The performance of wvrgcal The 4 quasar, band 6 experiment, uid A002 X X4cd.ms
|
|
- Agatha Sherman
- 5 years ago
- Views:
Transcription
1 The performance of wvrgcal The 4 quasar, band 6 experiment, uid A002 X X4cd.ms Marcel Clemens, Astrophysics Group, Cavendish Laboratory, University of Cambridge, UK 18/9/2011 Summary This document reports on an analysis of the performance of the wvrgcal program and focuses on the effects of performing wvr correction when wvr data is not available for some antennas. This is done simply by using the wvrflag option in the call to wvrgcal. In this case the program uses wvr data from neighbouring antennas to derive a correction via interpolation. A test is also made on the effect of not using the tie option to wvrgcal. The results are quantified directly with the resulting images via both image statistics and Gaussian fits to the source using imfit. The dataset used was the quasar experiment uid A002 X X4cd.ms taken on 2011, June 13 th in band 6 (230 GHz). There were 14 antennas in the array but 5 are flagged so that the final maps contain data from only 9 (see fig. 1). Note that antenna DV01 was probably unecessarily flagged (see below). The brightest source, , was used as a calibrator for the other 3 (phase, amplitude and bandpass). There is no absolute flux calibrator in the dataset so fluxes are relative to that has an assumed flux of 1 Jy. The calibration process therefore lacks the setjy and fluxscale steps that would normally be used. Antenna DV02 was used as the reference antenna. I referred to both Ed Fomalont s script on a similar dataset and T. Sawada s report on the same dataset, but also to the casa guides on the NRAO web pages. Data reduction The script used to calibrate, image and quantify these data is given in the appendix. Here is a summary of the procedure. Antenna position corrections were applied using gencal using the corrections reported in T. Sawada s report (I did not re-derive these). s were then optionally applied. The antenna position corrections and tables were then applied ( applycal ) and the 4 science spws were split out. A priori flagging commands were then applied to the split dataset (autocorrelations, shadowing, quack and end spectral channels). A little further flagging was also applied in which the XX correlation for antenna DV01 was flagged. This effectively flags tha antenna becasue gaincal requires both polarisations in order to find a solution at present. This could be improved by flagging only spw 2 in XX. This is unlikely to change any of the conclusions reached here. A bandpass calibration table was then made using after correcting its phase variations as a function of time. Gaincal was then run on in a similar to the casa guide on TWHydra: ie. first calculate phases only for each integration time, then for each scan. Then solve also for amplitudes applying the integration time table on-the-fly for the calibrator and the scan time table on-the-fly for the other sources. Applycal was then run, to apply the bandpass, phase and amplitude calibration tables and the dataset split merging all spws and channels to create a continuum dataset for imaging. Stokes I,Q,U and V, pixel images were made with 0.25 arcsec pixels. Weighting was Briggs with robust=0, and 100 iterations of clean were used with an 18 pixel square clean box centred on the source. For every version of the script uniformly weighted maps were also made (robust = -2) in order to give more weight to long baselines. The script was run several times with different calls to wvrgcal, and also without wvrgcal, as a benchmark. The wvrgcal calls were as follows: wvrgcal not called. No flagged antennas: wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource tie , , ,
2 An antenna with close neighbours (DV06) flagged: wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource tie , wvrflag DV06 A rather isolated antenna (DV08) flagged: wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource tie , wvrflag DV08 3 flagged antennas (DV06, DV08, DV10): wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource tie , wvrflag DV06 --wvrflag DV08 --wvrflag DV10 A very central antenna (DV10) flagged: wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X2 --toffset -1 --segsource --statsource tie , , , wvrflag DV10 No flagged antennas but omittng the tie option: wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource Figures 2-8 show the results of running the script with these wvrgcal calls. For each source the colour scales and contours are identical. Analysis Imstat was used to quantify the images. The background area was a large rectangle covering a large part of the image above the source (see appendix). Imfit was used to fit Gaussians to the sources in the Stokes I images. Conclusions from this dataset The results discussed here are summarised in table 1. Applying the water vapour radiometer corrections when all antennas have wvr data is a big improvement over not applying the corrections. S/N values increase from 372, 260 and 248 to 535, 489 and 304, for fields 1,2 and 3 respectively. Image background rms was reduced by 30, 45 and 17%. The size of Gaussians fitted to the images is also always reduced (very slightly) indicating that there are fewer phase errors. The flagging of a single antenna during wvr corrections and the use of interpolation from nearby antennas to derive corrections for the flagged antenna, works extremely well if the flagged antenna has several neighbours (DV06 or DV10). It doesn t seem to be important whether this antenna is near the centre of the array or not (though the dataset is rather limited in this sense). The S/N, rms, and fitted Gaussians are virtually identical to the no flagged antenna case. If the flagged antenna has fewer, nearby neighbours (DV08) the results are still good, but some deterioration is seen over the no flagging case. Rms values are 519, 430 and 302 for fields 1,2 and 3 respectively. For 3 flagged antennas the situation changes. The S/N values are similar to the no wvr correction case. However, the minima in the images are significantly lower, and the resulting images show the effects very clearly. In this case wvrgcal degrades the resulting maps. Perhaps surprisingly, not using the tie option to wvrgcal does not seem to effect the results. At least for this dataset the images were equivalent to tie -ing all 4 sources (no antennas were flagged for this comparison). Uniformly weighting the data did not appear to change any of the trends seen between the various runs.
3 Table 1: Stokes I image properties for various applications of wvrgcal. The first column describes how wvrgcal was run: none = no wvr corrections, norm = no flagged antennas, antenna names refer to the antenna which was flagged via wvrflag. 3ant =DV06, DV08, DV10 flagged, and tie = tie option not used. Max and min refer to the whole image, rms refers to a large background area not including the source, omin is the minimum within the background area. Flux, a, b and PA refer to the Gaussian fit to the source by imfit. wvrgcal max min rms omin max/rms imfit Gaussian parameters flux a b PA none ± ± ± norm ± ± ± DV ± ± ± DV ± ± ± ant ± ± ± DV ± ± ± tie ± ± ± none ± ± ± norm ± ± ± DV ± ± ± DV ± ± ± ant ± ± ± DV ± ± ± tie ± ± ± none ± ± ± norm ± ± ± DV ± ± ± DV ± ± ± ant ± ± ± DV ± ± ± tie ± ± ± none ± ± ± norm e ± ± ± DV e ± ± ± DV e ± ± ± ant ± ± ± DV e ± ± ± tie e ± ± ±
4 Figure 1: Antenna positions. The flagged antennas, DV05, DV09, DV11 and DV13 are marked with black dots. Note that the flagged antennas still had WVR data that could be used for interpolation.
5 No Figure 2: Field 0, , used as the phase calibrator. Now wvr corrections. Colour scale (-0.003,0.1), contour level No Figure 3: Field 1, Now wvr corrections. Colour scale (-0.005,0.05), contour level
6 no flagged antennas DV06 flagged DV08 flagged DV06, DV08, DV10 flagged DV10 flagged no flagged antennas - no tie Figure 4: Field 1, with wvr corrections.
7 No Figure 5: Field 2, Now wvr corrections. Colour scale (-0.005,0.05), contour level
8 no flagged antennas DV06 flagged DV08 flagged DV06, DV08, DV10 flagged DV10 flagged no flagged antennas - no tie Figure 6: Field 2, with wvr corrections.
9 No Figure 7: Field 3, Now wvr corrections. Colour scale (-0.002,0.01), contour level
10 no flagged antennas DV06 flagged DV08 flagged DV06, DV08, DV10 flagged DV10 flagged no flagged antennas - no tie Figure 8: Field 3, with wvr corrections.
11 Appendix Script for calibration, imaging and statistics. print Starting script for 4 quasar data set reduction... print Here we apply wvr corrections and flag a more isolated antenna (DV08). #Set up some name conventions specific to this version of the script. root = wvr1 #Root name to use for all cal tables and png files. split1 = X4cd wvr1.ms #Name for new ms after initial split of science data. split2 = X4cd wvr1 split cont.ms #Name for new ms after final split that merges channels. #Cal table names become root + etc. #T sys corrections: none. scriptmode = False #Antenna position corrections. print ---- ANTENNA POSITION CORRECTIONS ---- #gencal inputs. default(gencal) vis = uid A002 X X4cd.ms caltable = antpos fix caltype = antpos antenna = DV02,DV04,DV05,DV06,DV07,DV08,DV10,DV12,DV13,PM01,PM03 parameter = [ , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ] gencal() #WVR CORRECTIONS. INCLUDE WITH VARIOUS OPTIONS. print Executing the following wvrgcal command: print "os.system(../wvrgcal/bin/wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource tie , , , wvrflag DV08 )" os.system(../wvrgcal/bin/wvrgcal --ms uid A002 X X4cd.ms --output uid A002 X X4cd.W --toffset -1 --segsource --statsource tie , , , wvrflag DV08 ) print ---- APPLY CAL FOR ANTENNA POSITIONS (AND POSSIBLY WVR) ---- #Applycal default(applycal) vis = uid A002 X X4cd.ms #gaintable = antpos fix gaintable = [ antpos fix, uid A002 X X4cd.W ] applycal() print SPLIT OUT SCIENCE DATA ----
12 #Split off science spws. default(split) vis = uid A002 X X4cd.ms output datacolumn = corrected #We have applied the antpos fix table (+wvr table perhaps). spw = 1,3,5,7 split() print ---- SAVE ORIGINAL FLAG TABLE ---- #Save original flag table. default(flagmanager) #(Output name from split above) mode = save versionname = Original comment = Right after split. flagmanager() print ---- A PRIORI FLAGGING ---- #A priori flagging. Use flagmanager to back up. print...autocorrelations #Autocorrelations default(flagautocorr) flagautocorr() print...shadowing #Shadowing (looks like there is no shadowing) default(flagdata) mode = shadow flagbackup=f flagdata() print...quack #Quack (as little as possible. 1.5s beginning of scan) default(flagdata) flagbackup=f mode = quack quackinterval = 1.5 quackincrement = T flagdata() #First 5 channels always have high amplitudes. Last 2 a little low. #Flag end channels. (first 5 last 2) print...1st 5 channels and last 2 default(flagdata) flagbackup=f spw = [ *:0 5, *:62 63 ] flagdata() #Look at result with plotms... print ---- BACKUP FLAGS AFTER A PRIORI FLAGGING ----
13 #Backup flags. default(flagmanager) mode = save versionname = apriori comment = After, autocorr, shadow, quack and end channel flagging. flagmanager() print ---- FURTHER FLAGGING ---- #Other flagging. #According to previous study antennas DV05,DV09,DV11 and DV13 were flagged because 9,11 and 13 #didn t have position corrections and 5 had bad phases in the Y polarisation. #--> DV05 corr YY indeed has bad phases. #So flag, DV05, DV09, DV11, DV13. default(flagdata) flagbackup = F antenna = DV05, DV09, DV11, DV13 flagdata() print...backup flags after flagging DV05, DV09, DV11, DV13 #Backup flags. default(flagmanager) mode = save versionname = antennae comment = After flagging antennae 5, 9, 11, 13. flagmanager() print ---- MORE FLAGGING ---- #Further inspection: #All fields have a wide spectral dip in spw 1 centred on channel 38 (chans affected). #In spw 2 some high fluxes across the whole band. Always antenna DV01 correlation XX. #All fields. All times. default(flagdata) flagbackup = F antenna = DV01 correlation = XX flagdata() #Note: as gaincal REQUIRES both polarisations this last step effectively flags #antenna DV01! SHOULD HAVE HAD SPW = 2 at least. default(flagdata) flagbackup = F spw = 1:32 44 flagdata() #SETJY would go here. No flux cal for this dataset. #---> bandpass cal #Strongest source is (field 0). #Probably want to correct for phase changes during abservations. #Significant phase variation within scans so we want to correct for phase variations #with time. print ---- CORRECT PHASES FOR BANDPASS CALIBRATOR ----
14 #Correct bandpass calibrator phases. #(We don t need a gaintable; antenna positions already applied in split). default(gaincal) caltable = root+ bpphase.gcal field = 0 refant = DV02 calmode = p #Phase only. spw = *:20 30 #Few channels so bandpass phase slopes don t decorrelate the signal. solint = int minsnr=2.0 minblperant=4 gaincal() print ---- PLOTCAL TO CHECK PHASE VS TIME FOR BANDPASS CAL (bpphase.x.png etc) ---- #Check ffile = root+ bpphase.x.png os.system( rm + ffile) default(plotcal) caltable = root+ bpphase.gcal xaxis = time yaxis = phase iteration = antenna plotrange = [0,0,-180,180] poln = X figfile = ffile subplot = 441 if scriptmode: showgui = True else: showgui = False plotcal() ffile = root+ bpphase.y.png os.system( rm + ffile) poln = Y figfile = ffile if scriptmode: showgui = True else: showgui = False plotcal() print ---- BANDPASS CALIBRATION ---- #Do bandpass calibration. default(bandpass) caltable = root+ bandpass.bcal #Output name. gaintable = root+ bpphase.gcal #Input table with phase corrections. Applied on the fly. field = 0 spw = combine = refant = DV02 solint= inf solnorm=t minblperant=4 fillgaps = 14 #(Interpolate across the flagged channels in spw 1)
15 bandpass() #Lots of errors due to flagged antennas. OK. #Check bandpass solutions. Do once for each spw. print ---- PLOTCAL FOR BANDPASS TABLE (bandpass.phasespw+spw+.png etc) ---- default(plotcal) if scriptmode: showgui = True else: showgui = False caltable = root+ bandpass.bcal xaxis = chan yaxis = phase iteration = antenna plotrange = [0,0,-180,180] subplot=441 for spw in [ 0, 1, 2, 3 ]: figname = root+ bandpass.phasespw +spw+.png os.system( rm + figname) spw = spw figfile = figname plotcal() yaxis = amp plotrange = [] for spw in [ 0, 1, 2, 3 ]: figname = root+ bandpass.ampspw +spw+.png os.system( rm + figname) spw = spw figfile = figname plotcal() #Uneven bandpass for antenna 12 (presumably YY). SPW 0 only. #Otherwise phases are smooth and near 0 and amplitudes are all near 1 and fairly smooth. print ---- GAIN CALIBRATION (FIELD 0, ) ---- print...phase for each integration time #GAIN CALIBRATION. Use field 0 as the phase calibrator too. default(gaincal) field = 0 gaintable = root+ bandpass.bcal refant = DV02 caltable = root+ intphase.gcal calmode = p solint = int #One phase solution per integration. minsnr=2.0 minblperant=4 gaincal() print...phase for each scan time caltable = root+ scanphase.gcal solint = inf #One phase solution per scan. gaincal() #Rest as above.
16 print...amp and phase for each scan time caltable = root+ amp.gcal gaintable=[root+ bandpass.bcal, root+ intphase.gcal ] #Apply more frequent phase solutions. solint = inf #Generate one solution per scan. calmode= ap gaincal() #Rest as above. print ---- PLOTS OF CALIBRATION TABLES ---- print...intphase X.png, intphase Y.png #Inspect...Solutions for each integration time. default(plotcal) if scriptmode: showgui = True else: showgui = False caltable = root+ intphase.gcal xaxis = time yaxis = phase field = spw = iteration = antenna subplot = 441 plotrange=[0,0,-180,180] poln= X figfile = root+ intphase X.png os.system( rm + figfile) plotcal() #Colours are different SPWs. All sources in each line (higher noise for weaker source). poln = Y figfile = root+ intphase Y.png os.system( rm + figfile) plotcal() print...scanphase X.png, scanphase Y.png #Solutions for each scan. caltable = root+ scanphase.gcal poln = X figfile = root+ scanphase X.png os.system( rm + figfile) plotcal() poln = Y figfile = root+ scanphase Y.png os.system( rm + figfile) plotcal() print...amp phase.png #Amplitude and phase solution table. caltable = root+ amp.gcal plotrange = [0,0,-1,1] figfile = root+ amp phase.png os.system( rm + figfile) plotcal() #Phases always within + 1 degree. print...amp X.png, amp Y.png yaxis = amp
17 plotrange = [0,0,0.0,0.08] poln = X figfile = root+ amp X.png os.system( rm + figfile) plotcal() poln = Y figfile = root+ amp Y.png os.system( rm + figfile) plotcal() #Very steady amplitude values. Constant (but different) for each source. #All seem to bo OK. #BOOTSTRAPPING WOULD GO HERE. But we have no flux calibrator. #fluxscale not run. #APPLY CALIBRATION. print ---- APPLY CALIBRATION (applycal) ---- print...field 0 #Bandpass calibrator and phase reference source. default(applycal) field = 0 interp = [ nearest, nearest, nearest ] gaintable = [root+ bandpass.bcal, root+ intphase.gcal, root+ amp.gcal ] gainfield=[ 0, 0, 0 ] flagbackup = True applycal() print...field 1, 2, 3 field = 1,2,3 interp=[ nearest, linear, linear ] gaintable=[root+ bandpass.bcal, root+ scanphase.gcal, root+ amp.gcal ] gainfield=[ 0, 0, 0 ] applycal() #All look very regular and reasonable in terms of relative fluxes. #Look at residual amp/phase for sources. Copied from Ed Fomalont s script. #This is just a diagnostic step. print --- CALCULATE RESIDUAL PHASE ERRORS ---- default(gaincal) field = caltable = root+ gresid gaintable=[root+ bandpass.bcal, root+ scanphase.gcal, root+ amp.gcal ] solint = int refant = DV02 gaincal() print...generate plots of phase vs time for 3 baselines. resid phase spw0 X.png. default(plotcal) figfile = root+ resid phase spw0 X.png os.system( rm + figfile) caltable = root+ gresid xaxis = time yaxis = phase markersize = 2
18 plotrange=[0,0,-40,40] spw = 0 poln = X antenna= DV10 ;subplot=311 overplot = F; field = 0 ; plotcolor = red ; plotcal() # DV02 DV10 overplot = T; field = 1 ; plotcolor = green ; plotcal() # overplot = T; field = 2 ; plotcolor = blue ; plotcal() # overplot = T; field = 3 ; plotcolor = black ; plotcal() # antenna= DV07 ;subplot=312 overplot = F; field = 0 ; plotcolor = red ; plotcal() # DV02 DV07 overplot = T; field = 1 ; plotcolor = green ; plotcal() # overplot = T; field = 2 ; plotcolor = blue ; plotcal() # overplot = T; field = 3 ; plotcolor = black ; plotcal() # antenna= DV06 ;subplot=313 overplot = F; field = 0 ; plotcolor = red ; plotcal() # DV02 DV06 overplot = T; field = 1 ; plotcolor = green ; plotcal() # overplot = T; field = 2 ; plotcolor = blue ; plotcal() # overplot = T; field = 3 ; plotcolor = black ; plotcal() # #SPLIT print ---- SPLIT, MERGING CHANNELS ---> X4cd nowvr split cont.ms ---- default(split) outputvis = split2 datacolumn = corrected width = 64 split() #Image merging all SPWs and polarisations to get deeper image. print ---- CLEANING ---- default(clean) vis = split2 cell = 0.25arcsec imsize = 512 niter = 100 stokes = IQUV weighting = briggs robust = 0.0 spw = mode = mfs mask = [247, 247, 265, 265] for field in [ 0, 1, 2, 3 ]: field = field imagename = root+ f +field clean() print ---- IMAGES MADE, NOW COMPUTING STATS ---- #STATS: imnames = [root+ f0.image, root+ f1.image, root+ f2.image, root+ f3.image ] for imname in imnames: obj = imhead(imname, mode= get, hdkey= object ) st = I gstat I = imstat(imname, stokes=st) bgstat I = imstat(imname, stokes=st, box= 20,320,490,490 ) st = Q gstat Q = imstat(imname, stokes=st) bgstat Q = imstat(imname, stokes=st, box= 20,320,490,490 ) st = U
19 gstat U = imstat(imname, stokes=st) bgstat U = imstat(imname, stokes=st, box= 20,320,490,490 ) st = V gstat V = imstat(imname, stokes=st) bgstat V = imstat(imname, stokes=st, box= 20,320,490,490 ) print str(obj[ value ])+ \n + ST MAX MIN RMS OMIN MAX/RMS\nI +str(gstat I[ max ][0])+ + str(gstat I[ min ][0])+ +str(bgstat I[ rms ][0])+ +str(bgstat I[ min ][0])+ +str(gstat I[ max ][0]/bgstat I[ rms ][0]) + \n + Q +str(gstat Q[ max ][0])+ +str(gstat Q[ min ][0])+ +str(bgstat Q[ rms ][0])+ +str(bgstat Q[ min ][0])+ +str(gstat Q[ max ][0]/bgstat Q[ rms ][0]) + \n + U +str(gstat U[ max ][0])+ +str(gstat U[ min ][0])+ +str(bgstat U[ rms ][0])+ +str(bgstat U[ min ][0])+ +str(gstat U[ max ][0]/bgstat U[ rms ][0]) + \n + V +str(gstat V[ max ][0])+ +str(gstat V[ min ][0])+ +str(bgstat V[ rms ][0])+ +str(bgstat V[ min ][0])+ +str(gstat V[ max ][0]/bgstat V[ rms ][0]) print ---- EXPORTING FITS (I,Q,U,V) IMAGES ---- #Export final images as fits. default(exportfits) for imname in imnames: exportfits(imagename=imname, fitsimage=imname+.fits ) Script for imfit #Script to run imfit on each field (0-3) in the 4 quasar dataset. root = wvr1 #Root name for the images. flds = [ 0, 1, 2, 3 ] default(imfit) for field in flds: imname = root f +field.image print imname fit vals = imfit(imname, box = 243,243,269,269, stokes = I ) flx = fit vals[ results ][ component0 ][ flux ] shp = fit vals[ results ][ component0 ][ shape ] print Flux: + str(round(flx[ value ][0],4))+ +/ +str(round(flx[ error ][0],5)) + \n + Major axis FWHM: + str(round(shp[ majoraxis ][ value ],3))+ +/ +str(round(shp[ majoraxiserror ][ value ],4)) + \n + Minor axis FWHM: +str(round(shp[ minoraxis ][ value ],3))+ +/ +str(round(shp[ minoraxiserror ][ value ],4)) + \n + PA: + str(round(shp[ positionangle ][ value ],1))
Calibration with CASA
Calibration with CASA Philippe Salomé LERMA, Observatoire de Paris Credits: (Frédéric Gueth, George Moellenbrock, Wouter Vlemmings) Calibration On-line Source of possible problems that may need flagging
More informationALMA CASA Calibration
ALMA CASA Calibration Allegro - CASA Tutorial Day Luke T. Maud 3 March 2017 Calibration - the basics Remove effects of the instrument itself Remove effects of the atmosphere Scaling to the correct flux
More informationALMA Calibration Workshop
ALMA Calibration Workshop Lab #1: Basic Calibration December 1, 2011 Overview The goal of these exercises is to complete the initial calibration of an ALMA data set. There are two example data sets contained
More informationPhase and Amplitude Calibration in CASA for ALMA data
Phase and Amplitude Calibration in CASA for ALMA data Adam Leroy North American ALMA Science Center Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope
More informationA Crash Course in CASA With a focus on calibration
A Crash Course in CASA With a focus on calibration CASA team NRAO Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array CASA
More informationCASA Tutorial. Bradley S. Frank. University of Cape Town SKA South Africa
CASA Tutorial Bradley S. Frank University of Cape Town SKA South Africa This Session A southern-hemisphere non-blackbelt user s guide to CASA aka How I Learned to Stop Worrying and Learned to Love the
More informationData Processing: Visibility Calibration
Data Processing: Visibility Calibration The delivered ALMA data consist of the amplitudes and phases for the combined signals from pairs of antennas. These are called visibility data. The goal of visibility
More informationAtacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array
Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array Self-Calibration Ed Fomalont (NRAO) ALMA Data workshop Dec. 2, 2011 Atacama
More informationAtacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array
Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array Basics of Interferometry Data Reduction Scott Schnee (NRAO) ALMA Data
More informationArchive data weblog and QA2 report. Obtaining information of the observation and calibration of ALMA Archive data
Archive data weblog and QA2 report Obtaining information of the observation and calibration of ALMA Archive data Purpose of ALMA weblog/qa2 report Information about the observation: weather, antenna configuration,
More informationWhen, why and how to self-cal Nathan Brunetti, Crystal Brogan, Amanda Kepley
When, why and how to self-cal Nathan Brunetti, Crystal Brogan, Amanda Kepley Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline
More informationSelf-calibration. Elisabetta Liuzzo Rosita Paladino
Elisabetta Liuzzo Rosita Paladino Why self-calibration works When it is possible to self-calibrate in practice Calibration using external calibrators in not perfect interpolated from different time, different
More informationSelf-calibration Overview and line-continuum case study
Self-calibration Overview and line-continuum case study Anita M.S. Richards, UK ARC Node, Manchester, with thanks to Fomalont, Muxlow, Laing, ALMA, e-merlin, DARA teams & 'Synthesis Imaging 'Principles'
More informationAdvanced Calibration Topics - II
Advanced Calibration Topics - II Crystal Brogan (NRAO) Sixteenth Synthesis Imaging Workshop 16-23 May 2018 Effect of Atmosphere on Phase 2 Mean Effect of Atmosphere on Phase Since the refractive index
More informationObserving Modes and Real Time Processing
2010-11-30 Observing with ALMA 1, Observing Modes and Real Time Processing R. Lucas November 30, 2010 Outline 2010-11-30 Observing with ALMA 2, Observing Modes Interferometry Modes Interferometry Calibrations
More informationPdBI data calibration. Vincent Pie tu IRAM Grenoble
PdBI data calibration Vincent Pie tu IRAM Grenoble IRAM mm-interferometry School 2008 1 Data processing strategy 2 Data processing strategy Begins with proposal/setup preparation. Depends on the scientific
More informationPerformance of H Maser During the EOC Week 29 July to 03 August
Performance of H Maser During the EOC Week 29 July to 03 August ALMA Technical Note Number: 6 Status: FINAL Prepared by: Organization: Date: Anthony Remijan (EOC Program Scientist for Extension and Optimization
More informationREDUCTION OF ALMA DATA USING CASA SOFTWARE
REDUCTION OF ALMA DATA USING CASA SOFTWARE Student: Nguyen Tran Hoang Supervisor: Pham Tuan Anh Hanoi, September - 2016 1 CONTENS Introduction Interferometry Scientific Target M100 Calibration Imaging
More informationRecent imaging results with wide-band EVLA data, and lessons learnt so far
Recent imaging results with wide-band EVLA data, and lessons learnt so far Urvashi Rau National Radio Astronomy Observatory (USA) 26 Jul 2011 (1) Introduction : Imaging wideband data (2) Wideband Imaging
More informationHow small can you get? reducing data volume, retaining good imaging
How small can you get? reducing data volume, retaining good imaging Anita Richards UK ALMA Regional Centre Jodrell Bank Centre for Astrophysics University of Manchester thanks to Crystal Brogan and all
More informationVLBI Post-Correlation Analysis and Fringe-Fitting
VLBI Post-Correlation Analysis and Fringe-Fitting Michael Bietenholz With (many) Slides from George Moellenbroek and Craig Walker NRAO Calibration is important! What Is Delivered by a Synthesis Array?
More informationSpectral Line II: Calibration and Analysis. Spectral Bandpass: Bandpass Calibration (cont d) Bandpass Calibration. Bandpass Calibration
Spectral Line II: Calibration and Analysis Bandpass Calibration Flagging Continuum Subtraction Imaging Visualization Analysis Spectral Bandpass: Spectral frequency response of antenna to a spectrally flat
More informationALMA Phase Calibration, Phase Correction and the Water Vapour Radiometers
ALMA Phase Calibration, Phase Correction and the Water Vapour Radiometers B. Nikolic 1, J. S. Richer 1, R. E. Hills 1,2 1 MRAO, Cavendish Lab., University of Cambridge 2 Joint ALMA Office, Santiago, Chile
More informationWide Bandwidth Imaging
Wide Bandwidth Imaging 14th NRAO Synthesis Imaging Workshop 13 20 May, 2014, Socorro, NM Urvashi Rau National Radio Astronomy Observatory 1 Why do we need wide bandwidths? Broad-band receivers => Increased
More informationReduction with CASA. Kana Sugimoto, Erik Muller, and ALMA-J computing & EA-ARC science team (NAOJ)
Single ge Dish Data a Reduction with CASA Kana Sugimoto, Erik Muller, and ALMA-J computing & EA-ARC science team (NAOJ) How to reduce and analyze observation data from single dish radio telescopes by CASA
More informationCalibration in practice. Vincent Piétu (IRAM)
Calibration in practice Vincent Piétu (IRAM) Outline I. The Plateau de Bure interferometer II. On-line calibrations III. CLIC IV. Off-line calibrations Foreword An automated data reduction pipeline exists
More informationWide-Band Imaging. Outline : CASS Radio Astronomy School Sept 2012 Narrabri, NSW, Australia. - What is wideband imaging?
Wide-Band Imaging 24-28 Sept 2012 Narrabri, NSW, Australia Outline : - What is wideband imaging? - Two Algorithms Urvashi Rau - Many Examples National Radio Astronomy Observatory Socorro, NM, USA 1/32
More informationEvolution of the Capabilities of the ALMA Array
Evolution of the Capabilities of the ALMA Array This note provides an outline of how we plan to build up the scientific capabilities of the array from the start of Early Science through to Full Operations.
More informationLOFAR: From raw visibilities to calibrated data
Netherlands Institute for Radio Astronomy LOFAR: From raw visibilities to calibrated data John McKean (ASTRON) [subbing in for Manu] ASTRON is part of the Netherlands Organisation for Scientific Research
More informationWide-field, wide-band and multi-scale imaging - II
Wide-field, wide-band and multi-scale imaging - II Radio Astronomy School 2017 National Centre for Radio Astrophysics / TIFR Pune, India 28 Aug 8 Sept, 2017 Urvashi Rau National Radio Astronomy Observatory,
More informationRecent progress in EVLA-specific algorithms. EVLA Advisory Committee Meeting, March 19-20, S. Bhatnagar and U. Rau
Recent progress in EVLA-specific algorithms EVLA Advisory Committee Meeting, March 19-20, 2009 S. Bhatnagar and U. Rau Imaging issues Full beam, full bandwidth, full Stokes noise limited imaging Algorithmic
More informationEVLA Scientific Commissioning and Antenna Performance Test Check List
EVLA Scientific Commissioning and Antenna Performance Test Check List C. J. Chandler, C. L. Carilli, R. Perley, October 17, 2005 The following requirements come from Chapter 2 of the EVLA Project Book.
More informationError Recognition and Data Analysis
Error Recognition and Data Analysis Greg Taylor (UNM) With help from: Urvashi Rao, Sanjay Bhatnagar, Gustaaf van Moorsel, Justin Linford, Ed Fomalont Fifteenth Synthesis Imaging Workshop 1-8 June 2016
More informationHigh resolution/high frequency radio interferometry
High resolution/high frequency radio interferometry Anita Richards UK ALMA Regional Centre Jodrell Bank Centre for Astrophysics University of Manchester thanks to fellow tutors, ALMA and JBCA colleagues
More informationarxiv: v1 [astro-ph.im] 23 Sep 2013
CADRE: The CArma Data REduction pipeline D. N. Friedel a arxiv:1309.5844v1 [astro-ph.im] 23 Sep 2013 a University of Illinois, Department of Astronomy, 1002 W. Green St., Urbana, IL 61801 Abstract The
More informationCommissioning Report for the ATCA L/S Receiver Upgrade Project
Commissioning Report for the ATCA L/S Receiver Upgrade Project N. M. McClure-Griffiths, J. B. Stevens, & S. P. O Sullivan 8 June 211 1 Introduction The original Australia Telescope Compact Array (ATCA)
More informationEVLA Memo #166 Comparison of the Performance of the 3-bit and 8-bit Samplers at C (4 8 GHz), X (8 12 GHz) and Ku (12 18 GHz) Bands
EVLA Memo #166 Comparison of the Performance of the 3-bit and 8-bit Samplers at C (4 8 GHz), X (8 12 GHz) and Ku (12 18 GHz) Bands E. Momjian and R. Perley NRAO March 27, 2013 Abstract We present sensitivity
More information2010 PASEO Meeting. CASA: Common Astronomy Software Applications. July 15-16, 2010 Socorro, NM. Steven T. Myers (EVLA CASA Subsystem Scientist)
2010 PASEO Meeting July 15-16, 2010 Socorro, NM CASA: Common Astronomy Software Applications Steven T. Myers (EVLA CASA Subsystem Scientist) Atacama Large Millimeter/submillimeter Array Expanded Very Large
More informationNext Generation Very Large Array Memo No. 47 Resolution and Sensitivity of ngvla-revb. C.L. Carilli (NRAO)
Next Generation Very Large Array Memo No. 47 Resolution and Sensitivity of ngvla-revb C.L. Carilli (NRAO) Abstract I investigate the noise performance vs. resolution for the new ngvlarevb configuration.
More informationThe WVR at Effelsberg. Thomas Krichbaum
The WVR at Effelsberg Alan Roy Ute Teuber Helge Rottmann Thomas Krichbaum Reinhard Keller Dave Graham Walter Alef The Scanning 18-26 GHz WVR for Effelsberg ν = 18.5 GHz to 26.0 GHz Δν = 900 MHz Channels
More informationGlobal (3)mm VLBI : a brief summary and overview of the standard data analysis path. T.P.Krichbaum
Global (3)mm VLBI : a brief summary and overview of the standard data analysis path T.P.Krichbaum Max-Planck-Institut für Radioastronomie Bonn, Germany tkrichbaum@mpifr.de The Global Millimeter VLBI Array
More informationBasic Mapping Simon Garrington JBO/Manchester
Basic Mapping Simon Garrington JBO/Manchester Introduction Output from radio arrays (VLA, VLBI, MERLIN etc) is just a table of the correlation (amp. & phase) measured on each baseline every few seconds.
More informationImaging and Calibration Algorithms for EVLA, e-merlin and ALMA. Robert Laing ESO
Imaging and Calibration Algorithms for EVLA, e-merlin and ALMA Socorro, April 3 2008 Workshop details Oxford, 2008 Dec 1-3 Sponsored by Radionet and the University of Oxford 56 participants http://astrowiki.physics.ox.ac.uk/cgi-bin/twiki/view/algorithms2008/webhome
More informationEVLA Memo # 194 EVLA Ka-band Receiver Down Converter Module Harmonics: The Mega-Birdie at MHz
EVLA Memo # 194 EVLA Ka-band Receiver Down Converter Module Harmonics: The Mega-Birdie at 29440 MHz R. Selina, E. Momjian, W. Grammer, J. Jackson NRAO February 5, 2016 Abstract Observations carried out
More informationATCA Antenna Beam Patterns and Aperture Illumination
1 AT 39.3/116 ATCA Antenna Beam Patterns and Aperture Illumination Jared Cole and Ravi Subrahmanyan July 2002 Detailed here is a method and results from measurements of the beam characteristics of the
More informationEVLA Memo #205. VLA polarization calibration: RL phase stability
EVLA Memo #205 VLA polarization calibration: RL phase stability Frank K. Schinzel (NRAO) May 2, 2018 Contents 1 Context........................................ 2 2 Verification of Calibration - Pointed
More informationT8: Very Long Baseline Interferometry
T8: Very Long Baseline Interferometry The dataset we are using for this tutorial is from the EVN experiment N14C3. This is a 6-cm network monitoring experiment. The EVN data were obtained from the EVN
More informationIntroduction to CASA
Introduction to CASA Anita Richards UK ALMA Regional Centre JBCA, University of Manchester With thanks to Danielle Fenech, Dirk Petry, James Miller-Jones and the rest of the JBCA, RadioNet, ESO and NRAO
More informationTo print higher-resolution math symbols, click the Hi-Res Fonts for Printing button on the jsmath control panel.
To print higher-resolution math symbols, click the Hi-Res Fonts for Printing button on the jsmath control panel. Radiometers Natural radio emission from the cosmic microwave background, discrete astronomical
More informationALMA water vapour radiometer project
ALMA water vapour radiometer project Why water vapour radiometers? Science requirements/instrument specifications Previous work ALMA Phase 1 work Kate Isaak and Richard Hills Cavendish Astrophysics, Cambridge
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY HAYSTACK OBSERVATORY WESTFORD, MASSACHUSETTS
To: From: EDGES MEMO #104 MASSACHUSETTS INSTITUTE OF TECHNOLOGY HAYSTACK OBSERVATORY WESTFORD, MASSACHUSETTS 01886 January 14, 2013 Telephone: 781-981-5400 Fax: 781-981-0590 EDGES Group Alan E.E. Rogers
More informationSymmetry in the Ka-band Correlation Receiver s Input Circuit and Spectral Baseline Structure NRAO GBT Memo 248 June 7, 2007
Symmetry in the Ka-band Correlation Receiver s Input Circuit and Spectral Baseline Structure NRAO GBT Memo 248 June 7, 2007 A. Harris a,b, S. Zonak a, G. Watts c a University of Maryland; b Visiting Scientist,
More informationJCMT HETERODYNE DR FROM DATA TO SCIENCE
JCMT HETERODYNE DR FROM DATA TO SCIENCE https://proposals.eaobservatory.org/ JCMT HETERODYNE - SHANGHAI WORKSHOP OCTOBER 2016 JCMT HETERODYNE INSTRUMENTATION www.eaobservatory.org/jcmt/science/reductionanalysis-tutorials/
More informationVery Long Baseline Interferometry
Very Long Baseline Interferometry Cormac Reynolds, JIVE European Radio Interferometry School, Bonn 12 Sept. 2007 VLBI Arrays EVN (Europe, China, South Africa, Arecibo) VLBA (USA) EVN + VLBA coordinate
More informationDelay calibration of the phased array feed using observations of the South celestial pole
ASTRONOMY AND SPACE SCIENCE www.csiro.au Delay calibration of the phased array feed using observations of the South celestial pole Keith Bannister, Aidan Hotan ASKAP Commissioning and Early Science Memo
More informationParselTongue. Mark Kettenis, JIVE. December 3, 2008
ParselTongue Mark Kettenis, JIVE December 3, 2008 ParselTongue Software infrastructure for the ALBUS project (a RadioNet JRA) to develop and implement new calibration algorithms to implement pipelines
More informationData inspection and editing (Flagging, demixing & averaging)
Netherlands Institute for Radio Astronomy Data inspection and editing (Flagging, demixing & averaging) Tammo Jan Dijkema LOFAR Data Processing School, 18 September 2018 ASTRON is part of the Netherlands
More informationLOFAR update: long baselines and other random topics
LOFAR update: long baselines and other random topics AIfA/MPIfR lunch colloquium Olaf Wucknitz wucknitz@astro.uni-bonn.de Bonn, 6th April 20 LOFAR update: long baselines and other random topics LOFAR previous
More informationGuide to observation planning with GREAT
Guide to observation planning with GREAT G. Sandell GREAT is a heterodyne receiver designed to observe spectral lines in the THz region with high spectral resolution and sensitivity. Heterodyne receivers
More informationPlanning ALMA Observations
Planning Observations Atacama Large mm/sub-mm Array Mark Lacy North American Science Center Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very
More informationLOFAR: Special Issues
Netherlands Institute for Radio Astronomy LOFAR: Special Issues John McKean (ASTRON) ASTRON is part of the Netherlands Organisation for Scientific Research (NWO) 1 Preamble http://www.astron.nl/~mckean/eris-2011-2.pdf
More informationHigh Fidelity Imaging of Extended Sources. Rick Perley NRAO Socorro, NM
High Fidelity Imaging of Extended Sources Rick Perley NRAO Socorro, NM A Brief History of Calibration (VLA) An Amazing Fact: The VLA was proposed, and funded, without any real concept of how to calibrate
More informationThe ALMA TelCal subsystem. Dominique Broguière, Institut de RadioAstronomie Millimétrique (IRAM) Casa Developers meeting - 12/05/2010
The ALMA TelCal subsystem Dominique Broguière, Institut de RadioAstronomie Millimétrique (IRAM) Casa Developers meeting - 12/05/2010 Introduction TELCAL is the on-line calibration software for the ALMA
More informationBasic Calibration. Al Wootten. Thanks to Moellenbrock, Marrone, Braatz 1. Basic Calibration
Basic Calibration Al Wootten Thanks to Moellenbrock, Marrone, Braatz 1 Basic Calibration Outline Sketch of a typical observation Short discussion of formalism Types of calibration A priori A posteriori
More informationNext Generation Very Large Array Memo No. 16 More on Synthesized Beams and Sensitivity. C.L. Carilli, NRAO, PO Box O, Socorro, NM
Next Generation Very Large Array Memo No. 16 More on Synthesized Beams and Sensitivity C.L. Carilli, NRAO, PO Box O, Socorro, NM Abstract I present further calculations on synthesized beams and sensitivities
More informationWhy? When? How What to do What to worry about
Tom Muxlow Data Combination Why? When? How What to do What to worry about Combination imaging or separate imaging??..using (e-)merlin (e-)merlin covers a unique range of telescope separations, intermediate
More informationPointing Calibration Steps
ALMA-90.03.00.00-00x-A-SPE 2007 08 02 Specification Document Jeff Mangum & Robert The Man Lucas Page 2 Change Record Revision Date Author Section/ Remarks Page affected 1 2003-10-10 Jeff Mangum All Initial
More informationSpecial Topics: AIPS. 24 February 2012 Socorro, NM USA. Eric Greisen. Robert C. Byrd Green Bank Telescope
Special Topics: AIPS 4 February 01 Socorro, NM USA Eric Greisen Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array Outline
More informationA repository of precision flatfields for high resolution MDI continuum data
Solar Physics DOI: 10.7/ - - - - A repository of precision flatfields for high resolution MDI continuum data H.E. Potts 1 D.A. Diver 1 c Springer Abstract We describe an archive of high-precision MDI flat
More informationALMA Memo 452: Passband Shape Deviation Limits Larry R. D Addario 2003 April 09
ALMA Memo 452: Passband Shape Deviation Limits Larry R. D Addario 23 April 9 Abstract. Beginning with the ideal passband, which is constant from Nf s /2 to (N + 1)f s /2 and zero elsewhere, where N =,
More informationLOFAR DATA SCHOOL 2016
LOFAR DATA SCHOOL 2016 Tied Array Imaging (II), with contributions from: RRL group Scintillation (R. Fallows) Pulsar Working Group Radio Observatory Outline Tools Calibration (Cyg A imaging) Beams Scientific
More informationCalibration. (in Radio Astronomy) Ishwara Chandra CH NCRA-TIFR. Acknowledgments:
Calibration (in Radio Astronomy) Ishwara Chandra CH NCRA-TIFR Acknowledgments: Synthesis Imaging in Radio Astronomy II: Chapter 5 Low Frequency Radio Astronomy (blue book): Chapter 5 Calibration and Advanced
More informationEqualization. Isolated Pulse Responses
Isolated pulse responses Pulse spreading Group delay variation Equalization Equalization Magnitude equalization Phase equalization The Comlinear CLC014 Equalizer Equalizer bandwidth and noise Bit error
More informationEVLA System Commissioning Results
EVLA System Commissioning Results EVLA Advisory Committee Meeting, March 19-20, 2009 Rick Perley EVLA Project Scientist t 1 Project Requirements EVLA Project Book, Chapter 2, contains the EVLA Project
More informationSpectral Line Calibration Techniques with Single Dish Telescopes. K. O Neil NRAO - GB
Spectral Line Calibration Techniques with Single Dish Telescopes K. O Neil NRAO - GB Determining the Source Temperature Determining T source T A,meas (,az,za) = T src (,az,za) + T system Determining T
More informationAtacama Large Millimeter Array Project Status. M. Tarenghi ALMA Director
Atacama Large Millimeter Array Project Status M. Tarenghi ALMA Director Atacama Large Millimeter Array Specifications Partners: US (NSF)+Canada (NRC) - ESO+Spain - Chile 64 12-m antennas, at 5000 m altitude
More informationEVLA Memo 170 Determining full EVLA polarization leakage terms at C and X bands
EVLA Memo 17 Determining full EVLA polarization leakage terms at C and s R.J. Sault, R.A. Perley August 29, 213 Introduction Polarimetric calibration of an interferometer array involves determining the
More informationImage preprocessing in spatial domain
Image preprocessing in spatial domain convolution, convolution theorem, cross-correlation Revision:.3, dated: December 7, 5 Tomáš Svoboda Czech Technical University, Faculty of Electrical Engineering Center
More informationIntroduction to Imaging in CASA
Introduction to Imaging in CASA Mark Rawlings, Juergen Ott (NRAO) Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very Long Baseline Array Overview
More informationPACS data reduction for the PEP deep extragalactic survey
PACS data reduction for the PEP deep extragalactic survey D. Lutz, P. Popesso, S. Berta and the PEP reduction team Herschel map making workshop Jan 28-31 2013 Ugly! Boring! how do we detect yet more of
More informationApplying full polarization A-Projection to very-wide fields of view instruments: An imager for LOFAR Cyril Tasse
Applying full polarization A-Projection to very-wide fields of view instruments: An imager for LOFAR Cyril Tasse ASTRON/Leiden: Joris van Zwieten, Bas van der Tol, Ger van Diepen NRAO: Sanjay Bhatnagar
More informationThe 4mm (68-92 GHz) Receiver
Chapter 18 The 4mm (68-92 GHz) Receiver 18.1 Overview The 4 mm receiver ( W-band ) is a dual-beam, dual-polarization receiver which covers the frequency range of approximately 67-93 GHz. The performance
More informationWFC3 TV3 Testing: IR Channel Nonlinearity Correction
Instrument Science Report WFC3 2008-39 WFC3 TV3 Testing: IR Channel Nonlinearity Correction B. Hilbert 2 June 2009 ABSTRACT Using data taken during WFC3's Thermal Vacuum 3 (TV3) testing campaign, we have
More informationarxiv: v1 [astro-ph.im] 27 Jul 2016
Journal of the Korean Astronomical Society http://dx.doi.org/10.5303/jkas.2014.00.0.1 00: 1 99, 2014 May pissn: 1225-4614 eissn: 2288-890X c 2014. The Korean Astronomical Society. All rights reserved.
More informationComponents of Imaging at Low Frequencies: Status & Challenges
Components of Imaging at Low Frequencies: Status & Challenges Dec. 12th 2013 S. Bhatnagar NRAO Collaborators: T.J. Cornwell, R. Nityananda, K. Golap, U. Rau J. Uson, R. Perley, F. Owen Telescope sensitivity
More informationA model for the SKA. Melvyn Wright. Radio Astronomy laboratory, University of California, Berkeley, CA, ABSTRACT
SKA memo 16. 21 March 2002 A model for the SKA Melvyn Wright Radio Astronomy laboratory, University of California, Berkeley, CA, 94720 ABSTRACT This memo reviews the strawman design for the SKA telescope.
More informationSpectral Line Imaging
ATNF Synthesis School 2003 Spectral Line Imaging Juergen Ott (ATNF) Juergen.Ott@csiro.au Topics Introduction to Spectral Lines Velocity Reference Frames Bandpass Calibration Continuum Subtraction Gibbs
More informationAPO TripleSpecTool User's Guide
APO TripleSpecTool User's Guide Updated 09MAR2009 Table of Contents 7. APOTripleSpecTool 7.1. Installation 7.1.a. Computer Requirements 7.1.b. Download 7.1.c. IDL Setup 7.2. Data Preparation 7.3. Quickstart
More informationSMA Technical Memo #166
SMA Technical Memo #166 Subject: A METHOD FOR HANDLING SMA DATA FROM SWARM CORRELATOR - Solving for bandpass of high- or full- spectral resolution data Date: October 2, 2017 $ From: Jun-Hui Zhao (SAO)
More informationVolume 82 VERY LONG BASELINE INTERFEROMETRY AND THE VLBA. J. A. Zensus, P. J. Diamond, and P. J. Napier
ASTRONOMICAL SOCIETY OF THE PACIFIC CONFERENCE SERIES Volume 82 VERY LONG BASELINE INTERFEROMETRY AND THE VLBA Proceedings of a Summer School held in Socorro, New Mexico 23-30 June 1993 NRAO Workshop No.
More informationVery Long Baseline Interferometry
Very Long Baseline Interferometry Shep Doeleman (Haystack) Ylva Pihlström (UNM) Craig Walker (NRAO) Eleventh Synthesis Imaging Workshop Socorro, June 10-17, 2008 What is VLBI? 2 VLBI is interferometry
More informationEVLA Memo 146 RFI Mitigation in AIPS. The New Task UVRFI
EVLA Memo 1 RFI Mitigation in AIPS. The New Task UVRFI L. Kogan, F. Owen 1 (1) - National Radio Astronomy Observatory, Socorro, New Mexico, USA June, 1 Abstract Recently Ramana Athrea published a new algorithm
More informationULTRASONIC SIGNAL PROCESSING TOOLBOX User Manual v1.0
ULTRASONIC SIGNAL PROCESSING TOOLBOX User Manual v1.0 Acknowledgment The authors would like to acknowledge the financial support of European Commission within the project FIKS-CT-2000-00065 copyright Lars
More informationIntroduction to Radio Interferometry Sabrina Stierwalt Alison Peck, Jim Braatz, Ashley Bemis
Introduction to Radio Interferometry Sabrina Stierwalt Alison Peck, Jim Braatz, Ashley Bemis Atacama Large Millimeter/submillimeter Array Expanded Very Large Array Robert C. Byrd Green Bank Telescope Very
More informationA Quick Review. Spectral Line Calibration Techniques with Single Dish Telescopes. The Rayleigh-Jeans Approximation. Antenna Temperature
Spectral Line Calibration Techniques with Single Dish Telescopes A Quick Review K. O Neil NRAO - GB A Quick Review A Quick Review The Rayleigh-Jeans Approximation Antenna Temperature Planck Law for Blackbody
More informationSink Pixels and CTE in the WFC3/UVIS Detector
Instrument Science Report WFC3 2014-19 Sink Pixels and CTE in the WFC3/UVIS Detector Jay Anderson and Sylvia Baggett June 13, 2014 ABSTRACT Post-flashed calibration products have highlighted a previously
More informationConstant Offset in Cross-Polarized HERA IDR2.1 Data
Constant Offset in Cross-Polarized HERA IDR2.1 Data Katherine Elder, CHAMP ASU, 08/16/18 This memo gives an overview of the project I worked on this summer with the CAMPARE/CHAMP summer internship program
More informationVoice Activity Detection
Voice Activity Detection Speech Processing Tom Bäckström Aalto University October 2015 Introduction Voice activity detection (VAD) (or speech activity detection, or speech detection) refers to a class
More informationSMA Technical Memo #165? (draft)
SMA Technical Memo #165? (draft) Subject: A METHOD FOR HANDLING SMA DATA FROM SWARM CORRELATOR - Solving for bandpass of high- or full- spectral resolution data Date: September 6, 2016 $ From: Jun-Hui
More informationSpectral Line Bandpass Removal Using a Median Filter Travis McIntyre The University of New Mexico December 2013
Spectral Line Bandpass Removal Using a Median Filter Travis McIntyre The University of New Mexico December 2013 Abstract For spectral line observations, an alternative to the position switching observation
More information