archive iscurrently 6.6Mbyte/s (see Chapter 14).

5.6.6

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 (eg 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 dimensions of
N channels per polarization product (for example 128 or 3840), and a second "hannel averaged version with one
channel per polarization product (this averaging is done in the correlator). The channel averaged data are usedby the on-line telescope calibration system (TELCAL) and for real time diagnostic purposes (QuickLook), andare typically not used downstream in the data reduction. Overall, this can lead to ASDMs with a large numberof spectral windows. For example, a typical science observation in FDM mode can have upwards of 25 spectral
windows. Luckily every scan/SPW combination has an "intent" associated with it that indicates its purpose(pointing, system temperature, science, etc). This 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 outline the ALMA local oscillator (LO) system and the various functions that it performs,
how to define spectral setups from the user viewpoint and how these are used to set up the LO system, as
well as some of the other points pertaining to the frequncy setup. In the later sections, we go into more detailabout the hardware, outlining the signal path between the frontends and correlators, the LO chain and the LO
distribution system, and describing some of the major LO components.
To the ALMA system, a spectral setup effectively consists of the settings of the local oscillators and correlator,
such that each spectral window (SPW) covers the desired lines and/or continuum frequencies. To the end-user,
the spectral setup is normally defined in the Observing Tool (OT) just in terms of the observing frequencies,
spectral window bandwidths and spectral resolutions: there is no need to worry about the details of each LO
setting. For full details of the OT and how to use it, see the user manual and reference manuals, available fromthe ALMA website1 (and also in the OT itself).
The following sections describe how to use the LO system. For those interested in the details of the components and how the hardware works, please jump to Appendix B.

6.1

Introduction

ALMA allows up to four 2-GHz wide Basebands to be placed within the IF range of the frontends using LO2.
Furthermore within each baseband it is possible to place up to 32 Spectral Windows (SPWs). Each Spectral
Window (SPW) forms a final contiguous spectrum, with bandwidths in FDM mode from 58.6 MHz up to 1.875
GHz wide (see Section sec:ubw). Using the OT during both proposal preparation by the PI (Phase 1) andscheduling block (SB) creation by ALMA staff (Phase 2), the user chooses the frequencies (or transitions) to
be observed and the required spectral window bandwidths or spectral resolutions, and the OT will look forthe best solution for the settings of the LOs, correlator etc. ALMA uses heterodyne conversion to shift thesignals from the frontend sky or observing frequency down to a range where electronics can be used to performthe digital sampling and cross-correlations. In general, the signals of frequency fsig are mixed to Intermediate
Frequency (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 the other signals. The output signal
may correspond to an input frequency above or below fLO , known as the upper and lower sideband (USB or
LSB).
During the spectral tuning, there are effectively four different LOs which are set up by the system:• LO1 which sets the frontend tuning frequency• LO2 which positions the basebands within the frontend receiver IF (each baseband uses a different LO2,
hence there are four LO2s)
1 http://almascience.org/documents-and-tools/

71

72

CHAPTER 6. SPECTRAL SETUPS• 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 all these LOs based on the required 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. Alternatively, no solutions may be possible, and the OT will flag this. A more detailed
description of the LO operation is given in Section B.2. Cycle 3 has similar restrictions on the spectral setups andtuning as Cycle 2 (see Table 6.2 in section 6.6). The main limits are that the edges of the 2 GHz basebands cannot
lie outside the receiver tuning range listed in Table 4.1, and the edges of the (untruncated) spectral windows
cannot lie outside the 2 GHz-wide basebands 2 . The settings of the SPWs in each baseband are independent, so
the resolution and correlator mode as well as the value of LO4 can be different in each baseband. So for example
it is possible to have a 62.5 MHz-wide SPW centered on a particular line in baseband 1, and simultaneously
use a broadband time division multiplexing mode (or TDM mode - see correlator chapter) for all the otherbasebands. Cycle 3 also allows for multiple FDM spectral windows within each baseband, described in Section
6.3.2 below. 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 average velocity of stars in 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.
2 Actually in Cycle 3 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.

6.3. SPECTRAL SETUP: MULTIPLE LINES AND CONTINUUM

73

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 Setup: Multiple lines and Continuum

The wide IF bandwidth and tuning ability allows for 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). Notethat in many cases the lines will not necessarily appear in the center of the SPWs (for example, in the Band
6 combination given). When <4 spectral windows are required for the primary lines, the others can be set up
to cover fainter lines or to observe the continuum, potentially in TDM mode. The selection of secondary lines
to be observed can be done using the OT spectral interface. In the case of continuum SPWs, to maximize thesensitivity, the widest bandwidth mode should be chosen in these SPWs (i.e. 1.875 GHz in FDM, or TDM –see Section 6.5.1). 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.

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 atmospherictransmission. For full continuum observations (without any required lines, or with only low resolution) the OT
has standard optimized frequencies for each band which can be selected in the OT Phase 1; these are noted inTable 6.1 and illustrated by the red in Figure 6.1.
If mixed line+continuum operation is desired, for example with a single line in SPW1 observed at frequency
f (GHz), the other SPWs (2-4) can be set up for continuum. For 2SB receivers, normally this would have SPW2
in the same sideband (offset by 2 GHz from f ) and SPW3 and 4 in the opposite sideband (offset by the frontend
center IF frequency, fIF ). The continuum SPWs should cover the maximum aggregate unique bandwidth. If sb
is the sign of the sideband of SPW1 (sb = +1 for USB, sb = −1 for LSB), then the four SPWs could be set up
as follows:• SPW1: f [SPW covering the primary line]• SPW2: f − 2.0 (in the same sideband, with a continuum SPW 2 GHz below the primary line)• SPW3: f − (2.sb.fIF ) (in the opposite sideband)• SPW4: f − (2.sb.fIF ) − 2.0 (in the opposite sideband)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 SPWs in the same sideband, so SPW3 and SPW4 would
be at f − 4.0 GHz and f − 6.0 GHz. Note that this is an approximate rule - if possible, adjustment of thecontinuum SPWs (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 6.1). Also, if contiguous spectral
coverage of the continuum is desired, the SPWs should be offset by 1.875 GHz rather than 2.0 GHz as suggested
above.

74

CHAPTER 6. SPECTRAL SETUPSBandSpecies/transition

Freq. (GHz)Sideb.

bandwidth

3a
3b *
4a
4b
6a
6b *
7a
7b *
7c
8a
8b
9a
9b
10a

Standard cont.
HCO+ 1-0
HCN 1-0
CH3 OH/H2 CO
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.

97.51
89.18888.632101.293/101.333
101.3
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
691.472685.436687.303674.009
875.0

dual
LSB
LSB
USB
USB
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

2 GHz/TDM
62.5 MHz62.5 MHz
125 MHz
2 GHz/TDM
2 GHz/TDM
125 MHz
125 MHz
125 MHz
125 MHz
2 GHz/TDM
125 MHz
2 GHz/TDM
125 MHz
125 MHz
2GHz/TDM
2 GHz/TDM
62.5 MHz62.5 MHz62.5 MHz
2 GHz/TDM
62.5 MHz62.5 MHz
125 MHz62.5 MHz
2 GHz/TDM
62.5 MHz
2 GHz/TDM
2 GHz/TDM
125
125 MHz
2 GHz/TDM
2 GHz/TDM
2 GHz/TDM
500 MHz
500 MHz
500 MHz
500 MHz
2 GHz/TDM

bb

SPW

1
2
3
4

1
1
1
1

1
2
3
4

1
1
1
1

1
2
3
3
4

1
1
1
2
1

1
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

Notes
LO1=97.5
HCO+ /HCN/H2 CO

LO1=145.0
CS/DCO+

LO1=233.0
J=2-1 CO isotopes

LO1=343.5
CO/HCO+ /HCN

J=3-2 CO + isotope

LO1=405.0
CI/13CI

LO1=671.0
CO/CS

LO1=867.0

Table 6.1: Examples of spectral setups possible in Cycle 3. 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 6.1. * Template spectral setup released with Cycle 3 version of
the OT.

6.3. SPECTRAL SETUP: MULTIPLE LINES AND CONTINUUM

75

Figure 6.1: ALMA bands available in Cycle 3 (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.

6.3.2

Multiple Spectral Windows in the Same Baseband

Cycle 3 allows the capability to have up to four SPWs in the same baseband. This is useful for projects where
several lines need to be observed simultaneously at high spectral resolution. In cases where four lines or fewer
are observed in total, if the full bandwidth/resolution is needed for each line and they are well-separated, it isoften better to place each line in a different baseband. In other 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 for maximizing the bandwidth for phase calibration. There are some
restrictions: each SPW within the same baseband must have the same resolution3 , and the correlator resources
used for one baseband (effectively the number of spectral channels, before channel-averaging) will be distributed
among the SPWs. An example of this is shown in Table 6.1 for spectral setup 6b, 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 than one spectral line in the same baseband. This will create SPWs with a correlator fraction less than
1.0 (so for 4 SPWs, each has a correlator fraction of 1/4). The number of SPWs may be increased up to 4 inCycle 3, however, the total number of spectral channels in each baseband is limited by this correlator resources
rule. So doubling the number of SPWs in one baseband will result in half the number of channels per SPW, someans either lower resolution or a reduced bandwidth per SPW.
Figure 6.2, which is adapted from the Phase 2 Spectral Editor of the Observing Tool (OT), illustrates amore complex spectral setup with multiple SPWs/baseband which is possible in Cycle 3. The lines observed
are given in Table 6.1 example 7b. The blue hashed area represents the receiver tuning range (in this case, asection of Band 7), and the curved line represents the nominal atmospheric transmission for the chosen PWV.
The 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 case by the green horizontal bars, can be moved around, but
only within the two sidebands. The spectral windows are also shown. In this example, baseband 2 is set for a
3 although, as before, SPWs in different basebands can have different resolutions

76

CHAPTER 6. SPECTRAL SETUPSTDM SPW covering the whole 2 GHz baseband for a continuum measurement. In some of the other basebands,
multiple spectral windows are used. Baseband 1 has 3 SPWs of 58MHz bandwidth and 960 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 partially overlap, as seen in this casewith bb3 and bb4. Many combinations of SPWs and basebands can be set up in this way.

Figure 6.2: 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 shows the possible tuning range of the frontend, and the curved line gives an indication of theatmospheric transmission. The bandwidths of the SPWs are illustrated by the widths of the horizontal bars.
The lines observed are given in example 7b in Table 6.1.

6.4

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 can

6.5. SPECTRAL SETUP IN BAND 9 & 10 AND DSB CONSIDERATIONS

77

be set to the closest valid frequency, resulting in an offset of the line from the SPW center (in this case, set to115.0 GHz and the line will be offset by 0.271 GHz). Another solution is to choose a narrow SPW bandwidth(e.g. 1 GHz or less); in this case the SPW will be offset from the center of the baseband, and the line will be at
the center of the SPW.

6.5

Spectral Setup in Band 9 & 10 and DSB Considerations

The spectral setup in Band 9,10 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.

6.5.1

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 6.3). 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 6.3.

Figure 6.3: 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).

78

6.5.2

CHAPTER 6. SPECTRAL SETUPS

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.

6.5.3

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 used in ALMA are:
Topocentric In this case no correction for the source or Earth motion is made. The Center Frequency - Restand 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 20.0kms−1 in the direction 18h , +30o
[B1900.0].
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 and the velocity of the observatory relative to the chosen reference
frame are normally used to set the center frequencies of the science SPWs4 . It is also possible to just make thecorrection for the motion of the observatory relative to the chosen reference frame, ignoring the source velocity
in that frame. This frequency setting for the science target will normally also be used in the same observation
for the bandpass and amplitude calibration. For sources with an external ephemeris file, the rate of changeof 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 with different velocities
must in done in CASA offline.

6.6

Limitations and Rules for Spectral Setups in Cycle 3

Although the correlators will eventually allow a broad flexibility of SPWs in a single observation, these abilities
are gradually being introduced and tested by the observatory before release. The current rules for spectral
setups are given in Table 6.2).

4 Note that ALMA does not do Doppler tracking, where the frequency would be continuously updated for Earth motion during
the observation. In ALMA it is only set once at the start of each execution.

6.6. LIMITATIONS AND RULES FOR SPECTRAL SETUPS IN CYCLE 3

Rule

Details

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 region 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 theedge of the anti-alias filter does not significantly affect the IF power. In practice it may bepossible to extend some part of the SPW to <50MHz of the IF edges; this is necessary for
the Band 6 setup 6b in 6.1, where the 12 CO and 13 CO lines are only 70MHz from the IFband 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.
Multiple spectral windows are allowed in a single baseband. However all the SPWs in thesame baseband are required to having the same bandwidth and resolution. An individual
SPW within a baseband may occupy 1, 1/2 or 1/4 of the resources (i.e. spectral channels)
available in the baseband and the sum of all the fractional resources used within one
baseband must be ≤1.

3.
4.

5.

8.
9.
10.

11.

Table 6.2: Rules for spectral setups.

79

80

CHAPTER 6. 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 = 0, . . . , 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:
V W (u, v) =N
X

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

(7.2)

k=1

In Equation 7.2, Rk , Tk and Dk are weights. Rk indicates the sensitivity of the k th visibility measurement
based on certain factors, such as the integration time, the system temperature, or the bandwidth. (Note thatthese factors are given by the instrument, technical set-up, and observing conditions, but not controlled by theimaging process.) Tk can be used to taper the outer edge of the uv-coverage, suppress small-scale sidelobes andincrease the beam width. Finally, Dk can be used to offset the high concentration of measurements near thecenter of the uv-plane and to reduce the sidelobes caused by gaps in the uv-coverage.
For the Dk weight, the following definitions are used commonly during the imaging process:• 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.

7.2

Cycle 3 Configurations

In Cycle 3, 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 information

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)
is 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 3, the 12-m Array, with 36 antennas, will be arranged in 8 different configurations. The maximum
baselines achievable will be 10 km for Bands 3-6, 5 km for Band 7 and 2 km for Bands 8-10. The 7-m Array,with 10 antennas, will be available in only one configuration. Due to insufficient baseline overlap, the twomost extended configurations, C36-7 and C36-8, will be offered alone and not in combination with any otherconfiguration. 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 and 7.3 show antenna locations for the configurations of the 12- and 7-m Arrays.
The two 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 users 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.

7.3

Shadowing

ALMA is located at latitude=-23.022917◦ , longitude=-67.754649◦ . During observations, particularly in very
compact configurations like those of the 7-m Array or C36-1, 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

83

7.3. SHADOWING

Configuration
7-m
C36-1
C36-2
C36-3
C36-4
C36-5
C36-6
C36-7
C36-8

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)

15.0
42.8
3.4
25.3
1.8
25.2
1.2
25.2
0.7
9.6
0.5
7.8
0.3
4.8
0.1
1.5
0.075
1.1

10.0
28.6
2.3
16.9
1.2
16.8
0.8
16.8
0.5
6.4
0.3
5.2
0.2
3.2
0.08
1.0
0.05
0.7

6.5
18.6
1.5
11.0
0.8
11.0
0.5
10.9
0.3
4.2
0.2
3.4
0.1
2.1
0.05
0.65
0.03
0.5

4.3
12.4
1.0
7.3
0.5
7.3
0.4
7.3
0.2
2.8
0.14
2.2
0.08
1.4
0.034
0.43
-

3.3
9.3
0.7
5.5
0.4
5.5
0.3
5.5
0.15
2.1
0.1
1.7
0.06
1.0
-

2.3
6.6
0.5
3.9
0.3
3.9
0.2
3.9
0.1
1.5
0.07
1.2
0.04
0.7
-

1.7
4.9
0.4
2.9
0.2
2.9
0.1
2.9
0.08
1.1
0.06
0.9
0.03
0.5
-

Table 7.1: θres and θM RS for the 7-m Array and 12-m Array configurations available during Cycle 3 as a functionof a representative frequency in a band. The value of θM RS is computed using the minimum baseline from Table
7.2 and equation 7.5; the value of θres is the mean size of the interferometric beam obtained through simulation
with CASA, using Briggs uv-plane weighting with robust=0.5. (This value of robust offers a compromise between
natural and uniform.)

Configuration
Minimum baseline (m)Maximum baseline (m)

7-m
8.7
32.1

C36-1
14.7
160.7

C36-2
14.7
376.9

C36-3
14.7
538.9

C36-4
38.6
969.4

C36-5
47.9
1396.4C36-6
77.3
2299.6

C36-7
248.3
6074.2

C36-8
346.5
9743.7

Table 7.2: Basic parameters of the 7-m Array configuration and the eight 12-m Array configurations offeredduring Cycle 3. The baselines are projected for a transiting source (HA = ± 0.5h) at a declination of −23◦ .
Note that C36-7 will not be available for Bands 8-10, and C36-8 will not be available for Bands 7-10.

84

CHAPTER 7. IMAGING WITH ALMA

C36-1

1000

500
Y (meter)Y (meter)

500

0

500

1000

1000
1000

500

0
X (meter)

500

1000

1000

C36-3

1000

Y (meter)Y (meter)0
X (meter)

500

1000

C36-4

500

0

0

500

500

1000

1000
1000

500

0
X (meter)

500

1000

1000

C36-5

1000

500

0
X (meter)

500

1000

C36-6

1000

500
Y (meter)500
Y (meter)

500

1000

500

0

0

500

500

1000

1000
1000

500

0
X (meter)

500

1000

6000

1000

4000

4000

2000

2000

0

2000

4000

4000
2000

0
X (meter)

2000

4000

6000

0
X (meter)

500

1000

C36-8

0

2000

4000

500

6000

C36-7

Y (meter)Y (meter)

0500

60006000

C36-2

1000

60006000

4000

2000

0
X (meter)

2000

4000

6000

Figure 7.2: Representative 12-m Array configurations for Cycle 3. Note that the scale changes for the final two
panels.

85

7.3. SHADOWING

20
7-m

15
10

Y (meter)

5
0
5
10
15
2020

15

10

5

0
X (meter)

5

10

15

20

Figure 7.3: Representative 7-m Array configuration for Cycle 3.
and can be quite severe for sources that are observed at very low elevation. Targets as far North as declination+40◦ , corresponding to a maximum source elevation at Chajnantor of ∼ 25◦ , can in principle be observed
from the ALMA site, but shadowing by adjacent antennas becomes an increasing problem at low elevations.
For example, Figure 7.4 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(C36-1). 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, isthat the uv coverage, and therefore the synthesized beam, will not be symmetric.

70

7-m
C36-1
C36-2

60

Shadowing (%)

50
40
30
20
10
0

80

60

40
20
Declination (Degree)

0

20

40

Figure 7.4: Shadowing fraction (%) for the most compact configurations as a function of declination.

86

CHAPTER 7. IMAGING WITH ALMA

1.6
1.4

θ (arcsec)

1.2λθ = Lmax

1.0
0.8
0.6
0.4
0.2
0.02.0

1.5

1.0

0.5

0.0

0.5

Robust factor (Briggs)

1.0

1.5

2.0

Figure 7.5: Angular resolution achieved using different values of the CASA robust parameter for a 1-hourobservation at 100 GHz in the C36-3 configuration. Note that robust = −2 is close to uniform weighting andλ.
robust = 2 is close to natural weighting. The dotted line corresponds to Lmax

7.4

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

kλ61800[arcseconds][radians] ≈Lmax
Lmax ν

(7.3)

where k is a factor that depends on the uv-plane weighting function, Lmax is the longest baseline in meters, λ isthe observing wavelength in meters, and ν the observing frequency in GHz. 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 weight based on its intrinsic uncertainty.
Uniform weighting, on the other hand, modifies the weights in such a 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 havea 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 7.5 shows the angular resolution
achieved for an observation with the C36-3 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 7.6 shows the different beam
shapes for sources observed at declinations of −70◦ (similar to the SMC and LMC) and −30◦ . Also, Figure 7.7
shows the uv-coverage for these sources, revealing the elongation of the uv-plane sampling distribution, together

87

7.5. RESPONSE AND SNAPSHOT

Figure 7.6: Beam shape for configuration C36-1 with a 2-hour observation of a transiting source at a declinationof either −70◦ (left) or −30◦ (right).
with the large fraction of shadowing, for the more southern sources. In order to mitigate this effect, one canconvolve the resulting images to a more circular (albeit larger) beam after deconvolution.
Figure 7.8 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 7.9 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., C36-8 is not available at bands
7-10.
Note that, in the OT, angular resolution is computed using Briggs weighting with robust = 0.5, while sensitivity
is computed assuming natural weighting. Thus, the final angular resolution achieved for a project with nominal
sensitivity may be slightly degraded by the use of natural weighting. The most appropriate value of robust
to use when imaging a dataset must be determined based on the goals of the scientific case (required angularresolution, sensitivity, etc). In cases where more 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 specific science use case. You should clean the images carefully, andyou should also add noise (and realistic systematic errors, if possible) to your simulations, to really see whatkind of residual sidelobes are expected. (Cleaning perfect data does not show the limitations that one mightobtain with real data.)

7.5

Response and Snapshot

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

δ(u − uk , v − vk )

(7.4)

k=1

If S were a continuous function, e.g., a Gaussian, the synthesized beam would also be a Gaussian i.e., a central
peak with a smoothly decreasing response away from the centre. However, given the finite number of baselines,
the sampling function is an ensemble of Dirac functions and the Fourier transform of this produces a central

88

CHAPTER 7. IMAGING WITH ALMA

Figure 7.7: uv-plane coverage for configuration C36-1 with a 2-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 19% of the total.

Figure 7.8: Cycle 3 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 1-hourobservation at 100 GHz. Configurations are arranged with C36-1 at the top and C36-8 at the bottom.

89

7.5. RESPONSE AND SNAPSHOT

Figure 7.9: Geometrical mean of the major and minor axes of the synthesized beams as a function of source
declination. These correspond to a 1-hour observation at 100 GHz. 12-m configurations are arranged with
C36-1 at the top and C36-8 at the bottom. The 7-m Array is also shown.
peak surrounded by a complex pattern of sidelobes. This “dirty beam” response is a consequence of the gaps
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 down-weightingof the visibilities on longer baselines, during the Fourier transform. Table 7.3 gives the level of sidelobes foreach configuration, for a 1-hour observation of a source at Dec=-23deg.
Configuration
NaturalBriggs (R = 0.5)
Uniform

7-m
62.6%
62.7%
62.1%

C36-1
11.7%
9.7%
9.3%

C36-2
9.0%
7.3%
12.2%

C36-3
10.1%
9.7%
13.0%

C36-4
9.2%
9.2%
12.2%

C36-5
12.5%
9.8%
12.0%

C36-6
11.0%
9.4%
10.1%

C36-7
13.3%
9.1%
8.1%

C36-8
14.3%
10.4%
11.4%

Table 7.3: Sidelobe levels for a 1-hour observation of a source at a declination of −23◦ with the different array
configurations. The levels are indicated with three different weighting schemes used for the imaging.
Figures 7.10 and 7.11 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 C36-4. As shownin Figure 7.10, 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 7.11)
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 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

90

CHAPTER 7. IMAGING WITH ALMA

Dec = -23

1000

V (meter)

500
0
500
1000

1000

500

0
U (meter)

500

1000

Figure 7.10: uv-plane sampling distributions of a model ALMA observation with 1-minute integration (left) and1-hour integration (right), using the C36-4 configuration to observe a source at a declination of −23◦ .

Figure 7.11: Images obtained from a model ALMA observation with 20-s integration (left) and 2-hour integration(right), using the C36-2 configuration to observe a source at declination of −30◦ . Black contours at 100, 200,
300, 500, 700 and 900 mJy beam−1 are overlaid.

91

7.6. SPATIAL SCALE FILTERING

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 7.12 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 ≈

37100
0.6 λ
[radians] ≈[arcseconds]
Lmin
Lmin ν

(7.5)

where Lmin is the shortest baseline in meters, λ is the observing wavelength in meters, and ν the observing
frequency in GHz. Table 7.1 lists the θM RS for the various Cycle 3 array configurations. In addition, Figure 7.13
shows the fractions of flux from a uniform disk lost according to angular scale for two array configurations,
together with the analytical expectation for θM RS . The most compact configuration, C36-1, can measure up to
50% of the total flux for angular scales larger than 2000 at 100 GHz. 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 for eachscience 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. This istaken from an H-α image, but we use it to indicate the flux expected at 100 GHz. The amplitudes of thevisibilities 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

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CHAPTER 7. IMAGING WITH ALMA

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 7.12: Expected visibilities of three model uniform disks (annular averages) at 100 GHz as a function of
uv-distance.

C36-1
C36-6

1.0

Flux (Jy)

0.8
0.6
0.4
0.2
0.00

5

10

15

Disk size (arcsec)

20

25

30

Figure 7.13: Fractions of flux expected from a uniform disk observed in two different array configurations, C36-1
and C36-6, at 100 GHz. The vertical ticks indicate the respective analytical expectation of θM RS .

7.7. MOSAICING

93

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).

∼23 Jy, whereas that detected by the configuration C36-6 (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 uniformly
λilluminated, circular aperture will have a beam width at half power (HP BW ) of 1.02 D. It will also havevery 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 theirantennas with approximately Gaussian illumination patterns that smoothly go down to -10dB to -15dB responseat the edges of the dish. The ALMA feedhorns were designed to illuminate the dish with a -12 dB edge taper inorder to provide a nearly Gaussian primary beam with low sidelobes while preserving as much of the resolution
and sensitivity as possible. This is one of the fundamental tradeoffs of radio telescope design. The resulting
λHP BW of the ALMA 12-m antennas is measured to be HP BW = 1.13 D= 5800 at 100 GHz, 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, thenoise will be increased by a factor of two compared to that at the phase center. Moreover, beyond a certain
map size, the antenna is not sensitive and it is necessary to observe several adjacent pointings, i.e., a mosaic,
to recover the sky emission.
Observing a mosaic with ALMA is needed if a map size larger than approximately the HP BW of the primarybeam is required. The default mosaic pointing pattern used by ALMA is a “fully sampled” hexagonal grid withequilateral triangles whose vertices are separated by θhex = Dλ√3 = 0.511 × HP BW which will sample theemission at the Nyquist
spatial frequency. Note that a hexagonal mosaic has spacing θhex along a row (e.g., in√3right ascension) and 2 θhex between rows (e.g., in declination). Figure 7.16 gives an example of such a mosaic.
To estimate the number of pointings (Np ) necessary to cover an area of LX × LY using this hexagonal pattern,
the following expressions can be used:

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CHAPTER 7. IMAGING WITH ALMA

Figure 7.15: Approximation of the primary beam profile of an ALMA 12-m antenna at 112 GHz with HPBW
= 5200 .
LX(int) 0.511HP
BW + 1.

2×LY √+
1.
(int) 0.511HP
BW 3

NX

=

NY

=

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 convolutionof 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 thefall 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 withlittle 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 for larger mosaics. The
OT can be used to easily setup a mosaic of adjacent pointings with a user-defined√ spacing, though it is notrecommended to exceed spacings greater than the constant noise pattern (HP BW/ 2) if a well-sampled mosaic
image is desired.

7.8

Multi-array and Multi-configuration Observations

As shown in Table 7.1, different 12-m Array configurations provide different angular resolutions, θres , dependingon the maximum baseline; and different maximum recoverable scales, θM RS , depending on their minimum
baselines. In order to achieve the requirements entered by the PI in the OT, θres and θLAS , one or more
configurations will be needed. Note that θLAS is a property of the science target, while θM RS is a property ofan array configuration. In particular, the smallest configuration for a project must deliver a θM RS that is larger

7.8. MULTI-ARRAY AND MULTI-CONFIGURATION OBSERVATIONS

95

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).
than or equal to the θLAS of the science target.
The PI should be very careful to set the angular properties {θres , θLAS } of their proposed ALMA observations
since they have a strong impact on the way they will be planned and executed. Below is a summary of how therequested ALMA arrays and array configurations are determined from these parameters. Note that in addition
to the guidelines below, there are some restrictions. For example, at most two 12-m configurations are allowed
and the two longest baseline configurations (C36-7 and C36-8) cannot be combined with smaller configurations
for Cycle 3. Additionally, for Cycle 3 the ACA is not available as a stand-alone array and its use should beconsidered only in combination with the 12-m Array. Note that the 12-m Array will be available forangular resolutions up to twice that of C36-1. The complete list of allowed combinations is given in
Table 7.4.
1. If {θres ,θLAS } is covered by the {θres ,θM RS } of a single 12-m Array configuration listed in Table 7.1, onlyone 12-m Array configuration is needed.
2. If {θres ,θLAS } is not covered by the {θres ,θM RS } of a single 12-m Array configuration, but is covered by
two distinct 12-m configurations, one compact and one extended, then those two 12-m Array configurations
will be used provided it is a valid combination described in Table 7.4.
3. If θLAS is larger than the θM RS measurable by any 12-m Array configuration at the wavelength of interest,
then 7-m Array data will also be obtained. Because the 7-m Array is designed to provide good uv-coveragein combination with relatively compact configurations of the 12-m Array (C36-1 – C36-3), two possibilities
arise:(a) The angular resolution θres is small enough to be achievable with a compact 12-m Array configuration,
overlapping with the 7-m Array in the shorter baselines. In this case, data will be obtained from the
7-m Array and a single configuration of the 12-m Array.
(b) The angular resolution θres is too high to be achievable with a compact 12-m Array configuration.
In this case, data will be obtained from the 7-m Array and two configurations of the 12-m Array,

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CHAPTER 7. IMAGING WITH ALMA

“C36-compact” and “C36-extended” (i.e., one of the more compact and one of the more extended 12-m
Array configurations). Here C36-extended provides the required angular resolution, and C36-compact
provides the sensitivity to intermediate angular scales needed to smoothly match up with the 7-m
Array data. Which specific 12-m Array configurations are used for C36-compact and C36-extended
depend on the range of {θres ,θLAS }; allowed combinations are shown in Table 7.4.
4. Finally, if θLAS is larger than the θM RS of the 7-m Array, the Total Power Array will also be included.
It is important that you provide an accurate estimate of θLAS for your target, as the quality of the
final image will depend very much on the observation with the proper set of array configurations.
θres (arcsec)
0.075
0.075
0.1
0.1
0.3
0.3
0.3
0.3
0.5
0.5
0.5
0.5
0.7
0.7
0.7
0.7
1.2
1.2
1.2
1.8
1.8
1.8
3.4
3.4
3.4

θLAS (arcsec)
< 1.1
> 1.1
< 1.5
> 1.5
< 4.8
4.8-25.2
25.2-42.8> 42.8< 7.8
7.8-25.2
25.2-42.8> 42.8< 9.6
9.6-25.3
25.3-42.8> 42.8< 25.225.2-42.8> 42.8< 25.225.2-42.8> 42.8< 25.325.3-42.8> 42.8Array combination
C36-8
C36-7
C36-6
C36-6 + C36-3
C36-6 + C36-3 + 7-m
C36-6 + C36-3 + 7-m + TP
C36-5
C36-5 + C36-2
C36-5 + C36-2 + 7-m
C36-5 + C36-2 + 7-m + TP
C36-4
C36-4 + C36-1
C36-4 + C36-1 + 7-m
C36-4 + C36-1 + 7-m + TP
C36-3
C36-3 + 7-m
C36-3 + 7-m + TP
C36-2
C36-2 + 7-m
C36-2 + 7-m + TP
C36-1
C36-1 + 7-m
C36-1 + 7-m + TP

Time ratios
1
1
1
1 : 0.5
1 : 0.5 : 2
1 : 0.5 : 2 : 4
1
1 : 0.5
1 : 0.5 : 2
1 : 0.5 : 2 : 4
1
1 : 0.5
1 : 0.5 : 2
1 : 0.5 : 2 : 4
1
1: 2
1: 2: 41
1: 2
1: 2: 41
1: 2
1: 2: 4

Total Time
1.0 × ∆extended
1.0 × ∆extended
1.0 × ∆extended
1.5 × ∆extended
3.5 × ∆extended
5.5 × ∆extended
1.0 × ∆extended
1.5 × ∆extended
3.5 × ∆extended
5.5 × ∆extended
1.0 × ∆extended
1.5 × ∆extended
3.5 × ∆extended
5.5 × ∆extended
1.0 × ∆extended
3.0 × ∆extended
5.0 × ∆extended
1.0 × ∆extended
3.0 × ∆extended
5.0 × ∆extended
1.0 × ∆extended
3.0 × ∆extended
5.0 × ∆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 Array and 7-mArray observations are run in parallel; b) for intermediate values of θres , please see text. The largest angularresolution allowed for a project will be twice the resolution offered by C36-1.
As a user, you will not be able to directly choose the number of 12-m Array configurations to use for yourproject, it will be decided automatically by the OT, based on the {θres , θLAS } that you have indicated, subject
to the guidelines above and the range of valid options described in Table 7.4). The ALMA staff will thenschedule the appropriate array configuration(s) to achieve the angular properties requested by the project. As
discussed above, the angular resolution depends on the weighting scheme used during imaging. For similarreasons, the combination of data from different configurations can alter the angular resolution and provide aslightly worse one than the most extended configuration taken alone. The quality of the data will be assessed
per observation on an array. For the observation with the most extended 12-m configuration, the goal will beto reach the angular resolution θres you have specified; for the most compact configuration, the goal will beto reach the θLAS you have specified; for the configurations in-between, if any, the goal will be to reach the7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

97

range {θM RS ,θres } of that configuration. A detailed desciption of the quality assurance process can be foundin Chapter 11. For the representative Cycle 3 12-m configurations described in Tables 7.1 and 7.2: C36-1,
C36-2, and C36-3 are considered compact, C36-4, C36-5 and C36-6 are considered extended (C36-7 and C36-8
are also extended, but will be offered alone, not in combination with any other configuration). The extended
configurations cannot be combined directly with the 7-m Array configurations because doing so would lead tolarge “holes” in the uv-coverage. For cases 3 or 4, the ALMA user will be advised by the OT to add the ACA:
it is then the choice of the user to accept this or not; if a user chooses to go against the recommendation by the
OT, he/she will need to adequately justify this decision in the proposal.
In addition to the different array combinations available during Cycle 3, Table 7.4 also summarizes the relative
integration times that will be used by each array: because of their smaller collecting areas, the TP Array and
7-m Array require more integration time than the 12-m Array in order to match sensitivity at similar spatial
scales. A time ratio of 2 between 7-m and 12-m Array will be used in Cycle 3. For TP Array, a ratio of 4
will be used, but the overall increase of time for the project will be less as the TP and 7-m Arrays will be run
in parallel. In the end, a typical time ratio for a full combination [TP : 7-m : C36-compact : C36-extended]
will be [4 : 2 : 0.5 : 1]. It is very important to note that θLAS can have a large impact on a proposal, since
it can multiply by a factor of 5.0 the total time needed for the project with respect to the 12-m Array due
to the longer integration times the TP Array and 7-m Array require. Thus a strong scientific justification for
θLAS should be provided when multiple configurations are required. 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 3, it is recommended that at least one hour of 7-m Array hour angle coverage is necessary to provide
sufficient uv-coverage for good image combination with the 12-m Array, and snapshot observations are strongly
discouraged. A comprehensive plot about the array combination is shown in the Figure 15 of the ALMA Primer
for Cycle 3 (Moriarty-Schieven et al., 2015).
Table 7.4 indicates the possible array combinations, assuming the angular resolution of each representative
ALMA configuration. However, it takes time to move antennas, which means that the transition from one
configuration to the next is progressive, thus providing intermediate angular resolutions. For the purpose ofdetermining the total time required by a project, the OT will assume only the set of 8 array configurations
described in Tables 7.1 and 7.2, using for the most extended configuration the one that provides an angularresolution just below the θres specified by the PI, and if necessary, for the most compact configuration the
one that provides a θM RS just above the θLAS specified by the PI (within the allowed combinations). Using
this information, the project will be broken down into one or more observations, each covering a different,
but complementary, range of angular scales. Later during scheduling, the range of angular scales available
to the current 12-m configuration will be compared to those required by the project and if they match that
portion will become queued for observation (assuming that other important parameters, such as the weather, theproject ranking, the executive balance, are appropriate). Note that, as mentioned before, the values of θM RS
and θres for a particular antenna array are intrinsically linked to the weighting scheme used at the imaging
stage; in particular, Figure 7.5 shows that the final angular resolution of an image can be tweaked continuously
thanks to the Briggs weighting scheme: this gives some flexibility at the scheduling stage, as it allows runningobservations whose angular scale requirements, though slightly different, are close to those covered by theantenna array available at the time.

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. Then, when all the observations have beenobtained, we will combine them to make the final image, and deliver it to you, again, if it passes the quality
assurance.
The combination procedure will include two steps: first, the imaging of all interferometric data together, thenthe actual combination of the single-dish map with the interferometric map. The imaging of all interferometricdata together can now be done directly with clean in CASA, as of the current release (4.3.0), assuming theentire calibration was also done with that version (or more recent). In Cycle 3, the combination

98

CHAPTER 7. IMAGING WITH ALMAof the single-dish and interferometric maps will be done with the feathering technique. The term “feathering”
is used in radio imaging to describe how to combine or “feather” two images together by forming a weighted
sum of their Fourier transforms in the (gridded) uv-plane. Intermediate size scales are down-weighted to giveinterferometer resolution while preserving single-dish total flux density.

Figure 7.17: Expected uv-coverğage for C36-2 (1 hour) and 7-m observations (2 hours)

10

7-m
C36-2
Full

8

weight

6

4

2

0
0

50

100

150
UV radius (meter)

200

250

300

Figure 7.18: Radial density of uv-coverage with uv-distance using C36-2 (1 hour) and 7-m observations (2 hours)
The feathering technique does the following:
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)), (alternatively, one canspecify some smaller portion of the single dish aperture, which corresponds to a wider beam).
3. The Fourier transform of the interferometer image is multiplied by (1 – F T SDB(u, v)). This basicallydown weights the shorter spacing data from the interferometer image.

7.9. MULTI-ARRAY AND MULTI-CONFIGURATION IMAGING

99

4. The Fourier transform of the single-dish image is scaled by the volume ratio of the interferometer restoring
beam to the single dish beam.
5. The results from 3 and 4 are added and Fourier transformed back to the image plane.

Figure 7.19: Images obtained using C36-3 (top left; 1 hour), C36-3 + C36-6 (top right; 1 + 2 hours) and C36-3+ C36-6 + 7-m (bottom left; 1 + 2 + 4 hours) array combinations, and the image model itself (bottom right).
A 1-hour observation with the C36-2 configuration and 2 hours with the 7-m Array is shown in Figure 7.17
(uv-coverage) and Figure 7.18 (uv-plane sampling distribution). The Cycle 3 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 C36-compact
configuration (C36-3), a compact and extended configuration (C36-3 + C36-6), 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 C36-6 configuration at 100

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CHAPTER 7. IMAGING WITH ALMA

GHz provides an angular resolution of 0.2700 . Combined with the C36-3 configuration, the angular resolution islowered to 0.3100 . Finally, the angular resolution with the full combination (C36-3 + C36-6 + 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. Changing the weighting scheme (e.g. to uniform) can restore thehighest angular resolution at the expense of sensitivity.
References[1] Briggs, D. S. 1995, High Fidelity Deconvolution of Moderately Resolved Sources Ph. D. thesis, New Mexico
Institute of Mining and Technology[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] Moriarty-Schieven, G. ed., 2013, Observing with ALMA: A Primer for Early Science, ALMA Doc. 2.1, ver.
1[5] Rohlfs, K, Wilson, T. L. 2004. Tools of Radio Astronomy, Fourth Edition, ISBN 3-540-40387-6 Springer

Chapter 8

Observing Modes
The ALMA Observing modes are the set of capabilities that ALMA offers each cycle to its user community. For
example, single field interferometry, single dish observations, polarization, etc. are observing modes. In order
to execute an approved ALMA observing project, the particular observing mode needs to be implemented in
the ALMA online software package and verified using the required hardware1 . Here, we describe the ALMA
observing modes along with the project structure and a brief description of the software.

8.1

Observing Project Structure

An observing proposal created using the ALMA Observing Tool (hereafter OT) and 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 for the successful completion of a project. A summary viewof the constituents of an Observing Project is shown in Figure 8.1.
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 OT which is the tool usedduring the Phase 12 stage of the project life cycle. The SB may be edited using the OT in Phase 2 after
proposal acceptance and before/during project execution3 . The SB is the fundamental unit of the observing
project and allows for flexibility given the properties of the ALMA site and the continuously varying status of
the observatory as a whole (including the weather). It also encapsulates the scientific objectives of the proposal
into a single entity.
An SB contains a large amount of information about what should be observed, such as the positions andvelocities of 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 tothe observing mode e.g., single-dish, single field interferometry, etc. The SB has relatively little influence over
the order in which the various sources are observed and does not describe all of the calibrations that may be
performed (e.g. measurements of the system temperatures).
Each SB has an execution time of typically one hour and all the set-ups, the calibrations, and target observations
are executed within this period. The end of an SB execution may be specified in terms of a maximum amount oftime or when certain well-defined science goals have been reached as specified in the science parameters sectionof the SB. An SB is atomic in the sense that it cannot be stopped and re-started from the last scan. Therefore, an
1 The implementation and verification of ALMA observing modes was part of the Commissioning and Science verification (CSV)
phase as well as also part of the Extension and Optimization of Capabilities (EOC)
2 For a description of Phase 1 and Phase 2 see the Cycle 3 Proposer’s Guide
3 SBs can also be created in and ad-hoc manner for commissioning purposes

101

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CHAPTER 8. OBSERVING MODES

Figure 8.1: Block diagram of an Observing Project from the point of view of the observation preparation as
done in the OT (top) and the internal hierarchical structure of the SB in the actual executions (bottom). All
projects have the same ObsUnitSet (OUS) levels, the Science Goal OUS level, the Group OUS level and theMember OUS level. Scheduling blocks are attached to the Member OUS.

8.2. PROGRAM EXECUTION

103

SB runs to completion, fails, or is terminated by the Astronomer on Duty (or AoD). Given the limited durationof 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 been chosen based on statistical measurements ofthe stability of the system. A system failure will prevent the online software from flushing the data into thearchive losing the observed project data. Thus, executing SBs for more than 2 hours becomes unsafe from theoperational perspective. To optimize this scheme, we implemented what we call a session, which is the continous
execution of a single SB until a certain goal has been reach (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, theObserving Unit Set (hereafter OUS) is the smallest unit for data processing.
An OUS comprises all SBs that have to be processed together to produce calibrated science data products (e.g.
images or data cubes). In most cases, there will be exactly one SB in each Member OUS, but the latter may holdmultiple executions of this SB. The actual execution of an SB is called Execution Block or EB. For polarization
observations, all the EBs that belong to the same session should be grouped together for data processing, which
for this cycle will be done manually by the ALMA staff (i.e. no pipeline processing).
If the calibrated science observations of a Member OUS have to be combined with science observations of anotherMember OUS, then these are grouped together into one Group OUS. A typical case of several Member OUSes
that belong to the same Group OUS are observations of the 12-m Array, the 7-m Array and the Total Power(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. In addition, processing happens also at the Group OUS level, in case the Group OUS contains
several Member OUSes which have already been processed. The only other event that triggers data reductionis the end of an observing season, when all the Member OUSes and potentially Group OUSes are reduced,
regardless of their degree of completion.
The SB/Member OUS/Group OUS are the smallest structures that hold science observations that need tobe observed/processed/combined together. This data hierarchy therefore maximizes observing flexibility andensures that data get 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 AoD), it is read into
the online CONTROL software, particularly by the Science Software Requirements subsystem (hereafter SSR).
An overview of the SSR, including communication with other software subsystems, is shown in Figure 8.2. The
SSR subsystem commands the lower level CONTROL software to create an EB object that is attached to the
SB. As many SBs will be executed several times, a number of EBs may exist for a given SB. Each EB contains
a record of the parameters and conditions under which SB was executed along with references to the acquired
data. The archived data identified by each EB uses the Alma Science Data Model (ASDM)4 . The internalhierarchical structure of the EB is also shown in Figure 8.1. The SSR subsystem constructs a sequential seriesof scans for each of the required calibrations and commands 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. Although commands are issued at the scan/subscan level, the correlator output corresponds toa particular integration. In general, each calibration observation consists of a scan containing several subscans(e.g. the 5 points of pointing calibration constitues a scan with 5 subscans). Similarly, the integration time on asingle science source between phase calibrations can consist of one scan comprised of a number of subscans. To
optimize the execution, scans may be organized in scan sequences which are passed to CONTROL for execution.
A typical example of a scan sequence is as follows:
4 The ASDM uses the relational databases paradigm to define the tables containing the data and metadata along with therelatioships between them

104

CHAPTER 8. OBSERVING MODES[CALIBRATE_SIDEBAND_RATIO, CALIBRATE_ATMOSPHERE, CALIBRATE_BANDPASS]
where each of the items in the list corresponds to ALMA calibration intents5 . Scans and scan sequences can beof arbitrary length, depending on the characteristics of a given observation, but subscans are recommended to
be 30 seconds or less. Integrations tend to be on the order of one to 10 seconds where the final value has to be
an integer multiple of the correlator dump time. These values can be specified during Phase 2 SB constructionin 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
SSR and the Control subsystem are responsible for the creation of all the metadata needed downstream for dataprocessing.

Figure 8.2: Overview of the SSR in term of the ALMA software components that the subsystem talks to.

8.3

The Observing Process

The execution of an ALMA observation is done by means of an observing script. The script will parse the
SB and, for a given project, the set of targets specified in the SB are created. These targets can correspondto either calibration or science executions. Targets are organized in observing groups6 where the first group(group 1) is always the initial calibration group, with subsequent groups detailing the science observations7 .
The associated calibrations are attached to a particular calibration right after the SB is parsed and the groups
created (see below). All Science targets and relevant calibrators within a group are observed before the nextgroup is started. A list of observing scripts is shown in Table 8.1.
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 wellas any deferred calibrators from group 1 are observed.
Most observing modes, including single field interferometry, multi-target executions, pointed mosaics, and polarization use the same ALMA observing script, called the standard interferometry script. The set of necessary
calibration measurements (e.g. amplitude, bandpass, etc) usually specified in group 1 are performed at the beginning of the observation sequence if appropriate astronomical 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.
Calibrations such as pointing, atmospheric, and sideband-ratio are associated to the main calibrations (bandpass,
amplitude, polarization, and phase) on an "as-needed" basis which is determined by the SSR at run-time8 , but
5 This intents are identifiers that the ALMA pipeline uses to process the data
6 These groups are different from the Group OUS described in Section 8.1
7 Additional calibrations can be added into subsequent groups to be interleaved according their cycle times. One example is thepolarization calibration
8 On some cases the atmospheric calibration might get associated to the science target

105

8.3. THE OBSERVING PROCESS

Script Name
StandardInterferometry.pyStandardSingleDish.py
AmpliCalSurvey.py
TowerHolography.py

Purpose
Performs a regular interferometric ALMA observation
Performs a regular ALMA single
dish observation (Total Power)
This script executes the observation of calibration sources (routine monitoring of quasars)
Performs a surface calibration
observation using the holographytransmiter

Table 8.1: The list of the most common observing scripts in the SSR are listed here along with brief description.
with little control from the user. Usually, pointing is verified before the amplitude and bandpass calibrators
are observed, and again before the main observations of the science target and phase calibrator cycle. Within agroup, the science targets are each observed in sequence until the observation of the primary phase calibrator(the calibrator with shortest cycle time in the group) is required. A typical cycle time for the phase calibrator
may be 7-10 minutes. This process is repeated until the observing requirements are met, or the SB reaches its
time limit. Any additional (secondary) phase calibrators are observed as specified in the scheduling block. Fora 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 calibrations for a given SB is done using astronomical sources selected at runtime. To
correctly select the appropriate calibration sources, a selection algorithm has been implemented in the SSR
using the following steps:• A list of sources is retrieved from the ALMA catalog using the query center and the search radius definedin the SB field-source parameters as inputs.
• For each source in the list we check whether there are flux measurements at the SB representative frequency.
If no flux measurement is present at the desire frequency, we extrapolate the flux using a spectral index
of -0.7 to the SB representative frequency from closest masurement available in frequency9 .
• The flux is weighted based on proximity to the representative frequency, target, and time since the lastmeasurement present in the source catalog.
• A signal-to-noise criteria is applied to the returned list of sources and ranked based on source strength,
separation respect to the query center and flux error.
• The final list is sorted based on ranking and returned.
Using these rules we implemented the criteria for all the ALMA calibrations adding specific requirements basedon the nature of the target, such as:
9 Higher frequency bands such as Band 9 or 10, may not have current measurements from the ALMA source monitoring observations due to the weather requirements, which increase chance that the flux used by the query is extrapolated

106

CHAPTER 8. OBSERVING MODES• Bandpass calibrator. A signal to noise of 50 given a 15 minutes integration is used in the flux estimation.
The smallest spectral window defined in the SB (bandwidth) is used for this calculation. The default
search radius is defined to the be 45◦ from the query center, but the user can overwrite this value as
needed. A minimum elevation is calculated to avoid antenna shadowing.
• Phase calibrator. A signal to noise of 15 given a 2 minutes integration is used in the flux estimation.
The widest spectral window bandwidth (usually 2 GHz) is used for this calculation. The default radiusused in the search is 20◦ from the query center, which can be modified in the SB as needed. As withthe bandpass a list of sources is assembled that passed the signal to noise criteria, but the closest one tothe query center is returned. Thus, we priviledge proximity to the science target rather than flux for thephase calibration.
• Flux calibrator. Solar system objects are queried first, then grid sources10 . The first visible grid source isused. The following list corresponds to both solar system objects and grid sources used for flux calibration,– Solar system objects: Mars, Venus, Jupiter, Uranus, Neptune, Titan, Ceres, Ganymede, Callisto,
Pallas.
– Grid sources J0237+288, J0238+166, 3c84, J0334-401, J0423-013 ,J0510+180, J0519-454, J0522364, J0538-440, J0635-7516, J0750+125, J0854+201, J1037-295, J1058+015, J1107-448, J1146+399,
3c273, 3c279, J1337-129, J1427-421, J1517-243, J1550+054, J1613-586, 3c345, 3c454.3, J1733-130,
J1751+096, J1924-292, J2025+337, J2056-472, J2148+069, J2232+117, J2258-279, J2357-5311

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 amplitude 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 theseamplitude calibration 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 from the catalog of routinely monitored sources by ALMA.
As the interferometer is a device for measuring the spatial coherence function, the phase calibration is used tocalibrate the phase variation at the individual antenna elements during the course of an observation. Since thephase is expected to change much more rapidly in time than the amplitude, these sources will be observed more
frequently than the other calibrators. Because the phase varies on small scales on the sky, the calibrator must bequite close to the science 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 atmosphere can fluctuate rapidly (specially at higher frequencies), radiometric observations of atmosphericwater lines are done to correct for these additional phase variations. These corrections can be applied online
and offline (See Chapter 5).
10 Grid sources correspond to a set of sources (usually quasars) that ALMA monitors periodicaly for flux calibration purposes8.5. POINTED MOSAIC OBSERVATIONS

8.5

107

Pointed Mosaic Observations

Pointed mosaic observations are also offered for this Cycle. This mode enables a single Science Goal to covera field of view larger than the primary beam by making observations of multiple single fields that overlap by
an amount 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
execution11 . In pointed mosaic observations, each of the fields will be assigned different field identifiers in thedata, but the same source identifier. 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 mayneed to be defined. The mosaic is arranged as a single scan composed of a number of subscans corresponding
to the individual positions in the mosaic (see Section 8.2). Both the science target specific last mosaic pointing
position and index within the science target list are handled by the SSR to ensure that the next scan begins
on the proper science target and proper offset position. Regular mosaic observations (including multiple small
mosaics) should be specified using a Rectangular Field in the OT; for irregular mosaics custom-mosaic under
Multiple Pointings should be selected.

8.6

Single Dish Observations

The purpose of adding data from single-dish observations using auto-correlations 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 (TP), although in practice they are taken in auto-correlation mode rather
than using a total power (square law) detector. Four 12-m antennas connected to the ACA Correlator areavailable for this purpose.
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
Mapping (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 theauto-correlation data will be written to the data set or ASDM12 and to minimize data rate and size, whereas
calibrations use cross-correlation information for analysis.
The OTF map is observed as a series of raster rows, scanning in the coordinate system specified in the SB. In
Cycle 3, 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 turns to minimize scanning effects. The reference
positions, assumed to be positions which are free of emission, are specified as offsets relative to the map center.
By default, the OTF map will cover an area one half of the full beam larger than the interferometric observationon all sides. This will ensure that undersampling at the map edges does not affect the data combination processwith the interferometric data. A raster row in these observations is defined as a subscan, and the length of ascan in time (consisting of some number of subscans) is defined in the SB. The reference position is observed as
specified by its cycle time during the science target scans. The pointing is calibrated on a bright calibrator near
the science target with a frequency indicated in the SB, and atmospheric calibrations are taken at the reference
position to measure the system temperature.
The calibrated TP map of the science target will be in units of Kelvin, on the antenna temperature (T∗a )scale. Since all TP observations are expected to be combined with 12-m and 7-m Array data which comein calibrated units of Jy/beam, the TP data must also be converted into these units. This conversion from
Kelvin to Jy/beam requires a Kelvin-to-Jansky conversion factor, which will delivered to the project principal
investigator (See Chapter 10). These are measured separately for each project by obtaining a continuum mapof a bright quasar or a planet with known flux. These amplitude calibration maps are reduced similarly to the
11 In future cycles this restriction may be lifted by using sessions, as the mosaic field index will be remembered from one SB
execution to the next
12 The ASDM it is also loosely used to name the actual raw data that is archived after an observation is executed

108

CHAPTER 8. OBSERVING MODES

science observations, but keeping the considerations required to process continuum data (e.g. no continuum
subtraction). The emission is compared to a known model or observed flux (taken from the most recent calibrator
survey measurements of grid sources in the case of quasars) to obtain the conversion factor, which will then be
applied to the science observations.

8.7

Polarization

The ALMA antennas have receivers with linearly polarized feeds followed by a waveguide with a polarization
splitter13 . Thus, the incoming radiation is separated into two orthogonal components (X and Y) which are
downconverted and digitized independently. The digital signals are cross-correlated for each baseline at thecorrelator and the output are four cross-correlations (XX, YY, XY, and YX). These four cross-correlations, asa 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),
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 in thissimple 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 frequency and band(cartridge design and external optics). Additionally, this quantity is measured in the frame of the antenna
which is an elevation and azimuth frame (Alt/Az) and thus, it rotates with respect to the frame of thesky. This rotation introduce an angular dependance into the visibilities as a function of the paralactic
angle. By design, the instrumental polarization is small (a few percent), but not neglible.
2. The signal path followed by each of the individual X and Y polarizations is sligthly different, which
instroduces a small delay in the signal that needs to be accounted for.
3. An XY-phase offset is introduced by using a reference antenna. The XY-phase offset is a spectral phaseonly bandpass relating the X and Y systems of the reference antenna.
13 In most of the antennas this device is an Ortho-Mode-Transducer (OMT) with the exception of Band 7 that has a polarizedgrid8.7. POLARIZATION

109

Figure 8.3: 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 unit 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.
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 3 (see below for a detailed explanation.)
By taking into consideration the instrumental polarization and the paralactic angle dependence, we can re-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 paralactic angle. Figure 8.3 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 with somevariations over frequency. Without any D − term calibration, an unpolarized source may appear to be polarizedat 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. Alternatively, it is possible to separate the source polarization,
the D − terms, and the cross hands phase spectrum and delay by observing an unresolved polarized source
over a wide range of parallactic angles, where many quasars suffice this condition. The polarization calibrator
should be observed at least to cover a wide range (> 45 degrees) of parallactic angle variation. The rotation of
the parallactic angle mostly occurs right before and after the transit, but low declination sources do not rotate
much (see Figure 8.4). The D − terms may have a slight elevation dependence, and therefore it is favorable forthe 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. The users
can check the calibrator candidates from the ALMA polarization calibrator database.
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, which will scale down with the number of antennas in final image. The user will be encouraged to see

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CHAPTER 8. OBSERVING MODES

100
80

parallactic angle [deg]

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

-60
-80
-100
-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

source hour angle [hr]Figure 8.4: Parallactic angle plot as a function of hour angle for the declination of 30, 10, -10, -30, and -50
degrees.
the polarized flux and polarization position angle of the calibrator in the data reduction process and check theconsistency comparing with the results obtained by the ALMA calibrator monitoring survey. 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 thecurrent 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, and thealignment 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 3, the off-axis instrumental polarization calibration will not be employed. Therefore, the acceptable
angular size for the observing source is limited where the off-axis instrumental polarization level does not
significantly become large. For this reason, the largest angular size of the source must be less than FWHM/3of the primary beam. Polarization imaging with accuracy better than 0.3% can be achievable in this area. The
users must justify that the source polarization level of science target is well higher than these accuracies.
For this cycle, polarization observations are limited to TDM correlation mode (or 64 channels per polarization
product with 2 GHz bandwidth), but at arbitrary frequencies within the offered bands (3, 6, and 7). No higher
spectral resolution, mosaic, ACA, and TP Array observations are offered. Further, a minimum execution timeof 3 hours will be imposed to ensure that sufficient coverage in parallactic angle for the calibration.

8.7.1

Sessions

Though not directly related to polarization iteself, sessions is the observing scheme designed to observed 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 calibration science target loop will
be broken (preserving phase calibration) when an additional calibration is-needed (e.g. polarization)14 . The
current mode for sessions in ALMA is the observation of polarization projects. Because for an Alt/Az antenna
14 The cycle time parameters are user controlled and can be explicitly specified in the OT target parameters section

8.8. MULTIPLE REGION MODES111

the frame of the sky rotates, the calibration of the of instrumental polarization requires sampling a strong compact source as a function of paralactic angle approximately every 30 minutes. The session will remember thelast time the polarization calibrator was observed and interweave the calibration when needed. We can achieve
the paralactic angle coverage by running the polarization SB 3 times, which will give between 3 to 4 hours ofobservation. This constitutes a perfect use for the session scheme. Other cases were the session scheme might
be useful are large mosaics, surveys (multi-target), and large single dish raster maps, but those cases are notoffered in session mode for Cycle 3. 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 toaccess a persistent component which we use to store and retrieve this information.

8.8

Multiple Region Modes

In the frequency division mode (FDM) of the correlator, the final spectrum is synthesized using individual filters
62.5 MHz wide. In multiple region modes, when the total bandwidth is between 125 MHz and 1 GHz, it ispossible to move these individual filter positions to create spectral windows covering a number of disjointed
spectral regions. This is called the Multiple Region Modes. The constraints are:
• The spectral window width must be a multiple of 62.5 MHz;• The aggregate width of these spectral windows must be equal to that of the original bandwidth selected;• The spectral windows must all fit within the 2 GHz baseband used;• The other parameters (resolution, polarization and sensitivity options) must the same for all spectral
windows.
This mode is useful when a number of line features which require high spectral resolution are spread across the
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 3, a maximum of 4 spectral windows per baseband will be offered.

8.9

Observations of Ephemeris Objects

Observation of solar system objects (with the exception of the Sun) is supported in Cycle 3. Several well known
solar system objects including planets, satellites and asteroids can be selected from a pulldown menu in the OT.
For other non-siderial 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 the date (time), right ascension, declination,
range and range rater. An enhancement for Cycle 3 are high precision ephemeris which are now supported (SeeFigure 8.5). The ephemeris file should contain at least one row for every hour and, except for fast objects, one
row every 20 minutes is sufficient. The online system will linearly interpolate between rows in an ephemeris
when determining the antenna pointing & signal propagation delay. A general example of an ephemeris file is:*******************************************************************************
Date__(UT)__HR:MN
R.A.___(ICRF/J2000.0)___DECdeltadeldot*******************************************************************************$$SOE
2014-Dec-01 00:00 Am 18 51 01.8305 -20 41 18.087 33.5888476523329 17.7176571
2014-Dec-01 00:20 Am 18 51 01.9382 -20 41 18.057 33.5889897735456 17.7169995
2014-Dec-01 00:40 m 18 51 02.0461 -20 41 18.027 33.5891318772715 17.7132925
2014-Dec-01 01:00 m 18 51 02.1542 -20 41 17.997 33.5892739389694 17.7065199
2014-Dec-01 01:20 m 18 51 02.2624 -20 41 17.967 33.5894159340629 17.6966891

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CHAPTER 8. OBSERVING MODES

Figure 8.5: Example of a high precision ephemeris test experiment to track the position of Pluto. Charon is
also seen at the top left.
More information on the format and precision needed is available in the ALMA Observing Tool documentation.
Finally, solar observations are not allowed for Cycle 3 but will be available at a later date.

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 opacity and the sky temperature are calculated using 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 assumes that the source is at the zenith and therefore the OT has to account for the greater
atmospheric emission at lower elevations. The emission from the atmosphere is often approximated asTsky = Tatm (1 − e−τ0 sec z )(9.1)

where Tatm is the mean physical temperature of the atmosphere. This can be calculated using Equation 9.1 and
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.

113

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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.
from there the sky temperature as a function of zenith angle:
Tsky,z = Tsky,z=0(1 − e−τ0 sec z )(1 − e−τ0 )(9.2)

Tsky 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 ×(9.3)
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 50 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 many of the ALMA bands, the calculator currently only uses the specifications for the receiver temperatures(required over 80% of the receiver bandwidth) and not the actual measured values. However, for five of the
Early Science Bands (3, 6, 7, 8 and 9), typical values measured in the laboratory are used as these are usuallysignificantly better 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 that single sideband noise temperatures are reported for Bands 1-8 and double sideband
temperatures for Bands 9 and 10.

9.1. CALCULATING THE SYSTEM TEMPERATURE

115

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.

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 9.3.

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
to Equation 9.3 and thus its total contribution is frequency dependent and can vary between the different
sidebands.

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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).

9.1.5

DSB receivers

Every heterodyne radio receiver detects radiation from two sidebands simultaneously, this being due to the waythat the astronomical signals are down-converted to an intermediate frequency before further processing. Thismeans that, if nothing were done to prevent 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 software that takes the input spectral window frequencies and calculates the tuning
solutions from these will always try and place these in the upper sideband if possible. Therefore, to take asimple case, a single spectral window centred at 637 GHz will find its image equivalent in the middle of thezero transmission feature at ∼621 GHz. This situation should be avoided if at all possible, including defining
dummy spectral windows such that the line of interest is swapped (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:
Tsys,dsb =1
ηeff e−τ0 sec z



2 × Trx + ηeff (Tsky,s + Tsky,i ) + (1 − ηeff ) × (Tamb,s + Tamb,i )where• Trx – receiver temperature• Tsky,s – sky temperature at the requested frequency in the signal sideband



(9.4)

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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,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 receivers that aren’t DSB, the equation is the following:
Tsys,ndsb =1
ηeff e−τ0 sec z

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



(9.5)

where the terms are all the same as in Equation 9.4.

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 the contribution of this to the system temperature. In this case, the same equation isused for all receiver types and the DSB noise contribution is simply double the single sideband case. This is118

CHAPTER 9. ALMA SENSITIVITY CALCULATOR

controlled via the sideband gain ratio, g:Tsys =



1+g
T
+
η
T
+
(1
−
η
)
×
T
.
rx
eff
sky,s
eff
amb,s
ηeff e−τ0 sec z(9.6)

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 =ηq ηc Aeffp

2 k Tsys.
N (N − 1) np ∆ν tint

(9.7)

The various symbols are• Aeff – effective area. This is equal to the geometrical area of the antenna multiplied by the aperture
efficiency (ηap ). The latter is given by the Ruze formula i.e. ηap = R0 exp (−16 π 2 σ 2 /λ2 ) where σ is therms surface accuracy of the antenna – the specification of 25 µm and 20 µm for the 12-m and 7-m antennas
respectively is currently used3 . Ro is equal to 0.72. See Table 9.3 for values of antenna efficiencies andeffective areas in various ALMA bands• 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 efficiency will 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 36 for the 12-m and 10 for the 7-m Array• np – number of polarizations. np = 1 for single polarization and np = 2 for dual and full polarization
observations• ∆ν – resolution element width. As already mentioned, this should be equal to 7.5 GHz for continuum
observations. This is due to the maximum usable bandwidth of a spectral window being limited to1.875 GHz by the anti-aliasing filter through which the baseband signal passes. np ∆ν is often referred toas the effective bandwidth• tint – total on-source integration time.
The associated surface brightness sensitivity (K) is related to the point-source sensitivity (Jy) byσT =σS λ 22k Ω(9.8)

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.

119

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 the efficiency multiplied by the physical area of the dish i.e. 113.1 m2 and 38.5 m2 for the
12 and 7-m antennas respectively.
where Ω is the beam solid angle. This is related to the user-entered spatial resolution, θ, by
Ω=

πθ2
.
4 ln 2(9.9)

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 same as Equation 9.7, apart from there only being a factor of
the total number of total power antennas.

(9.10)√

N in the denominator, where N is

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.
• 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.

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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.

• Number of antennas – the ASC currently defaults to the values for Early Science, namely 36 from the
12-m Array, 10 from the 7-m Array and two 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

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.

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 time-of-flight phase 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). Detailsof the flow of the astronomical data from the antennas through the correlator to the archive are given in
Chapter 14. These data are stored in the ALMA archive in the form of the ALMA Science Data Model(ASDM). For ASDM details see Chapter 12.
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 is included in correlator
processing in order to remove the a priori signal delays that are a function of baseline length, observing frequency,
and source position (See Chapter 5). An important part of the correlator delay model is the estimated atmospheric path delay to each antenna from the radio source with an assumed position, σ, called the phase centerof the observations. With this correlator model delay/phase rotation removed, the visibility function can thenbe averaged coherently over many seconds. Other parts of the a priori model can be included in the correlator
processing or applied directly in the antenna signal paths.

10.1.2The Visibility Function Dependence

The fundamental observational piece is the scan. It is an observation with one field name, associated with aphase center, and one band, b, and many other parameters to specify the observation details. The scan has manytime samples. Since virtually all ALMA observations use phase referencing as the major calibration method,scans associated with calibrator sources are usually interleaved with scans associated with the science target.
The visibility function associated with a scan/band has the following dependencies: time stamps, tk , antennapair indices (i, j), separation of the observing band into four SPW’s s with further channelization, c. Thisfrequency specification is called a tuning (See Chapter 6). Finally, each sample contains up to four polarization
correlations, pq . The observed complex visibility function, with all its dependencies, is written as
V o (σ, νb )i,j [tk , νs,c , pq ](10.1)

The 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.

121

122

CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESThe autocorrection data, where i = j is also contained from the correlation of the data. The calibration anduse of this data are given in Section 8.6 and Chapter 13.

10.2

Main Interferometric Calibration Strategies

10.2.1

Antenna-based Calibrations

Nearly all of the modifications of the measured visibility function are antenna-based since virtually all effects
occur in the signal path are associated with one particular antenna, from the troposphere above the antenna
through all of the electronic processing along any antenna path, up to the correlator. In general the calibration
equation is:to(tk , νc )(tk , νc ) = Gi (tk , νc ) ∗ G̃j (tk , νc ) V(i,j)
V(i,j)
t+noise + g(i,j) (tk , νc ) V(i,j)(tk , νc )(10.2)

where Gi (tk , νc ) is the antenna-based complex gain calibration as a function of time and frequency. This is thenormal calibration equation. The second line contains the effect of noise and a pure baseline-calibration, andthese will be ignored for the most part.
The complex antenna gain is also separated into the antenna-based amplitude and phase gains,
Gi (tk , ν) = ai (tk , νc ) exp[iψ(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.

10.2.2

Calibration Flow through ALMA system

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,1 , occur roughly in the propagation order of the radio signal is:
I = Ionosphere: Opposite rotation of linear polarization caused by ionosphere. Unimportant at 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 position, caused byfocus and pointing offset.
p = Parallactic angle: The rotation of the antenna feed orientation with respect to the sky (alt-azimuth mounts.
X = Linear pol angle: The orientation of the feed with respect to the antenna structure.
d = Polarization leakage: The non-orthogonality of the two orthogonal polarized feeds.
T = System Temperature: Amplitude calibration factor from system sensitivity.
M = Model used in the correlator to remove the major delay temporal and angular variations.
D = Delay offset of the signals between antennas.
B = Bandpass response: The relative amplitude and phase of an antenna system as a function of frequency.
1 https://science.nrao.edu/science/meetings/2014/14th-synthesis-imaging-workshop/lectures-files/
MoellenbrockCalibration2014_FINAL.pdf

10.3. ALMA-SUPPLIED A PRIORI CALIBRATIONS123

G = Electronic gain: The temporal amplitude and phase changes within the antenna system.
F = Flagging: Editing of data based on calibration problems.
Do not be intimidated by the above list. The main ALMA calibrations of interest to most users deal with thetemporal electronic gain G and the bandpass response B. A good approximation that simplifies the calibration
process is that the temporal dependence and frequency dependence of nearly all instrumental changes are only
lightly coupled, so their variations can be determined independently, or at least iteratively.

10.2.3A priori, Online and Offline Calibration Methods

There are three stages of calibrations in ALMA.
A priori Calibrations: These are calibrations that are associated with relatively fixed properties of thearray, for example the antenna response patterns. They are measured periodically by the ALMA staff
using methodologies that best suit the calibration. These calibrations are briefly outlined below.
One of the more important a priori calibrations in cycle 3 is the Go/noGo 2-min observation/analysis
procedure on a strong calibrator. It is run periodically in order to assess the current ALMA phasestability. Within minutes the 30-second phase rms as a function of baseline length at any frequency will
be determined. If the phase rms at the longer configuration baselines are larger than 30◦ at the frequencyof the anticipated observations, then observations are not recommended. Unless conditions are changing
rapidly, this Go/Nogo evaluation need be done only every few hours.
Online calibrations: Measurement of relevant instrumental parameters are made during the observations todetermine calibration values that can be applied as the data are taken. These include antenna pointing
calibration (applied as a collimation offset relative to the master antenna pointing models which are
updated on approximately weekly timescales), measurement of Tsys /TRX using the Amplitude Calibration
Devices (ACDs), and determining Water Vapour Radiometer channel coefficients to allow rapid online wetpath delay variation to be compensated in the correlator data processing software. Application of some
online calibrations such as Tsys are deferred to the offline calibrations, however.
Offline calibrations: The offline calibrations are those done after the completion of the experiment. These areusually associated with relatively fast-changing calibrations that cannot be made online. These correction
are applied by the reduction scripts (pipeline or script generator) using measured system properties, suchas the receiver operation temperatures, or by the analysis of of special-purpose calibrator observations thatare 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 the experiment, G. The accurate calibration of these terms have the largest impact on the image
quality, and are of most concern to the user.

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 beam center (called primary beam pattern) is used to correct the images ofextended sources, and multi-pointings observations (mosaicing) with overlapping fields. The measurements
are made by mapping the antenna beam using a bright radio source, either single dish scanning around astrong source or with interferometric observations at many points within the antenna sensitivity area. The
measurements are processed in special-purpose software to determine the accurate antenna surface, andadjustments of the antenna panel supports can be made if the surface is not within specifications. The

124

CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

measured primary beam patterns are available in the Casapy package and applied during the image-makestep (see Chapters 3 and 7 for more details).
Pointing Models (P): Blind 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, plus collimation offsets for each receiver band relative to a reference band (traditionallyBand 3, but this may be changed during cycle-3 in favour of a band without warm optics i.e. band 6 or 7).
The terms in addition to those already mentioned, and the deviation of receiver band collimation offsets
and antenna-type dependant elevation sag from a known average, are at the arcsecond level.
The pointing models are checked and adjusted on typically weekly timescales, primarily by making "all-sky
pointing runs", which are executions of around an hour in duration that make typically 50-100 interferometric pointing measurements on a well-distributed set of bright quasars of accurately known position.
Each pointing measurement scan consists of a set of subscans at different antenna pointing offsets aroundthe expected pointing direction (with fixed delay centre). The scalar-averaged visibilities at each pointing
offset are used to produce antenna pointing solutions, with typical accuracy of around 0.100 . Ideally all
antennas observe together on the Baseline (64-input) correlator, and the pointing offsets are appropriately scaled for different antenna diameters. Such pointing measurements in different bands on a subset
of bright sources are used to determine the band collimation offsets for the models. The models are
stored in the Telescope Monitor and Configuration Data Base (TMCDB), which includes change history.
Pointing measurements over many weeks, and including measurements made in other observations, including science executions, can also be used in deriving models when appropriate. Currently only nighttime pointing measurements are considered in these static models, with daytime pointing modelling andmetrology system improvements an ongoing effort.
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 observationally by fitting total power data recorded while the antenna performs azimuth
strokes across a planet or bright quasar. After this the pointing model is refined as described in theprevious paragraph.
In all science executions pointing measurements are made near the science targets and calibrators at thetime of execution, from which residual collimation offsets at typically arcsecond level are applied in an
auxiliary pointing model, which is added to the master static TMCDB pointing model for each antenna.
With this residual offset pointing correction, the pointing accuracy for science target 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 according to a six parameter model, plus offsets for each receiverband relative to the reference band (Band 7). The models contain an offset for each axis which describes
the optimum subreflector position for Band 7 at elevation 50◦ and temperature 0◦ C ("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 maintained by longterm compilation of focus measurements in all receiver bands for the antennas, with care taken with regard
to hardware changes which may change the focus characteristics. Focus measurements are traditionallymade in a similar way to as described for pointing measurements, except the subreflector is offset (in one
axis per scan) relative to the nominal model position. The subreflector position in the axis being offset
which yields maximum gain is solved for each antenna from the cross-correlation data. During Cycle-3 a10.4. ONLINE CALIBRATIONS

125

faster technique, deriving the 3 axis focus offsets from holographic beam maps (which don’t require thesubreflector to move), may be used in some cases. These measurements are made by the observatory as
needed to maintain the models. The models are stored in the TMCDB in the same manner as the pointing
models.
Typically at night time these models, including temperature dependance (a new feature for Cycle 3), canmaintain the focus to within a few tens of microns, which is adequate for most observations. Particularly
the X and Y position is generally better described by the models than can be determined from anindividual focus measurement. Generally when switching to a new receiver band it is a useful cross-checkto make a focus calibration in the Z axis, for which standard Scheduling Blocks are available, which allow
to check for pointing and delay errors as by-products. These are especially important for Band 9 and
10 where focus accuracy is most critical, but this currently requires an extremely bright quasar to beavailable, or the atmospheric conditions to be excellent. In daytime the focus can deviate from the models
by several hundred microns. In daytime a focus calibration observation is generally executed between
every science execution for Band 6 and above (typically Band 7 is the absolute maximum for daytime
observing) in order to try to track these variations, but the poor atmospheric stability means that thefocus measurements themselves have large uncertainties. Generally it must be expected to have focus
errors at the 100 micron level in daytime ALMA data. At night errors below 20 microns are achievable.
As for pointing, modelling and correction of focus during daytime is ongoing work.
The focus model in-use at any time during an observation is stored in a FocusModel table in the ASDM
datasets.
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 signal path of each array element. These are made with short interferometricobservations at the relevant tunings as needed. Typically if offsets of more than around 100 ps are seen
then the delay model in the TMCDB will be adjusted. Delay measurements for a given tuning are typicallyrepeatable to better than 10 ps, but the measurements vary by a few tens of ps from tuning to tuning
due to receiver RF and IF phase response variations. PIs can expect online delay errors in their data to
be below 100 ps, so it is possible to use channel-average data for quick continuum analysis. The primary
motivation for maintaining accurate delays is for pointing, focus and beam measurement calibrations,which use the channel-average data to reduce processing time and allow very short integrations where
needed.
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, about 50 microns. These
values are among the most critical for the determination of the accurate correlator delay model, M . For
the main array, the specification is 65 µm and for the 7-m array it is 33 µm. The baseline runs (asthey are called) are executed by the ALMA staff at least once per week, but also whenever one or moreantennas change pad locations. Then antenna positions are determined from about 50 to 100 one-minuteinterferometric scans at 100 GHz of quasar calibrators that are unresolved and have milli-arcsec accurate
positions. The observations cover a wide range of elevation and azimuth to determine the three spatialoffsets of the antenna position from that listed in the TCMBD used in the correlator model. The typical
position offset associated with an antenna that has been moved is 1 mm even for pads that have alreadybeen occupied, well above the specification, so that baseline 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 updated in the TCMBD for several days. Thus, the correlator delay
model will be incorrect and the visibility phase for data associated with this antenna can have significant
phase variations with time and between sources. There are offline procedures in the data reduction scripts
to correct for these known antenna position offsets from available antenna location/pad files.

10.4

Online Calibrations

Water Vapor Radiometer Corrections (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

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

at 90 GHz, and scales in phase linearly with frequency. The changes are driven by wind, and cover alarge range of spatial scales. All ALMA 12-m antennas are equipped with a Water Vapor Radiometer(Dicke-type) that measures the emission of the atmospheric water line within four spectral bands near
183 GHz at a rate of about 1 Hz. The radiometers are described in Sections 5.4 and A.6. From thesemeasurements, atmospheric models are used to convert the emission into delay changes in the line-ofsight of each antenna, and this estimated delay difference between any two antennas is removed from thevisibility phase. For cycle 3 the PWV correction will be applied online by inserting the appropriate value(M) into the correlator model, M . Less than 10% of the times, the application of the WVR corrections
increases the phase rms because of clouds or ice above the array. In these cases it is best not to use theWVR correction. The water vapor emission in the four channels are also stored in the archived visibility
data base, so the corrections can be determined and applied offline using a similar algorithm. The 7-marray with a maximum baseline of 50 m does not have water vapor radiometers since the phase corrections
between these antennas are small. The PWV measurements on the four PM antennas that surround the
7-m could be interpolated to apply an approximate WVR correction to each of the 7-m diameter antenna,
but this is not planned.
System and Receiver Temperature (T): At millimeter and submillimeter wavelengths, the atmosphereboth attenuates astronomical signals and acts as a black body emitter that adds additional noise to any
measurements, T . This effect is a strong function of frequency, elevation, the column of wet and dry
constituents of the atmosphere, and the temperature of the atmosphere. The noise from the receivers canalso vary for a given tuning with factors such as cryostat temperature and pointing direction with respect
to the local magnetic field.
To measure these effects, the ALMA front ends are equipped with an Amplitude Calibration Device(ACD) which can move hot and ambient blackbody loads in front of the receiver feeds. Consecutive
autocorrelation (or total-power) integrations on these loads and the sky are used to measure the Tsys andTRX in each spectral channel. This depends on 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 polarisation products) of the Baseline correlator23 . For the ACA correlator in Cycle-3 itis planned to use the same spectral configuration (resolutions) for temperature calibration as the science
setups, as it does not have distinct operating modes and produces linear output4 .
These are naturally total temperature measurements, which include the receiver-weighted contributions
from both sidebands. In cross-correlations the image sideband only contributes noise but not signal (LOswitching sequences are used to highly suppress image sideband cross-correlations), so the natural Tsysand TRX are scaled-up by a sideband gain factor to produce single sideband temperatures which can bedirectly applied to visibilities to put them in temperature units. In Cycle-0 to Cycle-2 scans were includedin every science execution to measure baseband-averaged sideband gains, however, at present it appears
these are not actually helpful overall in terms of calibration accuracy5 and the approximately 70 secondsof time taken per execution is not justifiable. For Cycle-3 it is planned to only use default sideband gains
that are a constant per receiver band (nominally 0.99 for 2SB and 0.5 for DSB bands). This policy may
be changed as deemed necessary by the observatory.
These measurements should be sampled every 5-15 minutes depending on frequency. The specifications
for Tsys calibrations are to reach 1% repeatability. The online measurements of Tsys and TRX are stored
in the CalAtmosphere table in the ASDM datasets, and are displayed as they are produced during the
2 In TDM mode the autocorrelation zero lags can be used to fully compensate for quantisation effects on the autocorrelations,however, in FDM mode which adds a filter bank before the correlations are produced an external measure of the total digitised
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 unfeasibly 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-3 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.
5 The main problem is that when you really care about the sideband gain is when strong atmospheric emission features arepresent in either sideband, but this unfortunately is the worst case to measure as you have low S/N from the calibrator sourceat the relevant frequency. Obtaining sufficient S/N also means that we can generally only derive baseband-averaged sideband
gains, which are of limited applicability to the atmospheric lines which are to be accounted for. Generally the measurements areerror-prone, and the situation gets worse with fewer antennas (i.e. ACA arrays) and at higher observing frequencies.

10.5. OFFLINE CALIBRATIONS

127

observations (baseband-averaged) to allow problems to be immediately seen by AoD or Operator. The
calibrations can also be re-derived offline from the raw data if there are problems online or it is desired
to use a different or updated algorithm. The Tsys spectra, suitably interpolated, are applied offline to thecorrelation data. Assuming that the correlated data is in units of percentage correlation, multiplicationby the Tsys will change the correlated data units to Kelvin.
Additional Antenna Pointing Checks (P) As mentioned previously under A Priori Pointing Models,pointing corrections are made during executions in order to reach ALMA’s 0.600 RMS pointing accuracy
specification. These account for small variations with respect to the static models which are updated on
weekly timescales. To some extent these per-execution pointing calibrations compensate for shortcomings
in the antenna metrology systems, and errors in the static models, for instance due to hardware changes
since the last update. These pointing measurements are managed by the observatory – there is no PI
input. At present a pointing calibration is triggered whem moving to a target more than 20 degrees fromthe previous pointing calibration.
Generally it is desirable to point using the receiver band used for science in an execution. This is mostly
possible up to Band 8, at least for large arrays of antennas. At Band 9 and 10 the combination of highTsys , low quasar flux, low antenna aperture efficiency (∼ 0.2–0.3% for 12m antennas) and inadequacy of theblind pointing accuracy (static model plus metrology correction) means that pointing must be done in alower frequency band and the collimation offsets between the two bands be relied on. Future improvements
may allow pointing in-band for Bands 9 and 10 in future Cycles. The choice of pointing tuning will bemade by the observatory in order to maximise available array elements by avoiding bands or frequencies
affected by hardware problems, and minimise pointing error.
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 by AoD or Operator. 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 offline calibrations are those that are applied by python/casapy scripts after completion of the SB observations. The first step in the 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) which contains
one-dimension tables for all of the data products (Chapter 12). A combination of python scripts and casapy
are then used for the calibration and display of the data.
An initial offline reduction at the OSF is called QA0. It is made on an MS that is been recently completed
in order to determine if there are serious errors in the MS (See Chapter 12). If it passes this inspection, the SB
is then queued for the complete offline calibration using the ALMA Pipeline for standard experiments, or the
Script generator code for non-standard experiments.
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 more thana specified amount from the calculated settings or when relevant local oscillators are not locked. These
flags are stored in the SB archive data base in two ways, xml and binary flags. One of the initial offline
calibration steps are to apply these flags.
Online vs Offline Calibrations?: Some calibration steps that could be applied online are applied during theinitial offline reduction step using the appropriate data tables written by the online system. One example
the WVR delay calibration. The main reason for postponing the online corrections is that occasionallythe relevant data are not complete or partially wrong, so must be modified before incorporation of therelevant calibrations.

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CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIES

Bandpass Calibration (B): The remaining frequency response associated with the SB will not be flat in
amplitude and phase, although the delay errors that produce a large slope of phase with frequency shouldhave been removed by the a priori and online calibrations. For each SB and tuning, the bandpass isdetermined from a scan of a bright calibrator source with a known radio spectral index in order to not
introduce an amplitude slope in the bandpass or between SPWs. After removing any significant phasevariations over the bandpass scan (see next item), the casapy task bandpass determines the amplitude andphase the for each antenna/SPW/pol as a function 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
below in the sensitivity section. The stability of the bandpass with time and with angle is extremely
good6 , so that one bandpass determination per tuning per SB (about an hour) will not change by morethan 0.4%, so that this bandpass can be applied to all of the data in the SB.
Electronic Gain Calibration (G): Virtually all ALMA observations use the phase referencing technique tocalibrate the target source visibility data. The largest temporal changes, especially in phase, should havebeen 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 results can be applied first and then the
combined SPW/pol antenna solutions for the phase calibrator can be determined.
The plots of the results 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 thanabout 20% among the antennas. For antennas with low gain or obvious drop-outs, check on the data
quality, Tsys application, and the observing logs for any mention of a problem with the antenna. (2) The
interpolation of the antenna-based phase determinations between calibrator scans should be obvious, since
this is the phase that will be applied to the target, even for the longest baselines. The use of the Go/Nogo
observational check in Cycle 3 should avoid observations with unacceptably large phase variations thatwould give poor image quality. Data flagging should be made for antennas and time ranges as appropriate.
Absolute Flux Density Calibration (T):The Calibration of the data using the Tsys measurements converts
the raw correlation amplitude into Kelvin. The conversion of the correlation units of Kelvin to Jy is madeusing the system equivalent flux density (SEFD) that is measured for each antenna. For example, the12-m antennas at Bands 3, 6 and 7 have an SEFD of about 35 K/Jy. This a priori conversion is accuracy
to about 5% at Band 3, 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 included in the SB. It is possible derive reliable Kelvin to Jy conversion byusing any of the 10 solar system object for which very accurate visibility models are available. Also about
30 bright quasars (grid sources) at Bands 3 and 7 are monitored by ALMA every few weeks, and thederived flux densities (as interpolated in time and frequency) also provide the K to Jy conversion of thevisibility.
Polarization Calibration (p,X): For Cycle 3, the polarization calibration is made on a bright polarized
quasar that is polarized by at least 3%. The observation period needed for the calibration is abut threehours during which the calibrator rotates at least 90◦ in parallactic angle. Two steps are needed to obtaincalibrated cross-hand (XY,YX) data using the polarization calibrator. First, after the XX and YY data
are calibrated (bandpass and gaincal), the XY and YX frequency dependence for each SPW will not be
zero, but reflect the (X-Y) polarization delay and phase difference. This phase frequency dependence isthe same for all antennas, but with opposite phases in the XY and YX data. These global phase-frequency
terms are then removed.
The second calibration setup determines the leakage between the X and Y polarizations (called D-terms)
for each antenna and SPW There are two leakage terms: one related to the non-orthogonality between the
X and Y feeds, and one related to the orientation offset for the feeds. Both of these calibrations are don in
the offline script and then applied to the entire data set in order to calibrate the polarization properties forall of the other sources. Because the XY,YX antenna beam sensitivity is considerably more complicated
6 See http://almascience.org/documents-and-tools/alma-technical-notes/ALMATechnicalNotes15_FINAL.pdf

129

10.6. APPENDIX

than that for the XX and YY polarizations, only sources with an angular extent less than 1/3 full-width
half-power can be accurately imaged in linear polarization.

10.6

Appendix

10.6.1

ALMA Catalog Description

The ALMA catalog of sources contains information for about 10,000 calibrators south of δ = 45◦ . About 1100
are high quality calibrators with a positional accuracy < 0.00200 , and flux density at 100 GHz greater than 30
mJy. The catalog is accessed in (https://almascience.org/sc/). The appropriate bandpass calibrator and phasecalibrators for an observation are automatically chosen when the observing scheduling block is prepared, butthese calibrators can be selected by the PI when the proposal is submitted or during discussions with the ALMA
liaison before the observations.
On the average, the separation between a target and the 1100 good quality calibrator in the catalog isabout 4◦ . A weak calibrator survey is now in progress at ALMA in order to find additional calibrators that are
sufficiently compact and strong. The goal is to double the number of available calibrators for the start of Cycle
3 observations.

10.6.2Phase Calibrator Sensitivity

The phase calibrator chosen for an SB is picked by the calibrator query (See Chapter 8) when the observing
schedule is prepared about a month before the nominal observation date. In most cases, the optimum calibrator
can be determined months ahead of time. If its flux density is less than about 1.3 times the lower flux density
limit, there is a slight possibility its strength may fall below the sensitivity limit at the observation time. The
flux limits should be scaled by (Nant /36)−0.5 (Tsys ) [(tscan /120) (νBW /7.5GHz)]−0.5
The lower flux density limits for a phase calibrator for all of the observing bands are given in Table 10.1
below.
Band
3
3
4
6
7
8
8
9
9
9
10

Flux Density Limit for Phase Calibrator
Frequency Assumed Tsys Assumed PWV Flux Density
(GHz)
(K)
(mm)
(mJy)
86.24383
5.186
4.6
115.271
173
5.186
9.7
146.969
86
1.796
4.9
230.538
102
1.262
6.0
345.796
151
0.658
9.5
461.041
431
0.472
30.0
492.161
638
0.472
46.0
624.208
4302
0.472
364.4
658.007
1721
0.472
152.9
691.473
1231
0.472
114.9
806.652
2405
0.472
271.3

Table 10.1: 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 36 antennas and elevation of 50 degrees.
The total bandwidth in both polarizations of 7.5 GHz is assumed.

The scaling of the flux density varies as Tsys , elevation, bandwidth, number of antennas in the usual way.

130

CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESThe recommended phase calibrator is the one closest to the target that meets the minimum sensitivity limitof an SNR = 15 per antenna solution. Since the nominal scan to scan atmospheric phase changes are larger
than 5◦, using a stronger but more distant calibrator is not recommended.

10.6.3

Bandpass Calibrator Sensitivity

The bandpass calibrator must be significant stronger than the phase calibrator since the frequency dependence
versus channel for each SPW and polarization separately must be determined. However, the bandpass calibrator
does not need to be close to the target (within < 45◦ ) so that a sufficiently bright source should be normallyavailable. The main sensitivity concern is obtaining sufficient SNR for FDM channels. Testing has shown thatbandwidths < 31 MHz, the bandpass is flat to 1%; so bandpass calibration over narrower bandwidths is notnecessary.
The minimum flux density for a calibrator to meet the 50 SNR specification for each antenna gain determination (2% rms in amplitude for each of the observing bands are given in the table below. The flux limits
should be scaled by (Nant /36)−0.5 (Tsys ) [(tscan /900) (νBW /128M Hz)]−0.5
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
60.7
115.271
173
5.186
128.0
146.969
86
1.796
64.1
230.538
102
1.262
78.8
345.796
151
0.658
125.2
461.041
431
0.472
395.7
492.161
638
0.472
605.8
624.2084302
0.472
4801.4658.0071721
0.472
2014.5691.473
1231
0.472
1514.2806.6522405
0.472
3575.0850.000
1817
0.472
2922.5

Table 10.2: 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, 36 antennas, and elevation of 50 degrees. The
resolution bandwidth is taken to be 128 MHz.

10.6.4Band-to-Band Phase Calibration

The closer a calibrator is to the target, the more accurate will be the phase-referenced the image. For imaging
at the higher frequencies (> 400 GHz), the technique of band-to-band phase transfer has been developed inorder to measure the phase of the calibrator in a lower ALMA Band, then suitably scale the phase solutions
to the higher frequency target. This calibration is effective if the low frequency calibrator is significantly
closer than the best high frequency phase calibrator (See Figure 10.1). This calibration method should beavailable in Cycle 3 for high frequency (Bands 8, 9 and 10) observations and will be discussed with PIs during
the generation of the SBs at Phase 2. Details are given in http://almascience.org/documents-and-tools/almatechnical-notes/ALMATechnicalNotes8_FINAL.pdf.

10.6.5

Bandwidth Phase Transfer

When observing a target within a narrow SPW bandwidth, a close phase calibrator that is detectable withthis narrow bandwidth is often not available. In this technique, a strong calibrator (not necessarily near the10.6. APPENDIX

131

Figure 10.1: Band-to-band imaging of target source J1743-0350 at Band 9. Left: The target image calibratedusing a strong source 14◦ away. Middle: The target image calibrated using a weaker calibrator 4◦ away with thesolutions derived in Band 6. Right: The actual target image after self-calibration. The target peak flux densities
from left to right are 0.17, 0.27, and 0.31 Jy. The rms noise on the images are 7.2, 3.6, and 1.6 mJy/beam.
Credit: Ed Fomalont, Violette Impellizzeri (NRAO/JAO)

target) is observed at both a wide and narrow bandwidth in order to determine the amplitude ratio and thephase difference between the two bandwidths. The phase calibrator is then observed only with the wide bandwidth, and the wide band to narrow band amplitude and phase corrections are applied in order to calibrate
the target observed only with the narrow bandwidth. This calibration method should be available in Cycle
3 for high frequency (Bands 8, 9 and 10) observations and will be discussed with PIs during the generation of the SBs at Phase 2. Details are given in http://almascience.org/documents-and-tools/alma-technicalnotes/ALMATechnicalNotes11_FINAL.pdf.

10.6.6

Astrometry

The goal of astrometric experiments are to determine the accurate position of a target source. If the position
accuracy needed is > 0.0500 , then normal phase referencing is sufficient if the calibrator position accuracy is< 0.0100 and it is within about 5◦ of the target. Band 7 is probably the best band to determine the accurate
position for most thermal objects.
For position accuracy to about < 0.00200 rms, it is recommended to include several check sources (secondary
calibrators) in addition to the target and main phase calibrator. A scheduling block is available, and the PI
should choose the main calibrator and several secondary calibrators. For more information, please contact the
ALMA Helpdesk (https://help.almascience.org/)

10.6.7

Long Baseline Observations with Baselines > 3 km

The calibration of long baseline observations is similar to that at the shorter spacings. Several considerationsare:
The possibility of self-calibration of the target is more important for long baselines, because the phase variations
will be larger. Thus, the image quality with phase referencing alone may not reach the intended signalto-noise and image fidelity. To determine if self-calibration is possible, the correlated flux density of thetarget at the longer spacing must be comparable to that needed to detect a phase calibrator.
Does the source have sufficiently small-scale structure for long baseline observations? For many thermal
sources, this requires an emission temperature of a few hundred degrees or more.

132

CHAPTER 10. CALIBRATION AND CALIBRATION STRATEGIESThe choice of a close calibrator to the target is important in order to removed systematic phase errors at thelonger baselines. If a calibrator is not available within about 4◦ of the target, requesting ALMA to search
for a closer calibrator, using the weak calibrator survey program, is recommended.
If the source is extended more than 200 at band 3 (scaling inversely with frequency), then the long baseline
configuration will not be able to include all of the emission. For Cycle 3, an additional configurationmust be proposed as a second science goal in the proposal.

Chapter 11

Quality Assurance
The goal of ALMA Quality Assurance (QA) is to ensure that a reliable final data product is delivered to the PI,
that is, the product has reached the desired control parameters outlined in the science goals, it is calibrated tothe desired accuracy and it is free of calibration or imaging artefacts. For Cycle 3, there are several restrictions
that may make it a bit more difficult to achieve this goal. It has therefore been decided that QA will still
be done on a “best effort” basis, covering all the major issues affecting data quality (see below). The QA
analysis will be based on a calibration plan that specifies which observations must be acquired and at whichintervals to monitor system performance and environmental factors as they evolve with time. Furthermore, itwill tackle issues related to the 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 incorrect source coordinates, inadequate frequency setting (e.g. an incorrect redshift) or
inadequate sensitivity limits (leading to an inadequate integration time or inadequate uv plane coverage) areoutside 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.
1 JIRA is a proprietary issue tracking product, commonly used for bug tracking, issue tracking, and project management

133

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11.1

CHAPTER 11. QUALITY ASSURANCE

Cycle 3 "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, during ALMA Early Science (including Cycle 3)
the Observations are subject to "best efforts", meaning that the observatory will attempt to meet the sensitivity
and resolution stated by PIs in their Science Goals, within certain tolerances as described later in this chapter.
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), but the resulting products may ultimately
fall short of the requested goals, due to limits imposed by the available configurations or system performance.
In particular, observers may need to invest their own time and expertise to ensure that the data products areof the appropriate quality and to re-reduce the raw data if the quality is not satisfactory. This may include theneed to 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). QA0 metrics/parameters havebeen 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.
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 images, but PIs can access those data and reduce them if they wish. QA0_FAIL datasets are thosethat 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 3 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 3 (i.e., 36), and the average system temperatures expected at the frequencyof the observations. Executions with higher rms noise levels than the reference will have fractional execution

11.3. QA1

135

weights between 0 and 1, while those with lower rms noise levels, which can be achieved, for instance, witha larger number of antennas in the array, or with lower system temperatures, will have a fractional execution
value above 1.

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 will, 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 and analysis of data productsthat some of the science goals set by the PI can be compared with the results (i.e., rms, angular resolution,
SNR, dynamic range, etc).
During Cycle 3, 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 for some basic imaging. Additional imaging will
be done by data reducers that will then perform the QA2 assessment. The Pipeline provides a Weblog page
with detailed information on the quality of the Calibration, which will provide the basis for Pipeline QA2. For
manually-reduced datasets, and the imaging of pipeline-calibrated data, 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.
Final Data Characterization:

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CHAPTER 11. QUALITY ASSURANCE• 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: standard (all-data) imaging; in images of specified spectral regions. These
values are compared with those predicted from data after flagging and with 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 a 10% of the specification. QA2_SEMIPASS refers to those datasets that fall short of meeting
the PI requested science goals, but are otherwise of good quality. QA2_FAIL is a temporary state used during
an observing cycle when an observation fails to meet the PIs goals by a significant margin (30% worse) andneeds to be reschedule for additional observations. If these data fail to obtain enough additional observations
to pass QA2 by the end of an observing season, their QA2 state is changed to QA2_SEMIPASS and they aredelivered 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
3 User Policies document.

11.6

The Quality Assurance Report

During Cycle 3 the Quality Assurance Reports of QA0 and QA1 will be accessible to the PIs using the Project
Tracker. These reports will be generated using the AQUA tool. For the QA2 reports, for Pipeline calibrated
datasets, the PI will receive, as part of the data delivery, the Weblogs, and the outputs of scripts that measure thecritical QA2 metrics. For non-standard observing modes that require manual data reduction, script-generated
QA2 reports will be delivered instead.
The basic unit of a Report is the ObsUnitSet, which represents a scientific goal stated by the PI during
Phase 1 (project creation and review). An ObsUnitSet will typically contain several executions of SBs. For

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137

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 3, an interface between the Pipeline and AQUA is made available. From that point
onwards, complete QA Reports will be generated using the AQUA software and delivered as such. The final
report per ObsUnitSet delivered to the PI would in that case be a concatenation of all the relevant QA0 and
QA1 reports per execution with the QA2 report. Comments on each 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 are quite far from what has been requested by the PIs. 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 an acceptable standard, they may bereleased to the PI.

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. Furthermore, the execution has to be "significant"in terms of the fractional execution (i.e., more than 0.2). If it does not meet these criteria, but has some usefuldata (calibrator or source), or has a fractional execution that is less than 0.2, it is classified as QA0 SemiPass.
This makes the data available through the ALMA archive, but it will not be used in the generation of theimaging 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 3 are based on thefollowing:- Antennas: QA0_SEMIPASS for fewer than 17 antennas available in the 12-m Array or fewer than 5antennas in the 7-m Array or fewer than 2 Total Power Array antennas. States that will be considered torender 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 bandpass calibrator signal too weak, with amplitude wiggles across the
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 9 antennas in the 12-m Array, or more than 3antennas in the 7-m Array, or more than 1 Total Power antenna with Tsys values > 50% of the others,with differences between polarizations > 50% for a given antenna or with Tsys > 2000 K. QA0_FAIL incase more than 15 antennas in the 12-m Array, more than 5 antennas in the 7-m Array, or more than 2antennas in the TP Array have Tsys in the ranges specified.
- 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
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, 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, respectively), the synthesized beam shape (i.e., 20%of goal) and the calibration quality (phase RMS and absolute accuracy).

Chapter 12

Logical Data Structure and Data Flow
This chapter describes the 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 andarchiving, 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 then selected from the list provided by the
Scheduler subsystem, and the execution is started. All the SBs for a given observing Cycle are stored in theArchive after successful Phase 2 completion. The Scheduler subsystem keeps a local up-to-date database of all
the SBs (including their status) for that Cycle. The Telescope Operator and Astronomer on Duty (AoD) have
two options for using the Scheduler during Early Science observations. They can either let the Scheduler suggest
possible SBs to execute, or they can carry out targeted searches of the local database. For Early Science, theScheduler 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 theadvice 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 which would have been manually selected by an AoD.
Once the execution of the SB has been selected from the Scheduler, it is dispatched to the Control subsystem.

139

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CHAPTER 12. LOGICAL DATA STRUCTURE AND DATA FLOW

Figure 12.1: Main actors and roles during observations with ALMA. The horizontal direction represents time
evolution.
Control parses the SB XML document into python objects, and executes the observing script selected in theSB, 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
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. The best way todescribe the Data Capture module is as an interface between the real-time domain of the data taking and the12.2. THE ALMA SCIENCE DATA MODEL

141

storage side. As an interface, it captures and stores into the Archive all the relevant meta-data information
pertaining to a complete description of the data and their supporting calibration and monitor datasets andcondenses 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 linksof 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 displayğ in semi-realtime. Finally, when the SB is finished, Data Capture is in charge of checking that all products representing
the raw data have been produced and stored in the archive, and announces the completion of the SB to the
Scheduler subsystem. It is clear from the list of roles above that Data Capture is a very complex module; it has
to handle Correlator and backend data in addition to supporting (source information, spectral set-up, etc), andmonitoring data which are needed for data reduction (weather, pointing, etc). All this information originatesin different hardware and software elements, each of which can be sampling at different rates and with limited
view of the behavior and state of the observing system.
A summary plot of the main elements involved in data flow is shown in Figure 12.2. As indicated in the
figure, all components passing through the Data Capture module contribute in the generation of the metadata
associated to a dataset, which is in XML format. The bulk of the data (binary) is sent to the Archive andlinked to the metadata using requests to the Archive.

Figure 12.2: Data flow components.

12.2

The ALMA Science Data Model

The ALMA Science Data Model (ASDM; Viallefond, F. 2006, Astronomical Data Analysis Software and Systems
XV, 351, 627) defines the collection of information recorded during an observation that is needed for scientificanalysis. As described above it contains both bulk binary data and metadata (XML) organized in tables. The
tables contain links to other XML tables and addresses pointing to the actual bulk data in the Archive. The
ASDM contains 16 core tables that are common to all observing modes, and up to 23 additional tables thatare 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, withthe columns listing the contents and the rows including the actual values. The core tables have been defined tooutline 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 some references, that is, some of
the information is shared between tables.

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CHAPTER 12. LOGICAL DATA STRUCTURE AND DATA FLOW

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 is also
possible, and the techniques will be optimised as Cycle 3 proceeds. Standard Pipeline processing recipes areused in Science Operations. In the future the Pipeline will also have the capability to combine the data takenusing 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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CHAPTER 13. PIPELINE PROCESSING

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 need to perform ALMA Quality Assurance 2 (QA2), i.e. itcalibrates the data and eventually will perform all imaging. This results in data products that can be delivered
to PI and stored in the archive. However, these products will only be delivered and ingested into the Archive ifthey 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 Quickstart Guide.
The Pipeline QA scores, and the algorithms used to determine them, will in future 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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CHAPTER 13. PIPELINE PROCESSING

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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13.2.5

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 3 are listed in the Cycle 3 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/or science target(s) observed in an OUS, the data from all
Execution Blocks is now imaged together for each target. During Cycle 3, some proportion of ALMA OUS will
be calibrated using the Pipeline but imaged manually until Pipeline science target imaging is commissioned.

13.3.2

Pause after Data Import

In current practice, the ALMA Pipeline does not run straight through after triggering. The first time that the
Pipeline is triggered, it will perform the import of each Execution Block of ALMA data only, with no calibration.
The reason for this is multi-fold. Firstly, it is useful to check at this point the flux calibrator fluxes that havebeen obtained for any quasar flux calibrator. These values can be overridden if desired at this pause. 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 improvethe 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 3 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. forinterferometric 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

149

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 can be 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 during the
OUS/session. Note that 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 3 Pipeline Quickstart Guide for a
full description of how the Cycle 3 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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13.5.4

CHAPTER 13. PIPELINE PROCESSING

Reference Antenna Selection

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

13.5.5

Offline 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 vis file is greater than the value in accept_threshold thenit makes available the wvr calibration file for merging into the context and for use in the subsequent reduction.

13.5.6

Low gain 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 3 Pipeline Reference Manual. The
CASA tasks employed during the heuristics for this step are bandpass and gaincal.

13.5.7

Bandpass calibration & flagging bandpass solutions

The Pipeline task hif_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). While it is common practice to perform this using a narrow frequency
range of each spectral window only, in case of delays (slopes in phase vs frequency), at ALMA it is generally fine
to 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). Flagging of the bandpass solutions may be performed.

13.5.8

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 themodel visibilities for the flux calibrator.

13.5.9Deriving 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. This is because the model is more trusted for the shorter baselines. This is performed by using
the CASA tasks gaincal and fluxscale.

13.6. LOW SNR HEURISTICS IN INTERFEROMETRIC PIPELINE PROCESSING

13.5.10151

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.

13.5.11

Applying the calibration

The Pipeline uses the CASA task applycal to apply the calibration tables to the dataset. A strict settingof applycal is used by default in the Pipeline (any data without full calibration available is flagged. Thisconservative approach is taken in order to prevent any non-properly calibrated data getting through the Pipeline.

13.5.12

Imaging

At minimum, the Pipeline images the bandpass and phase calibrators as a diagnostic check, producing an image
per spectral window. Pipeline science target imaging may be commissioned during Cycle 3. Prior to this,Pipeline calibrated datasets will be manually imaged by ALMA staff.

13.5.13

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 file 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

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.

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13.6.1CHAPTER 13. PIPELINE PROCESSING

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.

13.6.2Using 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.
This will become available in the Pipeline during Cycle 3.

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.

13.7

Total Power Data Processing

Differently to interferometer operation, total power observations are designed in paired MOUS: one ‘science’
MOUS (i.e. the science target), and one calibration MOUS (used to derive the Kelvin-to-Jansky conversion
factor). Both MOUS exist within the same GOUS and Pipeline processing is performed per MOUS at the
beginning of deployment of Single Dish Pipeline.
Pipeline operation slightly differs between processing science targets and amplitude calibrators. Since Cycle 3
offers only spectral line emission observations for science targets, the processing for science targets always haveline identification, baseline subtraction and subsequent flagging based on baseline rms after the Tsys and Sky
calibration, followed by imaging. The processing for amplitude calibrators is generally similar in many ways, butaims to extract only the continuum signal; i.e. the same calibrations steps are followed as for the science data,
although the imaging step immediately follows without line-identification, baseline subtraction, and baseline
rms flagging.

13.7.1

Data Import(Both Calibrator and Science data). The Pipeline first loads the data into the pipeline context unpacking and/or
converting it as necessary.
Note that the imported files are in MeasurementSet (MSs) format, but the Single Dish Pipeline converts the
MS-format files into Scantable format at the steps after generation of Tsys tables (see ‘Tsys & Sky Calibration
Tables’).

13.7. TOTAL POWER DATA PROCESSING

13.7.2

153

Deterministic & Manual Flagging(Both Calibrator and Science data). The Single Dish Pipeline applies online flagging of shadowing, identificationof un-needed intents such as FOCUS, as well as some edge-channel flagging. It is also possible to insert manual
flagging if an additional flagging than pipeline does is needed.

13.7.3Tsys & Sky Calibration Tables(Both Calibrator and Science data). The Pipeline creates Tsys calibration tables. Each spectral window of thescience targets is automatically mapped to the corresponding, frequency-matched Tsys spectral window.
The Pipeline creates the sky calibration tables, linking each ‘ON’ (i.e. on-source) spectrum to the corresponding spectrum at ‘OFF’ (i.e. reference) positions. In contrast, the edges of the maps of the amplitude
calibrators are treated as OFF points.

13.7.4

Applying the calibration(Both Calibrator and Science data). The Pipeline uses the CASA task sdcal2 to apply the Tsys and Sky
calibration tables to the dataset. At the completion of this step, the resulting data are bandpass-corrected andhave temperature units of K, in TA∗ .

13.7.5

Automated line identification and Baseline subtraction(Science data only). The Single Dish Pipeline employs automated line identification algorithm which identifies
candidate emission lines having a brightness above a certain threshold, and masks them. Then a low-orderbaseline is estimated and subtracted.

13.7.6RMS Flagging(Science data only). During the RMS flagging step, suspect data are flagged by outlier of RMS, by remarkably
large RMS (relative to the expectation computed for the appropriate Tsys), and by rapid increase of RMS
values.

13.7.7

Applying Kelvin-to-Jansky factors(Science data only). The current strategy to obtain Kelvin-to-Jansky factors demands an observation of bright
amplitude calibrator for each day the science targets are observed, and for each spectral window. After thecalibrator source is imaged (as described in the following step), the measured brightness temperature (in K,
TA∗ ), can be compared to expected flux density (in Jy), and a Kelvin-to-Jansky factor conversion can be derived,
relevant to each science observation, each day.
Since the factor is applied just before imaging of science targets, the Pipeline products (science targets) havea unit of Jy, while the pipeline processing product for the amplitude calibrators are always in Kelvin.

13.7.8

Imaging(Both Calibrator and Science data). The next step produces a data cube (image fits file) for each spectral
window per field. Aggregate continuum images will not be computed for the spectral line map.
Amplitude calibrator (continuum) images will be created inside the Pipeline only for the purpose of deriving
the Kelvin-to-Jansky factor.

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CHAPTER 13. PIPELINE PROCESSING

13.7.9

Exporting the products(Both Calibrator and Science data). The final step is to export the image cube defined in the pipeline context tothe 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 science target source image• a tar file per MS containing caltables for the MS• a tar file containing the file web log, a text file containing the final list of CASA commands• a python script that can be used to calibrate the data
• a text file containing the Kelvin-to-Jansky factors
No amplitude calibrator image shall be included in the data products. Instead, containing the Kelvin-toJansky factors will be delivered to the PIs.

Chapter 14

Data Archiving
14.1

Introduction

The ALMA Archive stores the observed raw data and metadata as well as the reduced data products and their
metadata resulting of the QA2 processing. These data and metadata are made available to PIs and archival
researchers for querying and download following ALMA’s data access policy. In the future, VO services will be
provided.

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 the 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 twice the average data rate. Currently proposals will not
be rejected on grounds of large data rates and the justification is only required to ensure that a configuration
yielding a less demanding data-rate and data-volume is scientifically not an option. In future cycles, however,it might be that data rate considerations play a larger role.
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
where the data and pipeline products are distributed to the three ALMA Regional Centers (ARCs) in North
America, Europe and Japan. 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 within a few seconds, transfer of bulk data cantake longer (up to several hours), depending on the amount of data to transfer to the individual ARC.
The ARCs hold copies of the entire ALMA archive for backup, user support and data distribution to the
ALMA PIs and archival researchers. The three ARCs provide a completely identical user experience to theircommunities and a user can download data from any ARC.
The ALMA archive consists of two parts - the ALMA frontend archive (hereafter AFA), which is used
for storing all data and metadata of the observations and observing projects, and the ALMA Science Archive(hereafter ASA), which stores a subset of the science metadata in a relational database to enable fast science
queries and VO access. The architecture is based on the Next Generation Archive System (NGAS) with Oracle

155

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CHAPTER 14. DATA ARCHIVING

technology for replicating the metadata (see Figure 14.1).

Figure 14.1: Archive design (frontend & backend) at the OSF to store metadata and raw and monitor data.
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 includes 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 Delivery 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 havebeen replicated to the users’ home ARC, PIs will receive a email notification containing a link to their data, andsupporting 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. Extensionsof the proprietary period can be granted under certain circumstances. When a Group OUS consisting of several
Member OUSs is processed (for example, a combined TP, 7-m and 12-m Array observation), the Group OUS
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 datadelegation service is available so that PIs do not have to give away their Science Portal password to anyone.
Instead PIs can give access rights to the data of a project to any registered ALMA user. To do so, PIs need to157

14.4. ARCHIVE QUERY

log 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 can 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 for 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.

159

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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 3 have both 12 meter and 7 meter diameters, with the receivers mounted
at the secondary (Cassegrain) focus. The 12 m dishes have a focal length of 4.8 meters, but the distance from thesecondary focus to the plane of the subreflector of the 12 m antennas is 6000 mm, giving an effective focal ratio
f/8, with an effective secondary focal length of 96 m and a plate scale of 2.15/arcsec per mm. The subreflector
has a diameter of 750 mm. The 7 m dishes have a focal length, to the primary focus, of 2.572 meters. Given an
effective focal ratio f/8, an effective secondary focal length is 56 m. The subreflector has a diameter of 457 mm.
The main reflectors of the ALMA 12 m and 7 m antennas are composed of individual panels. The size andnumber of panels varies between the different types of antennas:
VertexRSI: 264 panels spanning 8 rings with 12 (rings 1 and 2), 24 (rings 3 and 4), and 48 (rings 5 through8) individual panels which are roughly a half-meter-square in area.
AEM: 120 panels spanning 5 rings with 8 (ring 1), 16 (ring 2), and 32 (rings 3 through 5) individual panels
which are roughly one-meter-square in area.
Melco 12 m: 205 panels spanning 7 rings with 5 (ring 1), 20 (rings 2 and 3), and 40 (rings 4 through 7)
individual panels which are roughly one-meter-square in area.
Melco 7 m: 88 panels spanning 5 rings with 4 (ring 1), 12 (ring 2), and 24 (rings 3 through 5) panels which
are each roughly one-meter-square in area.

Figure A.1: The four different ALMA Antenna designs: Vertex 12 m, MELCO 12 m, AEM 12 m, and MELCO
7 m (from left to right).
Each panel has up to 5 adjustment screws, which can be used to optimize the surface accuracy of theindividual antennas (based on holographic measurements). The surface of the panels are etched to scatter
optical and near infrared solar radiation.
The antennas are equipped with a movable aluminum 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, aluminum, 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

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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

163

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 cryostat containing individual cold cartridge assemblies(CCA) with mixers and LO injection for each band, along with room temperature electronics for the IF and
LO for each band (the warm cartridge assembly, WCA) and fore-optics and entrance windows for each band.
1 http://www.almaobservatory.org/en/about-alma/how-does-alma-work/technology/transporters

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

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

A.4. CRYOSTAT

165

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

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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
3). 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)

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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 3.

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 watervapor 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

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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/

171

172

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

173

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

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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

175

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

176

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

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177

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.

178

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/IF179

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 6.5.1). 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.

180

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

181

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 3.

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

182

APPENDIX B. THE LO AND IF SYSTEM

Appendix C

Calibration Source Selection
C.1

Antenna-based Sensitivity Determinations

The proper selection of two calibrator types is critical to the success of the scientific experiment: the bandpass
calibrator to determine the relative frequency dependence of amplitude and phase during the experiment, andthe phase calibrator to determine the temporal variations of the amplitude and phase over the experiment.
An experiment will be defined here as one scheduling block or a series of consecutive scheduling blocks thatare tied together using scan sequencing. Some scientific experiments may span several configurations and eachshould be treated an separate experiments in determining appropriate calibrators, although the choice may
overlap.
The main criterion of the calibrator selection is that their correlated visibility amplitudes over all baselines issufficiently strong in order to obtain the specified signal-to-noise for the to determine of the frequency spectrum
and temporal variations during the experiment. Other calibration types, like determining the flux scale of theobservations and the polarization leakage, are described elsewhere.

C.1.1

ALMA Sensitivities

The present ALMA sensitivity must be known in order to choose the calibrators. These sensitivities are presently
determine from an ascii table that contains the nominal ALMA sensitivity as a function of frequency. It was
obtained from the ALMA Sensitivity Calculator by running it many times. A partial list of the table is show
in Table C.1.
For example, if the experiment frequency is 345 GHz, then the ALMA sensitivity in terms of an image RMS
made from 60-sec of integration over a 7.5-GHz bandwidth (all four TDM spectral windows) is 0.28 mJy, theaverage of the 340 and 350 GHz rows. The nominal Tsys is used and an assumption of a typical Water Vapor
column in the line of site. To be conservative, the RMS value should be taken from the least sensitive of the
SPW frequencies in the experiment.
New observing band data will be added as needed, and in the future these data will be down-loaded from asystem file; but for the present this sensitivity file is made by hand.

C.1.2

Calibration Parameters and Derived Antenna-based RMS

The calibration parameters, adopted in 2011 but subject to change, are as follows. The relevant SNR given are
for an antenna determination.
• Phase calibration minimum SNR (over entire BW): 15.0

183

184

APPENDIX C. CALIBRATION SOURCE SELECTIONSENSITIVITIES FOR 32 12-m antennas
DUAL POLARIZATION, TOTAL BW = 7.5 GHz
INTEGRATION TIME 60.0 sec
RMS in mJy
FQ
RMS TSYS WVR TSKY
280.0 0.194 133.0
1.27
26.3
300.0 0.212 144.0
1.27
32.2
310.0 0.234 157.0
1.27
39.7
320.0 0.480 319.3
1.26
98.5
325.0 16.57 9999.9 1.26
249.0
330.0 0.404 267.4
1.26
84.9
340.0 0.273 179.5
1.26
50.7
350.0 0.291 188.6
1.26
55.3
360.0 0.362 234.3
1.26
73.2
367.0 0.719 462.0
1.26
128.0
372.0 1.19
760.0
1.26
166.0
Table C.1: Table showing ALMA examples of sensitivities as function of frequency.
• Maximum phase calibration scan length: 2.0 minutes• Maximum phase calibration separation from target: 15.0◦• Bandpass Cal/chan minimum SNR: 50.0
• Maximum bandpass calibration scan length: 10.0 minutes• Maximum bandpass calibration separation from target 50.0◦
The phase calibration SNR is equivalent to an antenna solution rms accuracy over the scan of 4% in phaseand 2% in amplitude. The maximum scan length is chosen so that the phase calibrator observing time issignificantly less than that for the calibrator with normal phase referencing. Because of short-term pseudorandom tropospheric phase fluctuations and longer term systematic phases differences between the target andcalibrator, a calibrator measurement with high SNR is not useful.
The bandpass calibration SNR is equivalent to a channel rms accuracy of 1◦ in phase and 0.5% in amplitude.
Any variation of the normalized bandpass with time can only be determined using multiple bandpass calibrationscans. At present, one bandpass calibrator is observed for each experiment (observing block) which is rarely
longer than 90 min, hence the limit of a 10 minutes scan seems reasonable. The effect of temporal troposphericphase fluctuations can be removed from the bandpass determination.

C.2

Choosing the Calibrators

The image sensitivity for the experimental parameters can be obtained from the above sensitivity table, scaledby the square-root of the appropriate bandwidth and integration time. The conversion of the image sensitivity
Simage to antenna-based sensitivities Sant also depends on the number of antenna, Nant , and is given by Equation
C.1
Sant = Simage (Nant − 3)0.5
(C.1)

C.2.1

The Phase Calibrator

From the experiment frequency, ALMA sensitivities, the number of antennas, the total bandwidth, and the
maximum scan length, the minimum flux density for a phase calibrator can be determined. Two minimum flux
densities are determined: (1) The entire observing bandwidth and both polarizations can often be combined

185

C.2. CHOOSING THE CALIBRATORS

BAND
3
4
6
7
8
9

Frequency (GHz)
100
145
230
345
405
690

Assumed Tsys (K)
80
89
95
151
280
877

Assumed Pwv (mm)
5.2
2.7
1.26
0.91
0.66
0.47

Flux Density (mJy)
5.5
6.3
6.9
11.9
23.0
101.7

Table C.2: The minimum phase calibrator flux density in mJy need for an antenna-based phase determination(see Eq. C.1) with 4 deg rms (15 SNR) with a 2 min integration time, assuming 37 antennas. The total
bandwidth in both polarizations of 7.5 GHz is assumed.
coherently using the bandpass calibrator scan, and one amplitude and phase solution per antenna per scan canbe obtained. (2) An amplitude and phase solution is determined√for each SPW and polarization per scan. With
four SPWs and two polarizations, this minimum flux density is 8 larger than the full bandwidth solution. The
full bandwidth solutions are often made at the highest frequencies in order to find calibrators that are relatively
close to the target.
The ALMA cataloged is then searched for all unresolved or nearly unresolved calibrators that are less than15◦ from the target or the centroid position for a group of targets that are above the minimum flux density of theseparate SPW case and the full bandwidth coherence case. The relative goodness of the calibrators is determined
from: (1) the angular separation of the calibrator from the target; (2) the accuracy of the estimated flux density
at the experiment frequency that is derived from date, frequency and error estimate of the ALMA catalog
entries. The most important consideration is that the estimated flux density, with all realistic
uncertainties, must not go much below the threshold needed for successful phase calibration. The
algorithms now being used are undergoing review.
Examples of minimum phase calibration flux densities for some ALMA bands are given in the following
table. They assume an integration time of 2 minutes and a bandwidth of 2 GHz, one polarization. The flux
limit decreases by a factor 2.8 if 8 GHz in both polarizations are first coherently combined. These values assume
the use of 32 12-m antennas.
The calibrator-target separation is the most important consideration in the choice of phase calibrator. The
use of a strong calibrator that is significantly further from the target than a weak calibrator that does satisfy
the minimum SNR consideration, is not recommended. However, weak phase calibrators near the minimum
threshold should be avoided if there estimated flux density errors are large. For this reason, the more conservative minimum flux density (needed for solutions for each SPW and polarization) is often used, but with the
expectation of combining coherently all of the bandwidth if needed. Another reason for using the more conservative limit, is that the phase calibrator will be sufficiently strong for accurate pointing observations during theexperiment.
The paucity of recent observations at a frequency at or above 300 GHz is a major concern. Since very
few calibrator observations over these frequencies have been measured, their estimated flux density at higher
frequencies can only be estimated by extrapolating a lower frequency blues using a radio spectrum with aspectrum of the form ν −0.7 . This can introduce a further error of up to 50%.
With all of the above considerations, the best calibrator is chosen for the experiment. The calibration queriesalso list the next four calibrator possibilities. For strong calibrators, the maximum phase calibration scan length
can be significantly less than 2 min; however it is always more than 30 sec.

C.2.2

The Bandpass Calibrator

Although the same strategy in picking the phase calibrator was originally used to determine the bandpass calibrator, a more simpler scheme is now used. Forty-four bright, compact quasars are now monitored periodicallyand are tied to solar system objects with accurately known absolute flux density models, with ALMA at Bands
3 and 7. All are sufficiently bright to be used as bandpass calibrators (with a caveat given below). In addition,

186

APPENDIX C. CALIBRATION SOURCE SELECTION

many have sufficiently stable flux densities than can be followed to about 5 to 10% between frequencies 90 GHz
to 400 GHz, and can be used as secondary flux density standards for an ALMA experiment. Nevertheless, somesources can vary by a factor of three in a month or less (egs. 3c454.3 in 2012), but the monitoring will be
sufficiently frequent to remove such variables from consideration as soon as possible.
Source name
J0106–405
J0132–169
J0237+288
J0238+166
3c84
J0334–401
J0423–013
J0510+180
J0519–454
J0927+390
J1037–295
J1058+015
J1107–448
J1130–148
J1146+399
J1147–6753
J1159+292
3C273
3C279
J1337–129
J1426+364
J1427–421
J1517–243
J1550+054
J1613–586
3C345
J1733–130
J1751+096
J1800+388
J1924–292
J2025+337
J2056–472
J2148+069
J2157–694
J2202+422
J2232+117
3C454.3
J2258–279
J2357–5311

R.A.
01:07:24.60
01:33:25.19
02:38:43.07
02:39:26.44
03:20:44.96
03:34:44.61
04:23:58.75
05:10:51.43
05:20:13.94
09:27:53.63
10:37:54.09
10:59:11.37
11:07:46.03
11:30:48.11
11:47:40.03
11:48:11.56
12:00:13.03
12:29:48.23
12:56:53.33
13:38:23.37
14:27:10.27
14:28:48.32
15:18:30.37
15:51:15.97
16:18:27.85
16:43:26.41
17:33:49.77
17:52:12.51
18:00:52.70
19:25:44.10
20:25:44.79
20:57:14.66
21:48:48.21
21:58:16.56
22:03:19.72
22:33:19.12
22:54:40.47
22:58:52.60
23:58:37.84

Dec.
–40:29:44.3–16:50:24.3+28:51:41.4+16:40:34.2+41:33:32.8–40:05:28.7–01:18:36.3+18:01:37.3–45:45:42.7+38:58:36.4–29:38:16.5+01:29:35.7–44:53:32.7–14:53:56.9+39:54:00.9–67:58:17.6+29:10:11.8+01:58:40.6–05:51:43.3–13:01:30.2+36:21:43.0–42:10:00.2–24:25:14.5+05:24:56.4–58:50:12.9+39:47:28.9–13:05:11.8+09:39:08.5+38:48:56.1–29:12:43.9+33:46:06.1–47:11:32.4+07:01:46.0–69:37:25.6+42:20:58.8+11:48:22.1+16:13:32.5–27:53:45.1–53:06:29.1

B3 flux (Jy)
0.66
1.29
1.83
0.91
15.50
0.97
3.46
3.63
1.75
4.74
0.69
1.68
1.47
1.30
0.99
1.04
0.73
7.14
18.54
5.93
0.34
7.49
1.68
1.05
1.40
3.00
2.39
2.73
0.18
4.83
2.16
0.96
2.39
1.29
8.91
2.03
3.21
1.48
1.10

B6 flux (Jy)
0.30
0.89
1.59
0.96
10.21
0.98
3.60
2.09
1.18
3.31
0.83
1.58
0.75
0.78
0.57
0.58
1.20
2.95
13.07
4.14
0.17
3.93
1.29
0.59
1.17
1.68
1.66
2.25
0.06
3.97
1.05
0.99
1.01
0.88
2.72
4.89
2.47
3.25
0.78

B7 flux (Jy)
0.22
0.78
0.78
0.63
6.57
0.34
1.44
2.18
1.01
1.73
0.54
0.80
0.65
0.49
0.39
0.70
0.45
2.22
6.30
2.54
0.15
4.10
0.82
0.38
0.54
1.16
0.91
1.28
0.11
1.98
0.93
0.41
0.63
—
3.15
0.89
1.72
0.51
0.43

Table C.3: ALMA bandpass calibrator sources and their representative fluxes. Data downloaded on Sept 19,
2013.
The present list of bandpass sources is shown in Table C.3. Some changes will be made for extremely variable
sources or by the addition of sources that have become strong at Bands 7 and 9.
The density of these sources in the sky is sufficiently large so that at least one will be within 40◦ of any
target, and generally the brightest one that is not below elevation 30◦ during the experiment will be chosen.
[Note: the elevation limit at the beginning of Cycle 1 will be 57◦ to avoid shadowing with the most comparedC.2. CHOOSING THE CALIBRATORS

187

ALMA and Morita arrays.]
The channel to channel bandpass sensitivity for FDM mode with 3840 channels in a spectral window,
especially at frequencies above 300 GHz, cannot reach the 50:1 SNR per channel unless one of the few very
bright quasars is near the target. Since the instrumental frequency variations between consecutive channels areless than about 1is no need to determine the bandpass calibration for each channel. However, the number ofchannels that can be averaged and still meet the 50:1 SNR specification is under investigation. Presently, 64
channels are averaged in order to find the bandpass calibrator that can meet the 50:1 SNR. If none of the above
calibrators meets this level, the best one is chosen.

C.2.3

Other Calibrator Types

Absolute Flux density Calibration: An experiment will contain either a solar system object and/or a
bandpass calibrator with a flux density, extrapolated from ALMA monitoring data, to the experiment date.
Inclusion of both types are recommended if one of the eight solar system objects is available during the experiment. If extreme absolute amplitude accuracy is needed (< 3%), additional amplitude-type calibrators should
be included in the experiment.
Polarization Calibrators: The compilation of sufficiently strong calibrators that are also polarized morethan about 4% is underway. These are needed to calibrator the leakage signal between each antenna/SPW
X and Y polarization signals. Since only about 25% of the bandpass calibrators are sufficiently polarized,
additional strong sources are being checked. More information is given in the polarization chapter of thetechnical handbook.
Astrometric Calibrators: The positional expectation for a typical ALMA observation is about 10% of
the resolution, if there is sufficient SNR in the target. If higher precision is need, perhaps reaching 2% of theresolution, additional secondary phase calibrators are needed. More details will be forthcoming when ALMA
opens up to astrometric-quality proposals.
Check Sources: An accurate assessment of the quality of Band 9 observations is difficult to make. ALMA
staff can in cases like this add a check source in the experiment, a unresolved quasar with an accurate position.
This source should be at about the same angular separation from the phase calibrator as the target, although it
can be significantly weaker that the minimum phase calibrator flux density. After data editing and calibration,
an image of the check source will provide information about the calibration quality and the coherence of theobservations.

188

APPENDIX C. CALIBRATION SOURCE SELECTION

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

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APPENDIX D. ACRONYM DICTIONARY

DTX
EB
EL
EPO
ES
ESO
FDM
FE
FITS
FLOOG
FOM
FOV
FPGA
FT
FWHM
FWHP
GPS
HA
HEMT
HPBW
IF
IFP
IRAM
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
PI
PLL
PMG
PRD
PWV
QA
QA0
QA1

Data Transmitter module
Execution BlockElevation
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
Global Positioning System
Hour Angle
High Electron Mobility Transistor
Half Power Beam Width
Intermediate Frequency
Intermediate Frequency Processor
Institut de Radioastronomie Millimetrique
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
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

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

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
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