Observing Scripts
Basic Reduction
Scott Schnee (NRAO)
25 – April - 2014
Atacama Large Millimeter/submillimeter Array
Expanded Very Large Array
Robert C. Byrd Green Bank Telescope
Very Long Baseline Array
The General Idea:
Amplitudes and Phases
Imax - Imin Fringe Amplitude
V =
=
Imax + Imin
Average Intensity
b1
The visibility is a complex
quantity:
=/b
- amplitude tells “how much” of a
certain frequency component
- phase tells “where” this component is
located
phase
ALMA Data Workshop – Dec 1st, 2011
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The General Idea:
Amplitudes and Phases
• Each pair of antennas will generate a visibility
(amplitude and phase)
– Every integration: time interval
– Every channel: frequency interval
• Goal of calibration is to correct these amplitudes and
phases for atmospheric and instrumental effects
• Phase corrections are additive
• Amplitude corrections are multiplicative
• Measurements are baseline-based, but corrections
are antenna-based (usually)
ALMA Data Workshop – Dec 1st, 2011
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The General Idea:
Corrupted Data
• Variations in the amount of precipitable water vapor (PWV)
cause phase fluctuations and result in
– Low coherence (loss of sensitivity)
– Radio “seeing”, typically 1 at 1 mm
– Anomalous pointing offsets
– Anomalous delay offsets
Patches of air with different water
vapor content (and hence index of
refraction) affect the incoming wave
front differently.
ALMA Data Workshop – Dec 1st, 2011
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The General Idea:
Corrupted Data
• The atmosphere can absorb/emit significantly at (sub)millimeter
wavelengths, creating phase and amplitude variations that need
to be removed from measurement sets
• The antennas and other parts of the array also introduce noise
into data sets
ALMA Data Workshop – Dec 1st, 2011
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The General Idea:
Calibration
• Basic calibration involves observing “calibrators” of known
brightness and morphology
• Quasars (bright point sources)
• Solar system objects (well-characterized, so easily modeled)
• Determine corrections that make the observations fit the
model
• Derive the changes to amplitude and phase (complex gain)
vs frequency and time
• Apply the corrections from the calibration data to the science
target data
• Interpolating the derived calibration solutions
ALMA Data Workshop – Dec 1st, 2011
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What Goes into ALMA Observations?
Time
Source
Intent
09:29:29.5 - 09:30:26.3
J1107-4449
CALIBRATE_POINTING
09:32:26.9 - 09:32:43.3
J1107-4449
CALIBRATE_ATMOSPHERE
09:32:51.1 - 09:38:07.5
J1107-4449
CALIBRATE_BANDPASS
09:38:48.2 - 09:39:45.6
J1058-8003
CALIBRATE_POINTING
09:41:09.9 - 09:41:26.1
Mars
CALIBRATE_ATMOSPHERE
09:41:34.1 - 09:44:11.9
Mars
CALIBRATE_AMPLI
09:44:55.7 - 09:45:11.5
J1058-8003
CALIBRATE_ATMOSPHERE
09:45:13.0 - 09:45:43.8
J1058-8003
CALIBRATE_PHASE
09:47:24.3 - 09:54:16.6
Science Targets
09:54:25.9 - 09:54:56.2
J1058-8003
Repeat for ~1 hour
Quasar – Science loop
CALIBRATE_PHASE
ALMA Data Workshop – Dec 1st, 2011
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How to choose calibrators
• Bandpass calibrator
• Corrects amplitude & phase vs. frequency
• Choose brightest quasar in the sky
• (Sometimes) assume that corrections are constant in time
• Amplitude calibrator
• Sets absolute flux of all other sources in observation
• Choose something bright, compact, and very well known
• Phase calibrator
• Corrects amplitude and phase vs. time
• Choose quasar that is:
• Bright enough to get reasonable signal to noise in (a
few) minutes
• As close as possible to science target
ALMA Data Workshop – Dec 1st, 2011
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Other Calibration
• Focus observations
• Done automatically by ALMA observatory
• Data not included in observations delivered to PI
• Baseline observations
• Done after antennas are moved
• Determine the x,y,z position of each antenna in the array
• Pointing observations
• Done at beginning of observations and after each large (10s
of degrees) sky slew
• For CARMA, pointing repeated every 2 – 4 hours
• WVR observation
• Removes short timescale phase fluctuations caused by water
vapor in the atmosphere
ALMA Data Workshop – Dec 1st, 2011
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ALMA WVR Correction
Two different baselines Jan 4, 2010
Data
WVR
Residual
There are 4 “channels” flanking the peak of the 183 GHz water line
•Matching data from opposite sides are averaged
•Data taken every second, and are written to the ASDM (science data file)
•The four channels allow flexibility for avoiding saturation
•Next challenges are to perfect models for relating the WVR data to the
correction for the data to reduce residual phase noise prior to performing
the traditional calibration steps.
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ALMA WVR Correction
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First Look at Your Data
• In CASA: listobs(vis=‘my_data.ms’)
ALMA Data Workshop – Dec 1st, 2011
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Bandpass Phase vs. Frequency (Before)
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Bandpass Phase vs. Frequency (Model)
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Bandpass Phase vs. Frequency (Solutions)
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Bandpass Phase vs. Frequency (After)
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Phasecal Phase vs. Time (Before)
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Phasecal Phase vs. Time (Model)
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Phasecal Phase vs. Time (Solutions)
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Phasecal Phase vs. Time (After)
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Ampcal Amplitude vs. uv-distance (Before)
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Ampcal Amplitude vs. uv-distance (Model)
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Ampcal Amplitude vs. uv-distance (After)
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Phasecal Amplitude vs. Time (Before)
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Phasecal Amplitude vs. Time (Model)
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Phasecal Amplitude vs. Time (Solutions)
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Phasecal Amplitude vs. Time (Solutions)
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Phasecal Amplitude vs. Time (After)
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Task Names
•
•
•
•
•
•
•
setjy – Set the model for your calibrator
gaincal – Amplitude and phase vs. time solutions
bandpass – Amplitude and phase vs. frequency solutions
fluxscale – Overall amplitude scaling
applycal – Apply solutions from gaincal, bandpass, & fluxscale
plotcal – Plot the amplitude & phase solutions
plotms – Plot the UV data (raw, model, corrected)
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