1. NICMOS Calibration Challenges in the Ultra Deep Field Rodger Thompson Steward Observatory University of Arizona

2. Observational Data NICMOS Hubble Ultra Deep Field NICMOS 2 bands in Camera 3  F110W  F160W Covers 5.4 sq. arc minutes of the HUDF 5  AB source mag. ~28.2 NICMOS, ~29.5 ACS  Assumes a source covering 20 pixels. Treasury Catalog Produced  Thompson et al. 2005, AJ, 130, 1

3. Challenges 1  = 4.6x10 -9 Jy 1e = 2.9x10 -7 Jy 1  signal is 1 detected photon every 450 s 3 detected photons per integration Less than ½ an ADU per integration Sky signal is 1 photon/s 144 integrations in each filter Integrations separated into 2 epochs with different orientations

4. Approaches Dedicated Dark Frames Quadrant Bias Removal More Aggressive Bad Pixel List “Warm” Pixel Removal Techniques Median Background Subtraction SAA Avoidance Only through the grace of the schedulers Visual Inspection

5. Dark Frames A dark integration was taken during the occultation period after each observation. A median dark for each sample was produced from these darks The median dark samples were subtracted from each observation sample.

6. Dark Frame Issues The dark structure magnitude is much larger than almost all signals in the UDF The structure is temperature dependent Incorrect subtraction can lead to photometric errors The NICMOS Cooling System set point was changed during the program

7. Bad Pixels Standard bad pixels have less than 10% response or dark currents that saturate in 1000 seconds. The UDF images showed a pattern of pixels that did not satisfy the standard criterion but produced consistently bad signals. These pixels were declared bad which increased the bad pixel count from 170 to 1,012.

8. “Warm” Pixels “Warm” pixels have elevated dark current rates which are removed by the dark subtraction to a level sufficient for most programs. Their dark current varies slightly with temperature, but at a level that is significant compared to the UDF signal level. They appear as singular bright or dark pixels in the image depending on whether the dark current for that image is above or below the average.

9. “Warm” Pixel Removal The well known NICMOS PSF was used to identify the maximum contrast that can occur between pixels in response to a centered point source. In a single image a pixel value was declared bad if three criteria were all met. Its value was greater than the 3  noise value Its contrast relative to the 8 surrounding pixels was higher than the expected maximum contrast The average value of the surrounding pixels was less than a preset number of .

10. Quadrant Bias Removal Quadrant bias is a dc offset of the voltages of all pixels in a detector quadrant. Application of the flat field correction multiplies the offset by the flat field pattern. The NICMOS flat field function has very significant power, although less than during the cryogenic era of operation.

11. Removal Procedure Procedure was developed by Mark Dickinson and is described HST NICMOS data handbook. (Mobasher et al. 2004). A range of dc offsets are subtracted and added to the image. For each offset the fluctuation of the signal is measured and the proper offset is the one that gives the minimum fluctuation. Fluctuation is measured by the FWHM of the gaussian distribution of pixel values.

12. Fluctuation Distribution

13. Pixel Value Distribution

14. Background Subtraction The primary source of background is zodiacal emission. The background is determined by a median of all of the images in a band. The median background is then subtracted from all of the images. The first and second half images have different medians since the zodiacal emission changes with the earth’s position.

15. SAA Persistence Many thanks to Beth Perriello for a beautiful job of scheduling. Not a single image suffered from SAA persistence. SAA persistence correction methods have been developed at STScI.

16. Visual Inspection All 288 individual images were inspected for anomalies. Primary anomalies Massive cosmic ray events Moving objects through the field of view Random bad pixels that escaped correction but were clearly anomalous (few).

17. Masks Anomalous areas were masked and their weight set to zero. All masks are available from MAST A generic mask masked out the bottom 15 rows where there is slight vignetting and small region in the upper right corner with high QE variations.

18. Photometric Accuracy Absolute photometric accuracy is ~5% over most of the image. Dithering smoothed out QE variations and mitigated intra pixel QE variations. Comparison to VLT ISSAC data at the bright end by Bahram Mobasher found no photometric anomalies.

19. Conclusions Production of very deep images of faint objects requires procedures not needed for most observations. Very small effects become large relative to the very faint signal levels. It is worth the work.

20. Implications Any isotropic, uniform background other than the zodiacal emission will also be subtracted by this procedure. The existence of a near-infrared isotropic background is being investigated in the original images. Current limits appear to be significantly lower than many claims.