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WFC3/IR LESSONS FOR WFIRST Jay Anderson STScI. WFC3/IR Lessons for WFIRST 1)Absolute astrometry 2)PSF modeling and variation (space/time) 3) Bulge-type.

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Presentation on theme: "WFC3/IR LESSONS FOR WFIRST Jay Anderson STScI. WFC3/IR Lessons for WFIRST 1)Absolute astrometry 2)PSF modeling and variation (space/time) 3) Bulge-type."— Presentation transcript:

1 WFC3/IR LESSONS FOR WFIRST Jay Anderson STScI

2 WFC3/IR Lessons for WFIRST 1)Absolute astrometry 2)PSF modeling and variation (space/time) 3) Bulge-type fields

3 WFC3/IR Lessons for WFIRST 1)Absolute astrometry 2)PSF modeling and variation (space/time) 3) Bulge-type fields

4 Absolute Astrometry: What Can WFC3/IR Do? hst2galign software written for FrontierFields Excellent data set of UDF in F160W – 50 well-dithered obsns at each of 2009, 2010, 2012 – Same orientation Procedure – Found a few bright objects to align all images to first image – Made a x4 supersampled stack (iterative) – Extract high-res template for each galaxy: a “GSF” Simply gives distribution of light (convolved with PSF) Pick an arbitrary point as the “handle” Find that handle in each exposure Fit to 5×5 pixels in each exposure Properly account for distortion – Result: set of consistently measured positions for each object in each exposure – Next: assess quality of transformations 14  ×11 

5 Transformations Distortion: x raw  x corr General linear transformation: – Local frame (x,y) to – Master frame (u,v) – Really only 6 parameters ( A B C D ( ) ) u-u o v-v 0 = ( ) x-x o y-y 0 (x,y) (u,v)

6 The High Achievers The “best” objects are stars Defined by consistency residual – x obs − x trans (U mast,V mast ) – y obs − y trans (U mast,V mast ) > 100 objects! Transformation precision ~ 0.05/√100

7 Proper Motions Each point is an observation from one exposure Scatter within epoch  Measurement error: Inter-epoch trend  Proper motion! Galaxies used to define transformations 2009 2010 2012

8 Two neighboring stars… Open green circle is fixed in reference frame A binary orbit? Can see motion with your eyes!

9 WFC3/IR Lessons for WFIRST 1)Absolute astrometry 2)PSF modeling and variation (space/time) 3) Bulge-type fields

10 WFC3/IR F110W PSF (harsh stretch)

11 WFC3/IR F110W PSF (medium stretch)

12 WFC3/IR F110W PSF (linear stretch) 40% of light in central pixel

13 WFC3/IR F110W PSF (linear spatial variation)

14 WFC3/IR F110W PSF (medium stretch)

15 WFC3/IR F110W PSF (medium stretch; spatial grad)

16 WFC3/IR F110W PSF (x profile)

17 TIME DEPENDENCE OF F110W PSF (0.5% here, but ~10% for ACS/UVIS)

18 WFC3/IR Lessons for WFIRST 1)Absolute astrometry 2)PSF modeling and variation (space/time) 3) Bulge-type fields

19 Tom Brown’s Treasury Program

20 Sweeps SAHU’S BULGE MICROLENSING PROGRAM TO FIND BHs, NSs IN DISK

21 Fast BH, NS, WD or slow BD? Schematic of event Duration of event  mass   Astrometric offset  mass Astrometry Photometry

22 OBSERVING STRATEGY NUMBER OF TARGETS – Each ACS field has ~300,000 stars 50% have S/N > 100 – Each WFC3/UVIS field has 200,000 stars – Total of > 2,500,000 stars OBSERVING CADENCE – Optimized for long-duration events – One visit every 2 weeks over two 4-month windows 64 visits per year EXPECTATIONS: (54 / 120 events “astrometric”) – 18 events due to BHs – 14 due to NSs – 22 due to MS stars

23 SWEEPS 2003/4 F814W STACK

24 SWEEPS 2012/4 F814W STACK

25

26 SWEEPS 2012/4 STACK+REG

27 SWEEPS 2012/4 F814W STACK

28 SWEEPS 2012/4 F814W SUB

29 SWEEPS 2012/4 F814W STACK

30 BROWN 2010 F110W STACK

31 BROWN 2010 F110W INDIV

32 SWEEPS 2012/4 STACK+REG

33 SWEEPS 2012/4 STACK+REG 300,000 stars in one ACS Field 300,000 / (202”) 2 7 stars per square arcsec ACS typ sep = 10 pixels WFC3/IR typ sep = 3.5 pixels

34 Faint stars will be brighter in IR… WDs (Calamida et al 2014)

35 Calamida et al (2015), soon to be submitted 0.15 Msun

36 Calamida et al (2015), soon to be submitted

37 Challenges For Sahu’s ACS/UVIS program – use general software routine for finding and phot-ing Finding done on combined products Measuring done on individual images, simultaneously – ok, since most stars separated: “semi-crowded” neighbors are perturbations PSFs can be extracted easily – PMs not major issue, can be measured after the fact – easy to triage complicated cases For WFIRST – will need specialized software ground does crowded-field well, but not with undersampling undersampling means we must operate on original images – need to find all stars even neighbors within 1 pixel PSF creation will be complicated – crowding, color, spatial variations, – must do with neighbors in mind 10x more stars affect 5x5 fitting aperture (>1 per) – PMs need to be folded in – harder to triage complicated cases (too many)


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