Grism Sensitivities and Apparent Non-Linearity

Transcription

1 Instrument Science Report NICMOS Grism Sensitivities and Apparent Non-Linearity Ralph C. Bohlin, Don J. Lindler, & Adam Riess May 10, 2005 ABSTRACT Recent grism observations using the NICMOS instrument on HST have extended the spectrophotometric wavelength coverage of a subset of 16 STIS standard stars to ~2µm. These observations include the three primary WD standards that are used to establish the absolute sensitivities of the three grism modes. However in their overlap region at µm, the ratios of the STIS and NICMOS fluxes for brightest/faintest stars disagree by almost 25%. ACS spectrophotometry for two of the same stars in the same wavelength band agrees with STIS to 2%. A comparison of the grism spectrophotometry directly with ACS F850LP and F892N photometry for eight stars again verifies the need to correct the NICMOS grism data for non-linearity. After correction, the NICMOS grism fluxes have uncertainties ranging up to ~3% at 1.7µm. The possible effect of this newly discovered apparent non-linearity on NICMOS photometry is being investigated with new NICMOS photometric observations and by comparisons with independent IR data sets. Operated by the Association of Universities for Research in Astronomy, Inc., for the National Aeronautics and Space Administration

2 1. Introduction In order to extend the wavelength coverage of the HST spectrophotometric standard star network (eg. Bohlin & Gilliland 2004, Bohlin, Dickinson, & Calzetti 2001), a set of stars ranging in brightness from the V=9.5 Sloan standard BD to V~16 has been observed with the NICMOS grisms G096 and G141. A few of the brighter stars have G206 observations, as does the supplemental star HD observed by Gilliland out of its planetary eclipse phase. Table 1 lists the program stars. Section 2 details the extraction of the spectra from the images; Section 3 explains the flux calibration, which is based on the three primary standards GD153, GD71, and G191B2B (Bohlin 2003); Section 4 explains the non-linearity problem; and Section 5 compares the linearity corrected results with the WD models. A model for the non-linearity is suggested in Section 6. Table 1. HST FLUX STANDARDS WITH NICMOS G096 and G141 Data R.A. Dec. Sp. T. V Comment (J2000) (J2000) I. Fundamental Pure Hydrogen WD Primary Standards G191B2B* DA Primary WD Std GD DA Primary WD Std GD DA Primary WD Std II. Secondary Standards P041C G0V Bright Solar Analog P177D G0V Bright Solar Analog P330E* G0V Bright Solar Analog C G Faint Solar Analog SF A G Faint Solar Analog SNAP-2* G Faint Solar Analog SNAP-1* WD 15.6 Faint WD WD DA Faint WD no STIS G750L WD DA Faint WD VB8* M Cool Star 2M L Cool Star 2M T5 I=19.14 Cool Star III. Bright Stars HD209458* G0V 7.65 Non-eclipse data BD+17D4708* sdf Sloan Standard * G206 data also available

3 The observations were obtained primarily in programs 9998 and Spectra are dithered at 15 positions spaced by pixels in the NIC3 detector y- coordinate using a portion of the detector that is relatively free from blemishes. 2. Spectral Extraction and Wavelength Assignment Starting with the standard output of the STScI calnic-a pipeline, i.e. <rootname>_cal.fits file, the IDL routine CALNIC_SPEC extracts the spectrum at one dither position and assigns wavelengths according to the following procedures. The top level routine NIC_PROCESS finds the location of the target star in the direct image and calls CALNIC_SPEC repeatedly for each of the dither positions. The _cal files have the dark current subtracted by the DARKCORR step of the pipeline processing; but no flat fielding is applied, because a wavelength dependent flat field is required later in the data reduction. 2.1 Additional Data Quality Flagging. The data quality flags from the pipeline flat field file are propagated to the extracted spectrum. In addition, the following pixels (x,y) are flagged as hot (value=32) in the data quality array, where x is the first axis of the image, y is the second axis, and (0,0) is the position of the first image pixel. (119,95) (120, 82) (167, 131) (85,50) 2.2 Wavelength Assignment For a typical NICMOS grism image illustrated in Figure 1, wavelengths in microns are computed as a function of the image column (x) by: λ = a0 + a1( x xstar) (1) using the dispersion coefficients (Thompson 2002) and the wavelength ranges in Table 2. xstar is the x centroid of the star in the camera mode of the undispersed reference image. 3

4 Table 2 Wavelength Dispersion Coefficients Optical Element a 0 a 1 λ min λ max G G G Spectral Location The location of the center of the spectrum in the cross-dispersion direction (y) is found by dividing the image columns from λ min to λ max (Table 2) into column bins of size BINSIZE (default is 15 columns per bin). A cross-dispersion profile, P i (y), is determined for each column bin, i, by taking the average of all columns at each y position after applying a one dimensional 7 point median filter to each row of the image to eliminate bad pixels of all columns within the bin at each y position. The y-center of the bin is computed as the centroid of the central portion of the profile by ignoring the wings that fall below 25% of the peak value. The x-center of the bin is the middle column number of the bin. A linear least squares fit to the x and y centers of the column bins gives the center spectral position in y as a function of x. Y center ( x) = c 0 + c 1 x (2) where c 0 and c 1 are the coefficients of the least squares fit. 2.4 Background Subtraction Before any flat fielding is done, an upper background value, Bupper(x), is computed for each image column by taking the median image value of the pixels in BWIDTH rows (default=13) centered UBDIST pixels (default=15) above the center of the spectrum (Equation 2 rounded to the nearest pixel). The process is repeated to give the lower background, Blower(x), at a distance of LBDIST pixels below the center of the spectrum. Generally, UBDIST=LBDIST. The background BACK(x) is computed as the average of Bupper(x) and Blower(x). This background is smoothed in the x direction using a median filter (default width=7) followed by a mean filter done twice (default width=7). The values of the smoothed background, SBACK(x), are then subtracted from all values in the corresponding image column, x. Because no flat field is applied before the 4

5 background is computed and subtracted, the results are susceptible to errors that might be caused by curvature of the true background signal over the range of +15 to -15 pixels above and below the spectral trace. However, even for the faintest star WD , any G096 error due to background shape or nonlinearity is less than 1% of the final net counts/sec. 2.5 Flat Fielding The image values are flat fielded using the available NIC3 narrow-band SM3b flats in Table 3 that are distributed with the NICMOSLOOK package and are also available from the STScI data archive. After background subtraction, the remaining signal is entirely from the dispersed grism spectral image; and each pixel value is then divided by a wavelength dependent flat field value linearly interpolated from the flat field images in Table 3, where the wavelength of the pixel is given by Equation 1. If the wavelength value is less than or greater than the range of wavelengths tabulated in Table 3, then the value of either the first or last flat field is used, i.e. the flat fields are not extrapolated. Table 3 Wavelength Dependent Flat Field Files Wavelength (microns) File _F108N_STEP16_1On-AllOff_sflt.fits _F113N_STEP16_1On-AllOff_sflt.fits _F164N_STEP16_1On-AllOff_sflt.fits _F166N_STEP16_1On-AllOff_sflt.fits _F187N_STEP16_1On-AllOff_sflt.fits _F190N_STEP16_1On-AllOff_sflt.fits _F196N_STEP16_1On-AllOff_sflt.fits _F200N_STEP16_1On-AllOff_sflt.fits _F212N_STEP16_1On-AllOff_sflt.fits _F215N_STEP16_1On-AllOff_sflt.fits _F240M_STEP2_1On-AllOff_sflt.fits 2.6 Extraction of the Spectrum The net spectrum is extracted from the background subtracted, flat fielded image. For each wavelength (image column), an extraction slit is positioned with a y-center given by Equation 2 (see Figure 1). The default extraction 5

6 height is GWIDTH=4 pixels. With a FWHM of ~2 pixels in the cross dispersion direction, 80-90% of the total signal is included for GWIDTH=4. The extracted net count/sec at each wavelength is a weighted sum of the pixels within the extraction slit. Those pixels that fall entirely within the slit are given a weight of 1.0. Pixels at the ends of the slit are given a weight equal to the portion of their area falling within the slit. The 16-bit data quality value associated with each pixel of the extracted net spectrum flags conditions that occur for any of the pixels in the extraction slit (see Table 2.2 of the NICMOS Data Handbook). 2.7 Outputs of the Extraction Process The results of the spectral extraction are written to a FITS binary table with the following columns: x - x pixel position (image column number) of the extracted value y - Center y pixel position of the extraction slit wave - wavelength (microns) flux - extracted net spectrum (ADU/sec) gross - Spectrum extracted in the same way as the net spectrum except that it is extracted from the input (_cal) image instead of the background subtracted, flat fielded image. back - smoothed background (per pixel) with no flat fielding eps - propagated data quality value err - propagated statistical error xback - x-positions for the background vectors, which extend 5 pixels further in the x direction than the gross spectrum, so that smoothing is possible closer to the ends 6 Gwidth Slit centered to fractional pixel. End points weighted by area covered by the slit Figure 1: Spectral Extraction

7 blower - unsmoothed lower background spectrum from _cal image bupper - unsmoothed upper background spectrum from _cal image 2.8 Spectra Coaddition IDL Routine, NIC_COADD, registers and coadds the spectra from multiple dither positions and/or visits starting with the output data files of CALNIC_SPEC from Section 2.7 using the following processing steps Wavelength Registration Wavelengths of all the spectra are registered to the wavelengths of the first of the 15 dither positions by cross-correlation. Prior to cross-correlation, any data points with a bad data quality (points with any of the last 9 bits of the data quality flag not equal to 0) are replaced with the previous good data value. In practice, these cases are just the hot pixels (32) and the grot (16) flags. If any of the computed cross-correlation offsets are greater than 1 pixel, the data are considered too noisy for cross-correlation and left unregistered, because the offsets for brighter stars are less than 0.5px. For strong signals, the computed offsets are accurate to ~0.1px because of the strong wavelength dependent structure imposed by the interference filters used for limiting the bandpass coverage of each of the three grism modes Pixel Response Function (PRF) The response of the NICMOS detectors varies within a pixel. Therefore, the recorded signal extracted for each column depend on the distance from the center of the spectral trace to the center of a pixel in the cross dispersion direction, mainly because the intra-pixel gradient in response for the central pixel effects its integral response over the rapidly varying PSF in the crossdispersion direction. This second order effect is strongest at the shorter wavelengths, where the PSF is sharpest, and diminishes toward longer wavelengths, where the diffraction limited PSF is broader. The PRF affects only the pixel-to-pixel scatter; and applying the derived correction results in slightly 7

8 improved S/N. The correction for this intra-pixel sensitivity variation is modeled as F cor P F = (3) P1 Δy + P2 Δy + P3 Δy + P4 Δy where F is the uncorrected count rate, F cor is the corrected count rate, Δy is the distance from the center of the spectrum (Equation 3) to the center of the pixel closest to the spectral trace; and P i are polynomial coefficients. The values of P i are determined by reducing all (or selected stars) at all dither positions without the PRF correction. The ratio of each of the 15 dithered fluxes to the average flux is computed for all stars at all wavelengths. The polynomial coefficients are defined by a least squares fit of these ratios versus Δy. Figure 2 is an example of the PRF for G096. Figure 2 - The pixel response function for G096 and GWIDTH=4 versus the delta Y from a pixel center for all stars. The zero pixel position is defined by the crossdispersion profile centroid, which is offset from the peak response at ~+0.2 pixel 8

9 because of asymmetry in the profile. The correction is always less than 5% for all three grism modes Spectral Registration and Co-addition Spectra are linearly interpolated to the wavelength scale of the first observation using the wavelengths computed in Section 2.2 and then averaged. Points with a bad data quality (i.e. any of the last 9 bits of the data quality flag not equal to 0) are ignored in the co-addition. If all data points for a given wavelength are bad, all values are used and the output flux value is flagged as bad by setting Npts=0. This process is repeated for the gross and background spectra Output Coadded Spectrum The results are written to an ASCII file with the following columns. Wavelength - wavelengths (microns) Gross - Average gross spectrum extracted from the image before background subtraction or flat fielding Back - Averaged smoothed background spectrum (per pixel) extracted from the image before background subtraction or flat fielding Net - Averaged net spectrum after the wavelength dependent flat fielding Stdev - standard deviation of the coadded net data values Stat Error - propagated statistical errors Error Mean - Stdev divided by the square root of the number of points averaged Npts - number of data points averaged. 3. Flux Calibration The sensitivity values are computed for every pixel of the three grism modes as S=Net/Flux(star), where Net is the observed count rate in ADU/sec and where the flux distributions are for the three primary WD standards, GD71, GD153, and G191B2B (Bohlin 2003). The model fluxes are smoothed to the instrumental resolution with a box width equal to the wavelength spacing 9

10 of two pixels in the observed spectrum. Average sensitivities are computed for G096 and G141, while only G191B2B is bright enough for G206 observations. The instrumental signature has such a strong wavelength dependence that no smoothing can be applied to S as a function of wavelength. Thus, the mean sensitivity is a spline fit to the S values for all three stars as a function of wavelength, where the number of spline nodes is equal to the normal number of extracted wavelength points, i.e. 76 for G096, 116 for G141, and 106 for G206. For ease of use in flux calibration routines, the final sensitivity files are the spline fits evaluated on a uniform wavelength grid of 500 points covering the wavelength range of each grism. Sensitivities for individual observations are computed by sens.pro, while the fitting of spline nodes to the average of multiple observations is done by sensall.pro. 4. Apparent Non-linearity 4.1 Comparison with STIS Fluxes The wavelength coverage of the NICMOS G096 and the STIS G750L overlap from 0.8 to 1µm. However, there is a disagreement between these two independent sets, as illustrated in Figure 3. The response versus the input count rate is not the same for the two instruments, which suggests that either the STIS or the NICMOS detected signal is not a linear function of the stellar brightness. This apparent non-linearity is in the same sense as reciprocity failure for film but is in the opposite sense of the well-characterized non-linearity associated with accumulation of charge in the individual NICMOS pixels. The NICMOS pipeline corrects for the loss of signal due to this limited charge capacity; but the size of this correction is always less than ~ 5% and the uncertainty should be <1%. The STIS data have been corrected for CTE (Bohlin & Goudfrooij 2003) and for changing sensitivity with time (Stys, Bohlin, & Goudfrooij 2004). There is some evidence that for the faintest stars, the STIS CTE correction is slightly too large for these recent observations near the long wavelength limit at µm illustrated in Figure 3. Therefore, a pure hydrogen model atmosphere is fit to the shorter wavelength STIS fluxes and used in lieu of the actual STIS observations for WD and WD The other faint stars are not used in the least square fit illustrated, so that the difference between the fit and 10

11 the small squares are the typical STIS error of 3-4% for these stars that approach the STIS faint star limit. The issue of accuracy of the current STIS CTE correction will be investigated as part of the STIS final closeout calibration. To help determine whether the NICMOS or the STIS data are primarily responsible for the non-linearity illustrated in Figure 3, the STIS fluxes for two stars are compared to grism observations taken with the HRC in ACS in 2002, when any CTE is <1% for the ACS CCD cameras. The agreement to ~2% of the ACS and STIS count rates for GD153 compared to BD suggests that the NICMOS grism observations do not produce a response that is exactly in proportion to the stellar fluxes over the dynamic range of ~10000 in Figure 3. The ACS points in Figure 3 are plotted at the x location of the NICMOS points for the two stars. The y location for GD153 is normalized to unity, so that the y value of 0.98 for the BD point indicates that the ratio of the µm bandpass fluxes of BD /GD153 for ACS is only ~2% lower than for STIS. 11

12 Figure 3 - Big open squares and least square solid line fit Ratio of NICMOS grism fluxes to the STIS measurements averaged over the µm overlap range. The units of the abscissa are defined following Equation 4. For the two faint WD stars, pure hydrogen models are a more reliable estimate of the true flux and replace the STIS observations in the comparison. There is a non-linearity of 5.6% per dex or a total of 23% over the 4 dex dynamic range in observed response. The repeated NICMOS observations for BD , G191B2B, and GD71 agree to <1%. Small open squares Observations NOT used for assessing the linearity. Of the six faintest stars, only the two WD stars with good models are used for the fit, because the STIS fluxes seem to be systematically overcorrected for CTE by a few percent. The bright star HD was observed with NICMOS in a defocused mode. Small filled squares connected by a dashed line ACS grism fluxes compared to STIS in the same µm band. Over a dynamic range of ~100x between GD153 and BD , the CCD detectors on STIS and the HRC in ACS measure the same relative flux to within 2%. Apparently, the NICMOS HgCdTe detector does not respond proportionately to the stellar flux. Laboratory testing is required to verify the linearity of this type of detector to ~1% over their many dex dynamic range. 12

13 4.2 Non-linearity Correction To investigate the evidence for non-linearity as a function of wavelength, an estimate of the true stellar fluxes is required at wavelengths beyond the STIS limit of one micron. Two stars WD and WD have the same unreddened, pure hydrogen pedigree as the three primary WD standards. After normalization to the visible STIS fluxes, models with T eff and log g of 40500,7.9 and 45000, 7.8, respectively, represent the true IR flux of these stars to ~1% with respect to the three primary WDs that define the NICMOS flux calibration. Figure 4 shows the comparison of the calibrated NICMOS flux for G191B2B with its model to the same ratio for each of the two fainter WDs. The fractional errors are divided by the observed differences in dex between G191B2B and the fainter star to produce the same %/dex units shown for the slope in Figure 3. These slopes, b, are plotted as a function of wavelength for both stars in Figure 4 along with the adopted average slope as a function of wavelength. The correction is applied to the extracted Net spectrum as a function of wavelength by the routine nicflx.pro as Net( obs) Net ( corr) =, (4) Gross 1+ blog 100 where Gross is the extracted spectrum as a function of wavelength with no background subtraction and where b from Figure 4 must be converted from percent to a fraction, e.g. b=0.056 at one micron. The 100 in Equation 4 normalizes the correction to unity for 100 ADU/sec, which is a typical Gross response for G191B2B. Beyond 1.7µm, no correction is applied. 13

14 Figure 4 - NICMOS non-linearity correction, b, as a function of wavelength. Small symbols connected by dotted or dashed lines are from a comparison of WD models with observations of WD or WD , respectively. These errors are relative to the bright primary WD standard G191B2B, which is the reference for the brightness difference in dex units. Large filled circles connected by a bold solid line are the adopted corrections to the NICMOS spectrophotometry, where the long wavelength points are hand fit. The four short wavelength circles are from comparisons with STIS fluxes as in Figure 1, except that the µm bandpass is divided into four equal bins. 4.3 Additional Confirmations of the Non-linearity Correction Because advance expectations were that the NICMOS grism data should be perfectly linear, the following details have been investigated. 14

15 Curvature in the non-flat fielded background subtraction over the region between the upper and lower background areas causes <1% NICMOS flux errors. The non-linearity still appears for the brighter stars, even for no background subtraction. The results are independent of the GWIDTH extraction height, e.g. the count rate ratio for Snap1/ BD is the same to <1% for heights of four and eight pixels. The same results are obtained using the independent NICMOSLOOK spectral extraction package developed at the ECF by W. Freudling. To provide a blind test for subtle errors in the IDL spectral extraction software, artificial data were created by E. Barker and S. Malhotra. The observations of the bright star BD were scaled down by factors of and and added to the higher background images derived from the GD153 observations. Both factors are recovered exactly from the extracted fake data sets. After the first few non-destructive readouts in the sample sequences, the net differential count rates (from the _ima files) in the time interval between reads settles to the final cumulate net rate (from the _cal files) to within 2%. The spectra overlap between dither positions and are susceptible to persistence; but the first dither positions show no systematic deviation. The best verification of the grism non-linearity is via a comparison with ACS F850LP and F892N photometry in the overlap region with the G096 NICMOS spectra. Any correction for ACS CTE is <~1% (Riess & Mack 2004). Four faint stars in the G191B2B field and one in the GD71 field have ACS photometry and can be directly compared with their spectrophotometry extracted from the same data obtained for the primary targets G191B2B and GD71. The ratio NICMOS/ACS for these five faint stars and three brighter stars is illustrated in Figure 5. The dominant source of uncertainty is the repeatability of the spectrophotometry in the crowded field, which reaches ~4% for the faintest star, G191B2B-b. For the brighter stars, systematics, such as flat fielding errors dominate; and a minimum uncertainty of 1% is assigned to ACS and to NICMOS, which produces a minimum error bar of ±1.4% on the ratios in Figure 5. The synthetic 15

16 F850LP photometry is derived from the spectrophotometry omitting the 60Å bandpass shift from Bohlin and Gilliland (2004). Including the 60Å shift makes the slope of the fits ~0.4 steeper, which provides an estimate of the uncertainty due to errors in the bandpass function. The slope of the apparent non-linearity ranges from 5.4%/dex for HRC to 6.4%/dex for WFC, which is consistent within uncertainties of the slope of 5.6%/dex illustrated in Figure 3. Figure 5 - As in Figure 3 for the ratio of NICMOS synthetic photometry from the uncorrected grism flux distributions to actual ACS photometric count rates for eight stars. The ratios are normalized to unity for the primary standard G191B2B. The two weighted linear fits are to the red (HRC) and blue (WFC) F850LP points only, because the narrow band F892N synthetic photometry (green points) has larger uncertainties. The trends are consistent with the slope of the non-linearity shown in Figure 3. 16

17 5. Results The grism spectral extraction software has been verified by several checks. The non-linearity of these grism spectra appears in comparisons to STIS, to ACS photometry, and to ACS grism spectrophotometry. Thus, the existence of a significant non-linearity in the NICMOS grism data must be considered well established. Remaining work includes comparing the grism spectrophotometry to NIC3 photometry; and the question of whether all three NICMOS cameras have the same linearity must be answered. The comparison of NICMOS photometry with ground-based photometry is of indirect interest, because ground based data is normally less precise than HST photometry, although this deficiency is ameliorated in larger data sets and for data sets covering a larger dynamic range than the ~10,000_ (10mag) shown in Figures 3 and 5. Preliminary comparisons of NICMOS to ground based data sets for stars and for galaxies by do not seem to show as much non-linearity as found by the direct comparisons of grism spectrophotometry to ACS and STIS. After correcting for non-linearity per Equation 4, the precision of the NICMOS flux distributions can be assessed from the residuals of a comparison of the calibrated observational spectra with the WD models, as illustrated in Figure 6. For the three primary WD standards with V magnitudes of 11.8 to 13.3, the residuals in the bottom three panels are generally <1%. For the two fainter WDs in the top two panels, WD at V=14.8 shows residuals as big as 3%, while the residuals for the faintest star WD at V=16.1 are dominated by noise. Additional observations of WD are planned, while another observation of WD is required to ascertain whether the ~3% bump at µm corresponds to a repeatability uncertainty or whether that rise in the apparent flux above the model for this faint star is indicative of a reversal of the sign of the non-linearity correction, as suggested by Figure 4. 17

18 18

19 Figure 6 - Residuals of the calibrated NICMOS fluxes for G096 and G141, i.e. the ratio of the flux calibrated observations to the standard star fluxes that are defined by pure hydrogen model atmospheres. The average ratio and RMS scatter of the residuals are written on each panel. The bottom three panels show residuals for the three primary standards, where the average of the three residuals is unity at any wavelength, because the flux calibration is defined by these three stars. Any systematic deviation from unity is <~1% for all three primary standards. The upper two panels show the faint WD stars, where noise dominates the point-to-point scatter for WD The systematic residuals of up to +3% for WD may be indicative of the repeatability for faint sources. 6. Interpretation of the Apparent Non-Linearity in Terms of Charge Trapping A quantitative comparison of NIC3 F110W and F160W photometry of faint sources in the UDF with ground-based observations of the same sources (using ISAAC, an InSb detector operated in sky-dominated mode) shows excellent agreement between the NICMOS and ground over a dynamic range of ~10 astronomical magnitudes (Mobasher and Riess 2005). However, a key difference from the grism observations appears to be the length of the exposure time in the UDF observations, which are ~25 min, while the grism integrations are typically in the 1-3 min range. In a separate study, A. Riess (2005) shows that intermediate time-scale trapping and the associated de-trapping seen by Bergeron and Dickinson (2003) with a 155 sec time-constant explains both the apparent non-linearity in the grism data and the linearity of the UDF photometry. For short exposures of less than ~155 sec, there will be an apparent net loss due to trapping before the charge is released and detected. This net loss will gradually abate as the exposure time exceeds the time constant for de-trapping and charge is re-emitted at the same rate it is lost. Continued exposure time will reduce the fractional loss to the source as additional charge is accumulated at the proper rate. Evidence supporting this explanation is the appearance of a smooth rise in the apparent count rate in time intervals of less than 155 sec in the non-destructive reads. 19

20 In the Riess study, the intermediate reads in our NICMOS grism data and also in long-exposure photometric observations (from GO 9353) show a count rate deficit at shorter exposure times. Most observations obtained for science will not be strongly affected by this effect, because the integration times are significantly longer than the 155 second e-fold time or because the source count rates are sufficiently high that the fraction of charge lost to traps is negligible. Scientific observations with relatively short integrations of faint sources will be most vulnerable. REFERENCES Bergeron, E., & Dickenson, M. 2003, Instrument Science Report, NICMOS , (Baltimore: STScI) Bohlin, R. 2003, 2002 HST Calibration Workshop, ed. S. Arribas, A. Koekemoer, and B. Whitmore, (Baltimore: STScI), p. 115 Bohlin, R. C., Dickinson, M. E., and Calzetti, D. 2001, AJ, 122, 2118 Bohlin, R. C., & Gilliland, R. L. 2004, AJ, 128, 3053 Bohlin, R. & Goudfrooij P. 2003, Instrument Science Report, STIS 03-03R, (Baltimore: STScI) Mobasher, B., & Riess, A. 2005, Instrument Science Report, NICMOS , (Baltimore: STScI) NICMOS Data Handbook 2004, v. 6.0, part II, (Baltimore: STScI) Riess, A., & Mack, J. 2004, Instrument Science Report, ACS , (Baltimore: STScI) Riess, A. 2005, Instrument Science Report, NICMOS in preparation, (Baltimore: STScI) Stys, D. J., Bohlin, R. C. & Goudfrooij, P. 2004, Instrument Science Report, STIS , (Baltimore: STScI) Thompson, R. I. 2002, Preliminary NICMOS Grisms Recalibration, memo submitted to STScI 20