Planning and Analyzing WFIRST Grism Observa:ons

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Planning and Analyzing WFIRST Grism Observa:ons Stefano Casertano and the STScI Slitless Spectroscopy Working Group (Brammer, Dixon, MacKenty, Pirzkal, Ravindranath, Ryan) Pasadena 2/29/2016 - WFIRST mee6ng, p. 1

WFI Grism Observa:ons in the WFIRST Mission Slitless Spectroscopy observa6ons with the WFI Grism cons6tute a large part of WFIRST s mission High- La6tude Spectroscopic Survey will take 0.7 years of observa6ons One of three key cosmology measurements (Baryonic Acous6c Oscilla6ons, measuring the scale of the Universe at z = 1-3) Very desirable for high- visibility Guest Inves6gator and Guest Observer science Several one- page science ideas in the SDT Report involve Grism observa6ons Grism observa6ons cons6tute as much as 25% of HST observa6ons in recent years Scale, complexity, and required precision of grism observa6ons present several challenges: Calibra6on quality and complexity Source overlap Poin6ng stability and reconstruc6on Opera6ng mode separa6on of direct and dispersed images Data Analysis scale and complexity Wavelength accuracy Addi6onal observing modes This presenta6on summarizes the contents of two Technical Reports (found at hbp://www.stsci.edu/wfirst/technicalreports) and addi6onal work in progress WFIRST- STScI- TR1502: Planning for the Analysis of WFIRST- AFTA Grism Data: A Review of Current and Future Slitless Spectroscopy Sodware and Data Analysis Approaches (MacKenty et al.) WFIRST- STScI- TR1506: Slitless Grism Spectroscopy with WFIRST: Observing Modes and Strategies (Casertano et al.) Pasadena 2/29/2016 - WFIRST mee6ng, p. 2

The Wide Field Imager and the Grism element The wide- field channel of the Wide Field Imager is the WFIRST workhorse for wide- area imaging and spectroscopy Field of view ~ 0.27 square degrees (>100x ACS, NIRCAM) 18 4k x 4k IR detectors (110mas pixels) with throughput 0.76-2.5 µm Imaging: 5 normal filters (Z087, Y106, J129, H158, and F184) plus a very wide filter (W149, 0.927-2.00 µm) Spectroscopy: GRS grism, 1.35-1.89 µm, R ~ 500 Grism manufacture challenging (wide field of view, large dispersion, require 90% of light in first order) Three- element design with two dispersing surfaces Zero order suppressed, light spread over large area Engineering unit being manufactured to test design Readout every 5.4s except for guide windows (one 64x64 pixel per detector) Detector requirements achieved in lab devices Dark current < 0.1 e/s/pixel Read noise < 20 e (CDS) QE > 60% Pixel- to- pixel capacitance < 12% Pasadena 2/29/2016 - WFIRST mee6ng, p. 3

The High- La:tude Spectroscopic Survey Covers > 2200 square degrees Direct imaging in 4 filters (Y106, J129, H158, and F184), > 1000s total integra6on per filter, 2 orienta6ons, 3-5 exposures each Dithers to cover gaps between detectors at each orienta6on Expected point source sensi6vity 25.7 to 26.7 AB (5- σ) Slitless spectroscopy with grism over same area Current design has two passes ~six months apart, with two slightly different rolls in each pass (+/- 15 deg), resul6ng in dispersion angles differing by 15, 180, 195 degrees Two exposures at each roll; median exposure 6me ~2500s Line flux sensi6vity 1.2 10-16 erg/s/cm 2 (7- σ, for sources with 0.3 effec6ve radius) Survey cons6tutes 40% of mission 6me: 1.3 years for imaging, 0.7 years for spectroscopy Direct and dispersed images may not be taken at the same 6me Spectroscopic survey cri6cal for Baryonic Acous6c Oscilla6ons Redshid survey with > 15 million galaxies at z = 1-3, primarily measured through Hα and [OIII] emission Find angular scale of Acous6c Peak in galaxy correla6on func6on vs. redshid Expect measuring the scale of the BAO feature to 0.3% Systema6cs expected to be below 0.1% Requires accurate redshid measurement with rms error < 0.001 (systema6c and sta6s6cal) Other science returns include: Early structure forma6on (> 10,000 galaxies at z > 8) Characteriza6on of high- redshid QSO (~2000 at z>7) Iden6fying the highest starforming galaxies at z~2 (covering 5% of the sky) Improving census of ionizing radia6on at z~2 by extending the faint end of the luminosity func6on Pasadena 2/29/2016 - WFIRST mee6ng, p. 4

Performance needed to achieve BAO goals (1) Source density and distribu6on Expect 10 4 sources per square degree per redshid interval in Hα, 10 3 in [OIII] Assumes typical 70% completeness above sensi6vity threshold Line iden6fica6on helped by photo- z constraints Confusion, incompleteness at high S/N not fully discussed Low- redshid sources have similar density, spectra will overlap Bright sources can create avoidance regions (including zero order flux) Mul6ple dispersion angles can help both overlap and avoidance; quan6ta6ve analysis on realis6c simula6ons needed Image quality degrada6on may affect sensi6vity to line emission if poin6ng stability worse than 0.5 pixels (current requirement set at 0.2 pixels, under evalua6on) Pasadena 2/29/2016 - WFIRST mee6ng, p. 5

Performance needed to achieve BAO goals (2) Redshid accuracy σz ~ 0.001 (1+z) Requires total uncertainty < 15 Å, 1.4 pixels at 1.5 µm Contribu6ng elements include: Wavelength calibra6on Geometric calibra6on Poin6ng reconstruc6on Knowledge of source posi6on Measurement accuracy (limited by S/N, spa6al extent of emission region) Source structure is a significant source of uncertainty Line emission distributed differently from con6nuum Need to iden6fy posi6on of line emission for proper wavelength determina6on May be able to use colors to define line emission regions Angle diversity (180 degree flip or triangula6on) can also help reduce uncertainty Not included in current simula6ons and analysis Cri6cal upgrade needed for simula6ons Triangula6on methods, mul6- angle sodware under development for analysis Poin6ng reconstruc6on also under inves6ga6on Use of filter edges on bright stars (spectral ramp up/ramp down) subject to uncertain6es on underlying stellar SED Accuracy sufficient if edges sharper than 1% Con6nuum geometry vs. line posi6on at ACS resolu6on. White bar = 1. Line emission is typically unresolved. From Pirzkal et al (2013) Pasadena 2/29/2016 - WFIRST mee6ng, p. 6

Calibra:ng WFI Grism Includes geometric distor6on, trace, and wavelength calibra6on Experience with HST instruments provides star6ng point WFC3 used bright line sources (compact PNe) and con6nuum sources (WD) at 9 loca6ons to establish the basic wavelength and trace calibra6on Trace calibra6on refined from rich stellar fields All calibra6ons based on the match between direct and dispersed image Challenges for WFI Grism: Same density of calibra6on would require over 1000 observa6ons Larger field, dispersion might entail larger local devia6ons - > interpola6on may not be viable (to be reviewed on the basis of current design) Lack of zero order image, direct image limits precision of calibra6on to on- board blind small angle manoeuver precision Wavelength calibra6on requirements more stringent Calibra6on program will require careful design and analysis Could benefit from rich fields for trace *and* wavelength calibra6on (e.g., open clusters with tens of viable stars per detector) Higher dispersion enables use of stellar features for wavelength zero point solu6on and basic calibra6on Greatly reduce poin6ng- related errors, data volume required If single- target needed, consider par6al field readout to limit data volume Wavelength calibra6on using well- studied galaxy fields is also under considera6on Stars can serve as wavelength calibrators at WFI Grism spectral resolu6on (blue), not at WFC3/IR resolu6on (red) Pasadena 2/29/2016 - WFIRST mee6ng, p. 7

Poin:ng reconstruc:on HLS direct and dispersed images may not be obtained at the same 6me Wavelength calibra6on requires precise rela6ve astrometry (error budget 0.2 pixel) Registra6on can be achieved using bright stars and the edges of the grism transmission curve The quality of the registra6on depends strongly on the sharpness of the edges of the transmission curve: For a transi6on width originally assumed at 3% (from 0.1 to 0.9 over 0.03 of the midpoint wavelength), uncertain6es induced by SED varia6on on individual stars exceed the desired budget e.g., difference between K0III and K0V corresponds to 0.3 pixels Systema6c differences exceed noise for H < 19 Would require mul6ple stars and/or detailed SED modeling for each star If the transi6on width < 1% (suggested by current filter samples), stars with H < 19 will typically provide the needed accuracy Poin6ng reconstruc6on is feasible with no special tools if the transmission edges are 1% or sharper A Technical Report (Dixon, 2016) is currently in drad form Pasadena 2/29/2016 - WFIRST mee6ng, p. 8

Items to consider for future simula:ons and studies Realis6c number density and brightness of con6nuum and line sources Low- redshid con6nuum sources outnumber the desired line sources Confusion from overlapping spectra can be addressed with roll diversity; quan6ta6ve es6mates needed Es6mate completeness under expected survey parameters Consider image quality degrada6on and its impact on sensi6vity Effect of bright stars, including widely spread zero order light Reexamine wavelength error budget Develop es6mates of calibra6on accuracy (wavelength, trace, distor6on) based on complete plan Include effects of spectral diversity of targets (emission line region different from con6nuum) Quan6fy astrometric match between direct and dispersed images Set limits for line misiden6fica6on (redshid outliers) Fully account for focal plane geometry (including chip gaps) and possible instrumental and detector ar6facts Also consider the possibility of special observing modes: Limited field/chip readout (single chip, subarray) Can reduce data rates for programs with many short, single- target observa6ons (e.g., possible calibra6on programs) Faster reads (may need subarrays) Ability to observe brighter targets without satura6on Scanning mode Enables higher precision photometry, astrometry as for WFC3 Very high precision 6me- resolved spectrophotometry for extremely bright targets (e.g., exoplanet hosts during transits) Pasadena 2/29/2016 - WFIRST mee6ng, p. 9

Current Analysis SoLware: axe Several current HST projects use variants of the axe package (originally ST- ECF, now maintained and expanded at STScI) Iden6fy sources (and their light profile) in direct image Follow the spectral trace and apply wavelength calibra6on for each source based on calibra6on/configura6on files Extract 2- d spectra via axedrizzle Obtain op6mally- weighted 1- d spectrum axe can extract hundreds of spectra quickly Various groups (GRAPES, PEARS, WISPS) have adapted axe to their needs by adding processing steps or using custom wrappers for the axe package A companion package (axesim) can be used to generate simulated data (see presenta6on by James Colbert) Poten6al limita6ons of the axe approach: Current design expects direct image aligned with dispersed image Cannot readily incorporate informa6on from mul6ple rolls at the pixel level; overlapping sources cannot be separated Some special observa6ons (very bright sources, observa6ons obtained in scanning mode) are not well suited to the axe approach Ability to scale and run unsupervised over thousands of square degrees is untested Pasadena 2/29/2016 - WFIRST mee6ng, p. 10

Alterna:ves for the future: Forward Modeling Mo6vated by 3D- HST program (van Dokkum; Brammer, Momcheva, et al) Large area coverage (two- thirds of CANDELS fields, 625 sq arcmin) Aim to provide uniform, unbiased redshid measurements for CANDELS galaxies Rich photometric data available Has extracted spectra and determined redshids for 20,000 galaxies to H ~ 24 (AB); redshid precision ~ 0.3% Mostly automated, with visual inspec6on to clear out 5% of objects with poor data quality Current implementa6on performs template fit (using galaxy templates + line emission) directly to the 2- d extracted spectra Automa6cally accounts for source shape and light distribu6on Corrects for features such as edges in the transmission curves Future implementa6on will generalize to mul6ple sources/rolls Sources that overlap in one orienta6on can be separated in another Spectra for each source characterized by a number of parameters (e.g., stellar synthesis models, combina6on of empirical libraries, etc) Op6mize to determine the best descrip6on for all the available data (including photometry and morphology) Models can be itera6vely improved using the wealth of data obtained from WFIRST Self- calibra6on concepts can also be included Pasadena 2/29/2016 - WFIRST mee6ng, p. 11 2- d extrac6on and template fit (red curve) and joint redshid measurement (blue shaded area) for a galaxy with Ha at z=0.998 in 3D- HST data. The fit is carried out on the full 2- d spectrum.

Alterna:ves for the future: Linear Reconstruc:on New method for the analysis of mul6ple- roll data directly in observed pixel space Designed to handle sources with overlapping spectra Use linear least squares solu6on to solve simultaneously for the spectra of all sources in the field Computa6onally very demanding Need to store separately the coefficients of the signal produced by each wavelength element in each dispersed image A typical dataset may require storage of 10 8 coefficients and the solu6on of an extremely sparse 10 6 x 10 5 system for WFC3/IR Requirements scale by an order of magnitude or more for WFIRST Pilot sodware under development uses the LSQR algorithm (Paige and Saunders 1982) for the least- squares matrix solu6on Test cases carried out with WFC3/IR parameters Total run 6me 10 hours for 9 images Demonstrate very good extrac6on in the low- noise regime Currently inves6ga6ng noise proper6es; expect quan6ta6ve es6mates in < 6 months Pasadena 2/29/2016 - WFIRST mee6ng, p. 12

Linear Reconstruc:on test Input direct image and segmenta6on map (130 sources selected; not all visible on this scale) Simulated dispersed images (9 roll angles) Subset of extracted spectra (noiseless): Red (model), black (extracted) Pasadena 2/29/2016 - WFIRST mee6ng, p. 13

Concluding Thoughts Slitless observa6ons with WFIRST will present substan6al challenges in scale, complexity, and accuracy Extremely large field of view (1 exposure > a Large HST program ) Tight calibra6on and error requirements Higher dispersion than current HST grisms increases source overlaps Data volume and processing requirements will require rethinking of current paradigms Experience with current missions and observatories provides insight on how to meet these challenges Exis6ng data and tools can be used to guide necessary studies Careful models and simula6ons are needed to verify that the goals can be achieved to the desired level Realis6c parameters and analysis needed Account for spectral diversity in sources, spectral overlaps New tools are being developed that might be beber suited to WFIRST goals Let s figure out the right ques6ons to ask and work together to answer them! Pasadena 2/29/2016 - WFIRST mee6ng, p. 14