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Progress Report on PSFs and Pixels Jay Anderson, Elena Sabbi, Kailash Sahu, and Matthew Bourque TIPS Feb 19, 2015.

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Presentation on theme: "Progress Report on PSFs and Pixels Jay Anderson, Elena Sabbi, Kailash Sahu, and Matthew Bourque TIPS Feb 19, 2015."— Presentation transcript:

1 Progress Report on PSFs and Pixels Jay Anderson, Elena Sabbi, Kailash Sahu, and Matthew Bourque TIPS Feb 19, 2015

2 Lots of Inter-related Issues Why do we need a good PSF? (Or do we?) How do we get a good PSF? How do we use a good PSF? Issues involve: – Distortion solutions – Image alignment and reference frames – High-precision transformations – PSF modeling (spatial and time variability) – Forward modeling into data domain – Deconvolution – Background matching – Pixel-area corrections Chicken and Egg Problems

3 Why Do We Need a Good PSF? Not everyone does… High-precision science – PSF-fitting of bright stars Photometry to 1% Astrometry to 0.01 pixel – PSF-fitting of faint stars Simultaneous photometry to optimize S/N – Fitting barely-resolved galaxies Weak-lensing analysis, profiles, point-source removal, deconvolution

4 How Do We Get a Good PSF? Deal with undersampled nature of detectors – WFC3/IR: up to 40% of light in central pixel – ACS/WFC: up to 23% of light in central pixel – WFC3/UVIS: up to 18% of light in central pixel Deal with spatial variations – Every ~500 pixels the PSF changes appreciably – Geometric optics, Charge diffusion variation – Tiny Tim models not very good Deal with time variations – Focus changes… model? – Often not enough stars in an image to extract – “Library” PSFs actually quite useful No standard format for PSF models, no obvious tools – “effective” PSF is one approach – Purely empirical -vs- model-based – Will suggest a “standard” format

5 How to Use a Good PSF? Push through astrodrizzle – Must plant stars in multiple FLTs consistently – “Fuzzy” constraints uneven sampling, correlated noise Fit to the individual FLT/FLC pixels – The only “hard”, independent constraints Can properly treat the errors – Easier for bright isolated point-sources “one-pass” – Harder for faint or resolved objects Must simultaneously interrelate the FLT pixels with scene Must properly convolve model of scene to match pixels

6 The Impasse Many tasks at once – Provide PSFs – Provide access to pixel mappings – Provide tools to use Institute is in a unique position – Users can’t be expected to solve all these probs Requires astronomer-decades… – Legacy value for HST (higher-level data products) – Practice for JWST (on hook) This talk – Progress report – Stimulate ideas, pique interest

7 This Talk Intro Mapping – Frontier Fields: hst2galign routine – Enables inter-image mapping PSFs – PSF study of F606W WFC3/UVIS archive – Suggested “standard” PSF format Tools – “bundles”: convenient structure for modeling

8 Frontier Fields hst2galign

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10 “CENTROID” POSITIONS “TEMPLATE-FIT” POSITIONS

11 Other Filters/Detectors hst2galign software takes *_flc.fits list and flags it outputs “mat” files of point-association lists allows mapping of FLT to REF frame uses distortion reference images

12 This Talk Intro Mapping – Frontier Fields: hst2galign routine – Enables inter-image mapping PSFs – PSF study of F606W WFC3/UVIS archive – Suggested “standard” PSF format Tools – “bundles”: convenient structure for modeling

13 PSFs: Spatial variation F606W WFC3/UVIS Spatial variations

14 Star Images from Entire UVIS Archive 5,013,607 star images extracted raster of 21×21 pixels extracted for each record (i,j) location and sky and fitted position/flux

15 Star Images from Entire UVIS Archive 5,013,607 star images extracted raster of 21×21 pixels extracted for each recorded (i,j) location and sky and fitted position/flux S/N Distribution

16 PSF Moments “A” excess “B” excess

17 PSF Moments “A” excess “B” excess “A” corner

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19 How the upper-left PSF changes with Focus

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21 Solving for the Focus in an exposure To do: * extend analysis to entire chip * determine how many stars are needed * correlate with focus model Encouraging!

22 Suggested “Standard” PSF format A 3-D fits image cube – NX×NY = N TOT PSFs Specify i,j fiducial locations – Each PSF is 101×101 pixels Super-sampled ×4 Covers 25×25 pixels (out to r=12.5) Normalized to have flux of 1.0 within 10 pix – Already available for many filters/detectors Tools: –get_psf [i CEN,j CEN,psfloc()] Returns local PSF at detector location –rpsf_phot [Δx, Δy,psfloc()] Returns fraction of light in particular pixel NPSFs % 101

23 Example of the fits header for a STD PSF

24 This Talk Intro Mapping – Frontier Fields: hst2galign routine – Enables inter-image mapping PSFs – PSF study of F606W WFC3/UVIS archive – Suggested “standard” PSF format Tools – “bundles”: convenient structure for modeling

25 A High-level Product: Pixel Bundles Putting it all together – Uses the alignment from hst2galign – Identify an object of interest and size (ie, 21×21 pix) Bundle-extraction routine: hst2bundle bundle_21x21_00630_00979.fits

26 The Bundle Itself A set of N RAST × N RAST × NIMs fits images – in 8 extensions 1-3 FROM FLT 4-5 DIRECT MAPPING EACH PIXEL TO REF-FRAME 6-7 REVERSE MAPPING FROM REF-FRAME TO LOCAL PIXEL 8 PSF (actually 101 × 101 × NIMs)

27 The Pixels in the Bundle

28 A Bundle is Like an “object” Can imagine python “methods” to analyze Bundle2process example routine – DUMP (output P,E,DQ,I,J,U,V,PSF…) – PIXCOMP (to rem artifacts, match sky) – XYZFIT_IND – XYZFIT_SIM – STACKING Point-source fitting Deconv fwd-model Documentation…

29 This Talk Intro Mapping – Frontier Fields: hst2galign routine – Enables inter-image mapping PSFs – PSF study of F606W WFC3/UVIS archive – Suggested “standard” PSF format Tools – “bundles”: convenient structure for modeling Discussion…


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