Abstract -

This reduction is used to test DopplerTrackerr_haystack patch using Todd Hunter's SMA swarm data set 190314_11:50:03 of SMA project: 2019?-S??? with archived information:

PI                 - Todd Hunter
Target             - g358.93-0.03
RA (J2000)         - 17:43:10.05
Dec (J2000)        - −29:51:46.1
LO Freq (GHz)      - 298.4 (A), 210.9 (B) (A: 340 rx , B: 240 rx)
N-bsln             - 28(A), 28(B)
Angular resolution - 0.40"(B), 0.56"(B)
Time               - 208 min

Calibrators & targets -

T1:     G358.93-0.03
BP:     3c279
FL/BP2: Callisto
CG1:    1744-312
CG2:    1256-057
CG3:    1733-130
CG4:    1700-261
CG5:    1924-292
T2:     sgrb2n
T3:     ngc6334l 

Following the steps of calibrations described in The example of CASA reduction of SMA data after pipeline the swarm data into CASA. SMA continuum image of G358.93-0.03 at 210 GHz is constructed, in good agreement with ALMA 340 GHz image. The 1σ rms noise of the SMA continuum image at 210 GHz (one receiver data with BW=16 GHz) is 0.4-0.5 mJy/beam in an angular resolution of 0.9"x0.5".

Step 0: Pipeline SMA data to CASA and apply online corrections -
• Input SMA swarm data: 190314_11:50:03
Step 0.1: Keep daul rx data together -
• Usage of C-shell script: swarm2casa.csh with OPTIONS = 2, SEPARATE_DRX = N
• Purpose:
• convert SMA swarm data with all spectral windows into a single CASA measurementSet
• apply Tsys corrections and online error flagging
• Output of CASA measurementSet: SMA190314.ms, (pipelined file)
• C-shell log of the screen report from swarm2casa.csh
• Initially editing (flagging high amplitude spikes)

plotms field 0 spectra -


























Fig. 0_1: the 16 spectra of field 0 (3c279) from SMA190314.ms.
Step 0.2: Keep daul rx data separately (rx-based) -
• Usage of C-shell script: swarm2casa.csh with OPTIONS = 2, SEPARATE_DRX =Y
• Purpose:
• convert SMA swarm data with all spectral windows into two rx-based CASA measurementSets
• apply Tsys corrections and online error flagging
• Output of CASA measurementSets: SMA190314_rx1.ms & SMA190314_rx2.ms, (two pipelined files)
• C-shell log of the screen report from swarm2casa.csh
• Initially editing (flagging high amplitude spikes)

plotms field 0 spectra -


























Fig. 0_2: the 8 spectra of field 0 (3c279) from SMA190314_rx1.ms.





























Fig. 0_3: the 8 spectra of field 0 (3c279) from SMA190314_rx2.ms.
• Calibrations of SWARM data -
• Definition of variables for CASA-python-script modules -

############################################
#define variables for swarm data reduction #
############################################
datain   = 'SMA190314_rx2'
inttime  = 9.68   
dinttime = 20.
tinttime = 30.
qsecond  = 30.0
allspw   = '0~7'
allspw1  = '0~7:512~15871'
allspw2  = '0~7:1024~15359'
blckspw1 = '0~3:1024~15359'
blckspw2 = '4~7:1024~15359'
quadspw  = '0,2,4,6'
nchspw   = 16384
nchnew   =  1792
width0   =    1
width1   =    2
width2   =    4
width3   =    8
width4   =   16
width5   =   32
width6   =   64
width7   =  128
avgchan0 =   '1'
avgchan1 =   '2'
avgchan2 =   '4'
avgchan3 =   '8'
avgchan4 =  '16'
avgchan5 =  '32'
avgchan6 =  '64'
avgchan7 = '128'
#############################################
#user's setup below -                       #
#############################################
#
# Note for import data -                   
# the input measurementSet must be created via the swarm2casa path 
#
#prefix of swarm measurementSet -           
datain   = 'SMA190314_rx2'
#full name of swarm measurementSet -        
datainms = 'SMA190314_rx2.ms'
#number of channels to average -        
bw       = width3
#define source code -
BP =  '0'  #bandpass calibrator
BP2 = '1'  #optional bandpass calibrator
FL  = '1'  #flux density scale calibrator
CG  = '2,3,5'#complex gain calibrators
CG1 = '2'  #optional complex gain calibrator
CG2 = '3'  #optional complex gain calibrator
T1  = '4'  #primary target
CG3 = '5'  #optional complex gain calibrator
T2  = '6'  #secondary target
T3  = '7'  #secondary target
#define source name -
BPname  = '3c279'
BP2name = 'Callisto'
FLname  = 'Callisto'
CG1name = '1733-130'
CG2name = '1700-261'
CG3name = '1744-312'
CGname  = '1733-130, 1700-261, 1744-312'
T1name  = 'G358.93-0.03'
T2name  = 'sgrb2n'
T3name  = 'ngc6334l'
#define reference antenna -
rant = '5'
#

Step 1: Prepare for calibration-

CASA tasks:                              
     listobs                             
     plotants                             
     split  (not used) 

• Usage of CASA-python-script module -
• Listobs output -
Table 1: Source/Field information -

Source (Field) information reported from CASA listobs
ID	Code#	Name	RA	Decl	Epoch	SrcId	nRows
0	BP	3c279	12:56:11.165085	−05:47:21.52451	J2000	0	84672
1	FL/BP2	Callisto	17:30:06.907654	−22.37.37.71790	J2000	1	34720
2	CG1	1733-130	17:33:02.702637	−13.04.49.54811	J2000	2	46144
3	CG2/CG	1700-261	17:00:53.153229	−26.10.51.72272	J2000	3	99232
4	T1	G358.93-0.03	17:43:10.047455	−29.51.46.13022	J2000	4	289632
5	CG3/CG	1744-312	17:44:23.580322	−31.16.35.98618	J2000	5	47488
6	T2	sgrb2n	17:47:19.876556	−28.22.18.38196	J2000	6	7168
7	T3	ngc6334l	17:20:53.423309	−35.46.57.89703	J2000	7	8288

________________
*Check listobs_log for the issue of source ID and spw mix-up
^#Note for Code:
BP - bandpass
CG - complex gain
T1 - Target source
T2 - Secondary target source for examing calibration
T3 - Secondary target source for examing calibration
FL - Flux density scale calibrator
^$ BP2 = FL - Callisto is an option to be used to solve for bandpass

Table 2: Correlator/Frequency configuration, original -

Spectral Windows: (16 unique spectral windows and 1 unique polarization setups)
SpwID	Name	#Chans	Frame	Ch0(MHz)	ChanWid(kHz)	TotBW(kHz)	CtrFreq(MHz)	Corrs
0	none	16384	LSRK	207034.258	-139.648	2288000.0	205890.3274	XX
1	none	16384	LSRK	202735.106	139.648	2288000.0	203879.0364	XX
2	none	16384	LSRK	203034.787	-139.648	2288000.0	201890.8570	XX
3	none	16384	LSRK	198735.635	139.648	2288000.0	199879.5656	XX
4	none	16384	LSRK	214733.518	139.648	2288000.0	215877.4487	XX
5	none	16384	LSRK	219032.670	-139.648	2288000.0	217888.7400	XX
6	none	16384	LSRK	218732.989	139.648	2288000.0	219876.9191	XX
7	none	16384	LSRK	223032.139	-139.648	2288000.0	221888.2091	XX

• Plot antenna array -


































Fig. 1: Antenna array. Click the figure for enlargement.
• Split & bin data -
• Listobs output (binned data) -^@
_____________________________________
^@Note: the original spectral data are binned with bw = width3, or vector-averaging 8 channels to produce a new channel width of 1.117188 MHz, which provides an adequate velocity resolution (1 km/s) for this project.
Step 2: Inspecting and editing data -

CASA tasks:                               
plotms

• Usage of CASA-python-script module -
• Plot uv-coverage -







































Fig. 2: uv-coverage (spw 0,4,8,12) (all fields). Click the figure for enlargement.
• Plot elevation coverage -

































Fig. 3: Elevation coverage including all field (0~5). Black: 0 BP 3c273; Red: 1 FL Collisto; Orange: 2 CG1 1733-130; Green: 3 CG2 1700-261; Brown: 4 T1 G358.93-0.03; Blue: 5 T2 sgrb2n; Purple: 6 T3 ngc6334l. Click the figure for enlargement.
• Plot fringe amplitude vs time -




















Fig. 4: Fringe amplitude vs time after flagging a few high-amplitude spikes in the inspect&editing cycle (pre-calibration). Black: 0 BP 3c273; Red: 1 FL Collisto; Orange: 2 CG1 1733-130; Green: 3 CG2 1700-261; Brown: 4 T1 G358.93-0.03; Blue: 5 T2 sgrb2n; Purple: 6 T3 ngc6334l. Click the figure for enlargement.
Step 3: Set flux density scale -

CASA tasks:
setjy 

• Usage of CASA-python-script module -
Note: FL is Neptune that is used to set the flux-density scale with the model standard: Butler-JPL-Horizons 2012
• Setjy output -
Table 3: Results of setjy -

FL is Callisto that is used to set the flux-density scale with the model standard: Butler-JPL-Horizons 2012
Reference source	Specral window	Flux density	Frequency
Callisto:	spw0	Flux:[I=4.2679,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 207.03GHz
Callisto:	spw1	Flux:[I=4.0877,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 202.74GHz
Callisto:	spw2	Flux:[I=4.1002,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 203.03GHz
Callisto:	spw3	Flux:[I=3.9241,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 198.74GHz
Callisto:	spw4	Flux:[I=4.6005,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 214.73GHz
Callisto:	spw5	Flux:[I=4.7912,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 219.03GHz
Callisto:	spw6	Flux:[I=4.7778,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 218.73GHz
Callisto:	spw7	Flux:[I=4.9717,Q=0.0,U=0.0,V=0.0] +/- [I=0.0,Q=0.0,U=0.0,V=0.0] Jy	@ 223.03GHz
Step 4: Solve for delay & bandpass -

CASA tasks:
     plotms
     gaincal
     bandpass
     plotcal

• Usage of CASA-python-script module -
• Note: using the BP (3c279) to solve for delay.
• Plot delay corrections -
























Fig. 5: Antenna-based delay as function of time. The remaining delay shows a typical value of a few tens pico seconds, quite small. Click the figure for enlargement.
• Note: two options of solving for bandpass
• Option 1: 3c279 as defined early as a variable BP -
• Option 2: Callisto is weaker. (BP2) -
• Plot bandpass phase correction -
























Fig. 6: Antenna-based phase soultions as function of time solvd for BP, which needs to be applied to the data while solving for bandpass. Click the figure for enlargement.
OPTION 1 -
• Plot bandpass amplitude-





























Fig. 7: Antenna-based bandpass solutions (amplitude) for option 1 (BP=3c84), solved with averaging every 16 channels. Top panel for antennas 1~4; bottom panel for antenna 5~8. Click the figure for enlargement.
• Plot bandpass phase-





























Fig. 8: Antenna-based bandpass solutions (phase) for option 1 (BP=3c84), solved with averaging every 16 channels. Top panel for antennas 1~4; bottom panel for antenna 5~8. Click the figure for enlargement.
OPTION 2 -
• Plot bandpass amplitude-



























Fig. 9: Antenna-based bandpass solutions (amplitude) for option 2 (BP2=Neptune), solved with each channel. Top panel for antennas 1~4; bottom panel for antenna 5~8. Click the figure for enlargement.
• Plot bandpass phase-



























Fig. 10: Antenna-based bandpass solutions (phase) for option 1 (BP2=Neptune), solved with each channel. Top panel for antennas 1~4; bottom panel for antenna 5~8. Click the figure for enlargement.
Step 5: Apply the delay and bandpass solution to the BP, CG, FL data -

CASA tasks:
     applycal
     plotms

• Usage of CASA-python-script module -
• Note: edting the data before next step
Step 6: Solve for complex gains -

CASA tasks:
     gaincal
     plotcal

• Usage of CASA-python-script module:
• Note: solving for complex gains for the calibrators FL, BP and CG prior to bootstrape the flux-density scale
• Plot phase solutions in integration-





























Fig. 11. Antenna-based phase solutions (integration) for the calibrators FL, BP and CG. Click the figure for enlargement.
• Plot phase solutions in scan-




























Fig. 12. Antenna-based phase solutions (scan) for the calibrators FL, BP and CG. Click the figure for enlargement.
Step 7: Bootstrap flux-density scale from a reference source (FLname: Neptune) -

CASA tasks:
     fluxscale

• Usage of CASA-python-script module:
• Note: Report from CASA bootstraping
Table 4: A summary of flux density bootstraping -

Statistics of flux-density from the 16 spws
Calibrators	Flux density and 1 σ uncertainty (Jy)	Spectral index and 1 σ uncertainty	Frequency(GHz)
3c279	8.07928 +/- 0.617503	−0.542301 +/- 1.53944	210.73
1733-130	1.62645 +/- 0.00275459	−0.602464 +/- 0.0435007	210.73
1700-261	1.12312 +/- 0.00309053	−0.310968 +/- 0.0722647	210.73
1744-312	0.277765 +/- 0.00452225	−0.673763 +/- 0.434288	210.73
Step 8: Apply calibration solutions to the data -

CASA tasks:
     applycal 

• Usage of CASA-python-script module:
• Note: apply the calibrations to all the calibrators and target sources interested:
• 3c279 (BP),
• 1733-130 (CG1),
• 1700-261 (CG2),
• 1744-312 (CG3),
• Callisto (FL),
• G358.93-0.03 (T1), primary target
• sgrb2n (T2), secondary target
Step 9: Examine and edit calibrated data -

CASA tasks:
     plotms

• Usage of CASA-python-script module:
• Plot vis structure -
• BP(3c279) -




















































Fig. 13 Vis structure of bandpass calibrator (3c279). Top: amplitude. Bottom: phase. Click the figure for enlargement.
• FL(Callisto) -






















































Fig. 14. UV structure of the Flux-density calibrator (Callisto), amplitude (top) and phase (bottom). Click the figure for enlargement.
• CG1(1733-130) -
















































Fig. 15. Spetrum of the Complex gain calibrator1 (1733-130 (NRAO530)), amplitude (top) and phase (bottom). Click the figure for enlargement.
• CG2(1700-261) -





















































Fig. 16. UV structure of the Complex gain calibrator2 (1700-321 ( the main gain calinrator)), amplitude (top) and phase (bottom). Click the figure for enlargement.
• CG3(1744-312) -



















































Fig. 17. UV structure of calibrator3 (1744-312) after applying the corrections, amplitude (top) and phase(bottom). Click the figure for enlargement.
• T1(G358.93-0.03) -






















































Fig. 18. UV structure of the target source (G358.93-0.03). Click the figure for enlargement.
Step 10: Split calibrated multi-source into single-source data for continuum and CH2OH lines -

CASA tasks:
     split

• Usage of CASA-python-script module -
Step 11: Examine the calibrated data with imaging -

CASA tasks:
     clean (tclean)
     viewer

• Usage of CASA-python-script module:
• Image calibrators and the secondary target (continuum emission) -
Table 4: Images -

Examination of the calibrated data by making images with Brigg's weight (R=2) or nature weight
3c279 (BP)	Callisto (FL)	1733-130 (CG1)	1700-261 (CG2)	1744-312 (CG3)	G358.93-0.03 (T1)
Sp = 8.505 Jy/beam, rms = 20 mJy/beam, contours=Sp x (-0.025, 0.025, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8)	Sp = 1.428 Jy/beam, rms = 2 mJy/beam, contours=Sp x (-0.01, 0.01, 0.025, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8, 0.9)	Sp = 1.633 Jy/beam, rms = 0.8 mJy/beam, contours=Sp x (-0.002, 0.002, 0.005, 0.01, 0.025, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8)	Sp=1.144 Jy/beam, rms = 0.5 mJy/beam, contours=Sp x (-0.002, 0.002, 0.005, 0.01, 0.025, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8)	Sp=0.293 Jy/beam, rms = 1.0 mJy/beam, contours=Sp x (-0.01, 0.01, 0.025, 0.05, 0.1, 0.2, 0.4, 0.6, 0.8)	Sp=0.0897 Jy/beam, rms = 0.5 mJy/beam, contours=Sp x (-0.02, 0.02, 0.03, 0.04, 0.06, 0.08, 0.1, 0.12, 0.14, 0.16, 0.18, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9)

Note: The images are made with weight R=2; the synthesized beam is 0.9"x0.5". Click an image for enlargement.

Imaging calibrated SWARM data -

Step 12: Image continuum data -

CASA tasks:
     plotms
     clean (tclean)
     viewer

• Usage of CASA-python-script module:
• Image Callisto brightness distribution -

































Fig. 19: Image of Callisto at 210.88 GHz by synthesizing 8 x 2GHz spws with weight R=-0.5. Sp=0.835 Jy/beam, St=5.174 Jy, rms =3.6 mJy/beam; A circular beam with FWHM = 0.4" was used to convolve the clean components for the final image.


• Image G358.93-0.03 (T1) continuum emission -





















Fig. 20. SMA image of G358.93-0.03 at 210 GHz with Brigg's weight R=0 (left) and R=2 (right). Left: The peak intensity and rms noise of R=0 weight image are 79.4 mJy/beam and 0.6 mJy/beam, and FWHM beam is 0.72"x0.40" (15deg). Right: The peak intensity and rms noise of R=2 weight image are 89.7 mJy/beam and 0.45 mJy/beam, and FWHM beam is 0.91"x0.52" (5deg).


• Compare with ALMA 340 GHz image (Brogan et al 2019)
Fig. 21: ALMA 340 GHz (band 7) continuum image of G358.93-0.03 at an angular resolution of 0.46" x 0.42", cut-pasted from original Fig. 1 (right) of Brogan et al. 2019. Contours are 3.5 (?) mJy/beam (1σ) x ( 8, 12, 24, 48, 72, 96, 144, 240, 336); .... The ALMA continuum components M1, M2, M3, M4, M6, M7, M8 appear to be detected with the SMA at 210 GHz; M5 and its surrounding extension appear to be not as strong as them in ALMA 340 GHz image.
rms of 3.5 (?) mJy/beam (1σ) for ALMA band 7 image appears to be too high. Probably is a typo. According to SMA 210 GHz continuum image, this number more likely 0.35 mJy/beam. SMA's sensitivity of 0.45 mJy/beam at 210 GHz is close to ALMA band 7's sensitivity !? Needs double check.


Step 13: Identify spectral lines and construction image cubes -

CASA tasks:
     clean (tclean)
     viewer
     ...

• Usage of CASA-python-script module -
• Image Callisto brightness distribution -






















































































Fig. 22: CH3OH maser lines are identified for the three strong components near 200 GHz (top three panels) which are listed in Table 3 of Brogan et al 2019 (Bottom). The spectra of these maser lines are also plotted in Fig. 1 of Brogan et al 2019 (see left of Fig. 21 above).


Step 14: Combine different array data -

CASA tasks:
     ...

• Usage of CASA-python-script module:
Skip this step for this example.
Step 15: Convert CASA images to FITS -

CASA tasks:
     ...

• Usage of CASA-python-script module: