SIRTF-IRS software Fred Lahuis Leiden 18 Nov 2002 (presented by Ewine van Dishoeck and Adwin Boogert, c2d meeting Dec. 11, 2002)

IRS Instrument Low resolution R~ imaging spectrograph 1 st and 2 nd order SL Si:As micron LL Si:Sb micron High resolution R~600 echelle spectrograph order 11 to 20 SH Si:As micron LH Si:Sb micron

IRS images (128x128) Simulated single exposure of an extended source with an M82 + Circinus-like spectrum from mm, including cosmic rays. Simulated IRS SL image Sample IRS calibration files

IRS-ISO example IRS Low-Res IRS High-Res

IRS dataflow

IRS dataflow (cont’d) BCD products Lights-off Science pipeline Lights-on Science pipeline Science by legacy team TEXAS SSC Best effort Final delivery

SSC Pipeline Blackbox Products 2d images flatfielded BCD applied flatfield 1d spectrum nonimal extraction Flat-field is only controllable step Optimal extraction in SMART

SMART

SMART functionality " Read SSC data and handle complex projects (data volumes) " View and evaluate individual and series of files " Basic pixel arithmetic: add/subtract/multiple frames " Combine a series of images according to their quality " Spectral extraction for point and extended sources " (PU image analysis)  Combining spectra from different orders, modules, runs, … " Most of the ISAP features (line/BB/zodi fitting, photometry, line identification, dereddening) " Template fitting (source class identification, redshift) " Spectral maps (line ratio maps) " Interactive defringing

C2D Interactive Analysis SMART (legacy launch) project handler IRS image analysis optimal spectral extraction IRS calibration tools and data Defringing flatfield modification and robust sine wave fitting Modeling gas-phase molecules, disks, ices, solid state features C2D science pipeline scripts and data Spectral analysis/reduction tools zodiacal light, line-fitting,.... inspired by SWS IA, SMART-IDEA, ?

Catalogue 1. Spectra flux vs wavelength 2. Identification of features, where feasible 3. Flag for off-source emission, where feasible 4. Strengths of features 5. Classification of objects, cross refs 6. Complementary data Only 1-3 will be in catalog/deliveries to SSC; 4-6 TBC for final delivery

Instrumental fringes " Fabry-Perot effects on plane parallel surfaces within the instrument inside filters Plane mirrors detector surfaces Separations of a few mm are most efficient " Correction methods: FFT, bad Robust sine fitting Flatfield matching

Flatfield modification Minimize fringe residuals How? by modifying flatfield Fringe pattern changes per observation source offset in the slit shifts wavelength shifts fringe pattern source extent reduces effective resolution Stands or falls with the quality of the flatfield(s)

Flatfield modification II Determine phase shift and smooth/enhance factors for all orders Use smooth polynomial fit for phase shift and/or smooth/enhance factor?

Modflat pipeline issues #1 " Flat needs to be available, and in 1D approach extracted exactly the same way as science target. " In 1D approach: maximum sampling extracted spectrum crucial, in particular for highest echelle orders. " Smoothing fringe amplitude flat easier than enhancing. Flat used for Modflat should have highest possible resolution (point source). " Ideally, flat is available for each position in the slit, and best match with science observation is chosen from flat field 'database'. " For extended sources 2D version of Modflat may be considered: determine phase shift and smooth/enhance factors for each column. Adwin Boogert, IRS Fringing meeting Cornell, 30 August 2002

Modflat pipeline issues #2 " In case of extended source in combination with point source? Ideally extract spectrum of background and point source, and defringe independently, or simply subtract sky from point source. " Return header keywords: phase shift and amplitude reduction factor for each order. " 2D or not? May be better for extended source: apply modflat on each column. Point sources not expected to improve in 2D, what really matters is extraction at high sampling. Adwin Boogert, IRS Fringing meeting Cornell, 30 August 2002

Defringing: sine waves " Why use sine functions 'Simple' and robust algorithm Allows better estimation of fringe frequency than FFT Not limited by sampling or gaps in the spectrum Automatic mode using Bayesian evidence prevents overfitting " Goal: fringe artifact < 1% " Why? Most interesting science is in the weak features

Theory reflectance Computationally handy formula Implement a wavelength dependence of R and n and a x,y dependence of d Can we

Implementation Isolate fringes from continuum Find the strongest fringe components Compute the total fringe spectrum and return the defringed spectrum

Fringe characteristics Fringe parameters (frequency, amplitude and phase) relate to true physical parameters (refractive index, wafer thickness, reflectance and wavelength (source slit position)) ?..... what's next

Next " "Full" optical/physical model? " Parameters need to be extracted from the data " 2-D: requires optimal extraction and source modeling ".... " Will the data/calibration be good enough " We'll just have to try Good (self)calibration is crucial

Waterloo Conference First (to be) published IRS defringing paper

ISO-SWS Orion KL, Boonman et al. 2002

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