ALMA Study Total Power Map to Visibilitjes (TP2VIS) Joint-Deconvolutjon of ALMA 12m, 7m & TP Array Data Peter Teuben (U. Maryland) Jin Koda (Stony Brook/NAOJ/JAO); Tsuyoshi Sawada (NAOJ/JAO); Adele Plunketu (ESO/JAO); Crystal Brogan (NRAO)
Example Science Cases with Extended & Compact Structures Combining data from the difgerent ALMA arrays is a science driver for a number of topics, namely those that probe size scales of extended and compact structures simultaneously. • Example science cases include – Protostar outglows and their environment – Evolutjon of AGB stars, planetary nebulae, and their winds – Formatjon of dense clumps and pre-stellar cores in molecular clouds – Interplay between molecular clouds and galactjc structures in nearby galaxies – Galactjc outglow & fountains – Analysis of the probability distributjon functjon (PDF) from difguse, extended emission to dense, clumpy emission. – Many more
Demonstratjon with MIRIAD Example: Structure in Molecular Cloud ALMA CO(1-0) cube of a molecular cloud in Large Magellanic Cloud “Stomach” of molecular cloud – the entjre FoV should be fjlled with emission 12m-only 12m+7m 12m+7m+TP ALMA 12m+7m visibilitjes Joint-deconvolutjon (CLEAN) in MIRIAD ALMA TP ⇒ visibilitjes (TP2VIS in MIRIAD)
Demonstratjon with MIRIAD Example: Structure in Molecular Cloud ALMA CO(1-0) cube of a molecular cloud in Large Magellanic Cloud Stomach” of molecular cloud – the entjre FoV should be fjlled with emission 12m-only 12m+7m+TP Joint-deconvolutjon: recovery of extended emission + virtually no negatjve sidelobes
Demonstratjon with MIRIAD TP2VIS vs Feather ALMA CO(1-0) Data of GMC in LMC; Reduced with MIRIAD TP2VIS Feather Difgerence 12m+7m+TP joint-Deconvolutjon 12m+7m Deconvolutjon + TP Feather – TP2VIS Systematjc difgerence around emission
Demonstratjon with MIRIAD Deconvolutjon with and without TP How well deconvolutjon works for 12m+7m part with and without TP? 12m+7m+TP joint-Deconvolutjon Minus TP 12m+7m Deconvolutjon Benefjt for the 12m+7m part . Joint-deconvolutjon: Less negatjve around emission! Peaks not as good? – need more tests.
ALMA Study Objectjves Our method already implemented in MIRIAD for combinatjon of CARMA and Nobeyama 45m telescope data (Koda et al. 2011). This study will make it user-friendly in CASA. • Developments – CASA-based TP2VIS tool – Visibility weight visualizatjon tool – Benchmark simulatjon data • Validatjons – Tests with simulatjon data – Tests with ALMA archival data • User manuals
Members and Expertjse • Jin Koda (Stony Brook/NAOJ/JAO) – Developed TP2VIS in MIRIAD (Koda et al. 2011, ApJS, 193, 19) – Jump-started tests for CASA TP2VIS during his sabbatjcal at NAOJ Chile/JAO in Spring 2016; we will show some progress in this talk. • Peter Teuben (U. Maryland) – One of the three founders of MIRIAD – Expertjse in CASA through the ADMIT development • Tsuyoshi Sawada (NAOJ/JAO) – JAO scientjst – Expert of ALMA TP performance. • Adele Plunketu (ESO/JAO) – ESO postdoc fellow at JAO – Extensive testjng of interferometer + single-dish combinatjon • Crystal Brogan (NRAO) – CASA subsystem scientjst
12m+7m+TP Combinatjon Methods 1) Initjal guess – TP map as initjal guess for 12m+7m CLEAN 2) Feather – Add CLEANed 12m+7m map with TP map 3) Joint-deconvolutjon (i.e., convert TP to VIS) – CLEAN 12m+7m+TP simultaneously Notes: • CLEAN could be replaced with MEM or any other deconvolutjon method • 3) can be used together with 1) or 2)
TP2VIS Flow Chart Weight Weight
Convertjng TP map into Visibilitjes • Basic parameters of each visibility – U – V – W – Amplitude – Phase – Weight • Supplementary parameters – Field for mosaic – Primary beam shape – Etc.
Convertjng TP map into Visibilitjes • Basic parameters of each visibility – U – V Visibility distributjon set manually – W Coupled in a sense – Amplitude From Total Power (TP) map – Phase Depends on system parameters, integratjon tjmes, etc. – Weight Will try two approaches • Supplementary parameters – Field for mosaic – Primary beam shape – Etc.
( U, V, W , Amplitude, Phase, Weight) Gaussian Visibility/Weight Distributjon Generate the distributjons of visibilitjes and their weights, so that their F.T. produces the TP beam patuern as synthesized beam under Natural weightjng. If the TP array has a The visibility/weight distributjon Gaussian beam patuern, should also follows a Gaussian. F . T . µ e − ( l 2 + m 2 )/2 σ 2 − (2 πσ ) 2 ( u 2 + v 2 )/2 Beam TP µ e Beam TP FWHM=2 2ln2 σ htup://www.cv.nrao.edu/course/astr534/FourierTransforms.html
( U, V, W , Amplitude, Phase, Weight) Progress report I: Gaussian visibility distributjon in CASA measurement set
(U, V, W, Amplitude, Phase , Weight) Obtain (Amp, Phase) from TP Map • Fourier-transform TP map and read (amp,phase) at a locatjon of each visibility. • Learning CASAtoolkit tasks in the “simobserve” script ⇒ some success, but not fully yet.
(U, V, W, Amplitude, Phase, Weight ) Weights of TP Visibilitjes • Among TP visibilitjes – Two ways to adjust • Adjustjng visibility distributjon • Adjustjng weights of visibility points ⇒ Already set the visibility distributjon to Gaussian. All visibility points should have an equal weight. • With respect to 12m+7m visibilitjes – Best approach • Stjll debatable • Need tests – Two approaches we plan to test • RMS noise-based approach • Matched beamsize approach
(U, V, W, Amplitude, Phase, Weight ) Noise-based Approach: Weight from T sys and t vis Calculate noise-based weight need to the relatjon between sensitjvity and Tsys, etc. ∆ S i µ T Idea: Image sensitjvity share the same proportjonality constant. sys v µ T (If we fjgure one out, we know the other one.) ∆ S Visibility sensitjvity k sys 2 2 1 1 In fact, with natural weightjng the noises of each ∑ = ÷ ÷ ∆ S i v ∆ S visibility and of fjnal image are related simply: k k t tot = N vis t vis For 12m, 7m visibility For TP map 2 k B 2 k B 1 C TP = C ij = Use this for TP visibilitjes η m b η a η q A ( η a , i A i )( η a , j A j ) 2 η q
(U, V, W, Amplitude, Phase, Weight ) Noise-based Approach: Parameters for weights T sys T ∆ S i = C Noise of TP single-dish map: s ys TP B × t tot Known or measurable 2 k B C TP = η m b η a η q A t vis = t tot t tot ∆ S i = RMS-noise from emission-free channels N vis T = typical Tsys from observatjons s ys N vis Arbitrarily-chosen number of visibilitjes Should be large enough to fjll UV-space smoothly T sys T These give the sensitjvity (or noise- v = C s ys ∆ S based weight) of each visibility point: k TP B × t vis
(U, V, W, Amplitude, Phase, Weight ) Matched Beamsize-based Approach With TP data, the beam area and emission have non-zero values. Dirty map CLEAN components + Residual CLEAN Jy / Ω dirty Jy / Ω C Jy / Ω dirty Unit: LEAN Ω dirty ≠ Ω C could cause inconsistency in fmux in a CLEANed map LEAN Ω dirty = Ω C We want to have for fmux conservatjon LEAN Depend only on weight at (u,v)=(0,0) Depend on weight distributjon in uv-space (e.g., on how extended the uv distributjon is) ∫∫ B ( l , m ) dldm = W (0,0) Ω dirty = Ω dirty = Ω C Set the weight of TP data to satjsfy LEAN
Progress Report II We can generate (U,V,W, Amp, Phase), but not yet other parameters Dirty map afuer CASA/TP2VIS Model Smoothed with TP beam Difgerence 33 pointjng mosaic: x – pointjng centers We can at least make a Gaussian visibility distributjon for TP. Stjll, banging head for many issues: for example, CASA CLEAN/TCLEAN do not accept our TP visibilitjes together with 12m+7m visibilitjes …
Benchmark Model Data • Need model data for benchmark test for TP2VIS and other combinatjon methods in future. • Not so good data with emission distributjon and dynamic range, e.g., like in molecular clouds. • This ALMA study will develop a set of benchmark model data with compact & extended emission.
Benchmark Model Data: Example Molecular cloud with power spectrum density fmuctuatjon n=4 • Power spectrum amplitude P 3 D ( k ) µ k − n • Random phase • Test script ok, but slow (~1 week to generate the right on a fast PC). • Include more coherent structure, such as spiral arm, outglow, etc. Resolutjon 0.05” Size 3.4’ x 3.4’
Benchmark Model Data: Example Molecular cloud with power spectrum density fmuctuatjon n=4 • Power spectrum amplitude P 3 D ( k ) µ k − n • Random phase One interestjng caveat to those who identjfy fjlaments/shells. Even this random realizatjon shows apparent Filament Resolutjon 0.05” Shell Size 3.4’ x 3.4’
Documentatjon & User Manual • Final product include – Descriptjon of the method – User manual Example descriptjon of the power- spectrum model
Summary of the New ALMA Study Total Power Map to Visibilitjes (TP2VIS) Our method already implemented in MIRIAD for combinatjon of CARMA and Nobeyama 45m telescope data (Koda et al. 2011). This study will make it user-friendly in CASA. • Developments – CASA-based TP2VIS tool – Visibility weight visualizatjon tool – Benchmark simulatjon data • Validatjons – Tests with simulatjon data – Tests with ALMA archival data • User manuals
Recommend
More recommend
