Discussion of CalWebb contents M. Robberto (facilitator)

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Presentation transcript:

Discussion of CalWebb contents M. Robberto (facilitator)

MASKCORR Bad Pixel Mask *_RAW.fits Data cube file DQ *_MSK.fits Mask file REFCORR Ref.pixel correction ERR /REF Ref. method flag BDCORR Bias/dark correction ERR *_DRK.fits Dark cube file LINCORR Linearity correction ERR *_LIN.fits Linearity table ITIME SAMP _IMA out? *_IMA.fits Data cube file CRWFCORR Cosmic/Weight/Fit *_NOI.fits Readout noise file ERR *_CRT.fits Count rate file File inProcedureFile outModified Non-SCI Extensions CALWebb

MASKCORR Flag values from the static bad pixel mask file are added to the DQ image.  How many types of bad pixels do we expect? hot, cold, dead, unstable, low QE, early saturation…  Can the user select the types of bad pixels to reject?  How do find bad pixels? dark => hot flat field => cold difference => dead …  Bad Reference pixels

REFCORR Reference pixels track voltage and allow to correct for time dependent drifts of the signal offset. Both the Rockwell H2RG arrays and the MIRI IBC arrays contain reference pixels. MIRI also contains additional reference outputs.  Are all reference pixels equally good? (not the case in WFC3)  How do we extract the reference value?  What do we do with the reference value?  Temperature effects?  Are reference pixels really insensitive to light?  What do we do with subarrays?

BDCORR (Bias and Dark subtraction) The BDCORR step subtracts the dark reference images, readout-by-readout for MULTIACCUM observations, from the science data. STScI will maintain a library of dark current images (files *_DRK.fits) for all instruments, covering the entire range of predefined MULTIACCUM sample sequences.  Are bias and dark stable? Do we need to perform extra correction (e.g T dependent darks)?  Should we take darks for all readout modes? What about subarrays?  If there is a light leak, do we need filter dependent “darks”? Should we anticipate these cases?  How do we account for the dark current noise?

LINCORR (Linearity correction) The LINCORR step applies the linearity correction to pixels with signal below their defined saturation levels. However, it applies no correction to pixels in the high signal regime, but rather flags them as saturated in the DQ image.  How do we really estimate the linearity correction?  Are (all) pixels linear at low fluxes? Should we distinguish between non linearity and reset anomaly? How?  Is it wavelength dependent? Does it depend on the photon rate?  How do we estimate the noise on the linearity correction?

CRID-WEIGHT-SLOPEFIT (Produce Slope Images) CRID: identify and flag pixels suspected of containing cosmic ray (CR) hits, WEIGHT: apply the proper weight to the single reads SLOPEFIT: combine the data from all readouts into a single image. (M. Regan)