1. 149.03 S. Baggett, J. Anderson, K. S. Long, J. W. MacKenty, K. Noeske, J. Biretta, and the WFC3 team (STScI) WFC3 : Understanding and mitigating UVIS charge transfer efficiency losses and IR persistence effects Abstract A panchromatic instrument, Wide Field Camera 3 ( WFC3 ) contains a UVIS channel with a 4096 x 4096 pixel e2v CCD array as well as an IR channel with a 1014x1014 Rockwell Scientific HgCdTe focal plane array ( FPA ). Both detectors have been performing well on-orbit since the installation of the instrument in the Hubble Space Telescope ( HST ) in May 2009. However, as expected, the harsh low-earth orbit environment has been damaging the UVIS CCDs, resulting in a progressive loss of charge transfer efficiency ( CTE ) over time. We summarize the magnitude of the CTE losses, the effect on science data, and the pre- and post- observation mitigation options available. The IR FPA does not suffer from accumulating radiation damage but it does exhibit persistence i.e. an after-glow from sources in previous exposures, an anomaly commonly seen in these types of IR arrays. We summarize the characteristics of persistence in WFC3, suggest methods for reducing the effects during observation planning, and describe the calibration products which are available via the Mikulski Archive for Space Telescopes ( MAST ) for addressing persistence in IR science data. Summary of mitigation strategies  Place small targets close to readout amp.  Ensure sufficient image background (e.g. broader filters, longer exposure times and/or post-flash).  Apply formulaic corrections to aperture photometry results.  Correct images using pixel-based image correction.  Keep exposure levels significantly below saturation.  Dither whenever possible.  Avoid dithering bright objects across regions on the detector where targets of interest will fall.  Group exposures with saturated sources at the end of the visit.  Check if persistence is an issue using MAST.  Evaluate archival persistence products: use them to mask areas of persistence or (with caveats) analyze the persistence- corrected products directly. References and further information \  WFC3 : www.stsci.edu/hst/wfc3 STScI general help desk: help@stsci.eduwww.stsci.edu/hst/wfc3help@stsci.edu  UVIS CTE : www.stsci.edu/hst/wfc3/ins_performance/ CTEwww.stsci.edu/hst/wfc3/ins_performance/ CTE  IR persistence: http://www.stsci.edu/hst/wfc3/ins_performance/persistence/http://www.stsci.edu/hst/wfc3/ins_performance/persistence/  Anderson, J., & Bedin, L., An Empirical Pixel-Based Correction for HST/ACS, PASP 122, 1035, 2010.  Baggett, S., & Anderson, “WFC3/UVIS Sky Backgrounds ”, WFC3 ISR 2012-12.  Long et al., “Characterizing persistence in the IR detector ”, Proc.SPIE, 8442, 84421W-9, 2012.  Noeske, K., et al., “ WFC3/UVIS CTE Monitor Results ”, WFC3 ISR 2012-09.  Massey, R., et al., “Pixel-based correction for Charge Transfer Inefficiency in HST/ACS ”, MNRAS 401, 2010.  Smith, R., et al., Proc. SPIE Vol 7021, 7021J, 2008. 1) Distance from amplifier: more transfers=more traps 2) Signal level: higher fractional loss in faint sources 3) Image background: higher background fills traps 4) Observing scene: sources preceding target source can fill traps and improve charge transfer CTE in the UVIS  HST’s low-earth orbit environment damages CCDs, generating new hot pixels, increasing dark current, & decreasing CTE.  The decline in CTE reduces detected source flux as defects trap and release charge during readout. Flux losses depend on: Ensure sufficient background Fig 2. Measured flux losses as a function of background level, faint and bright sources (top, bottom panels), and distance from the amplifier ( X axis). A higher image background reduces CTE losses. Fig 1. Traps capture and release charge during readout, generating trails above the sources (middle panel). A modest amount of background can reduce CTE losses. ‘truth’ imageNo background16e- background Apply formulaic corrections Fit coefficients can be used to estimate CTE losses or correct photometric results. Fig 3. CTE losses as a function of observation date and source flux fit with 2-parameter polynomials (lines). Image backgrounds are worst-case: 1-2 e-/pixel. Fig 5. Traps in the IR detector cause after-images (left panel) due to bright objects in prior data. Exposure to light changes voltage levels, trapping charge which is released during later image readouts (Smith et al. 2008). Right panel shows the same image after a persistence correction (see discussion below).  Flux losses range up to ~50% for faint sources on faint backgrounds, ~5-15% for more typical sources/backgrounds. Perform pixel-based correction Fig 4. WFC3 image subsections farthest from the amplifier before (top) and after (bottom) CTE correction. Further refinements of the model are in progress. Plans are to incorporate the code into the calibration pipeline in 2014. The CTE correction works well but the nature of the algorithm is such that it can not completely recover what was lost, particularly at the faintest levels. To avoid amplification of read noise, the algorithm is conservative in its reconstruction at the low background levels where losses are non-linear. A standalone version of the pixel-based CTE correction software is available for download from the WFC3 CTE page. Fig 7a. The MAST History page can be used to determine whether persistence is a problem. Fig 6. Amplitude and duration depend on exposure levels of, and time elapsed since, the preceding images. The effect is low for signals < ~half saturation but reaches 0.3-0.5 e-/s ~1000s after 2x–20x saturation. The decay time follows a power law (slope ~ -0.9). Repeat exposures (no dithering) show stronger and longer-lived effects. Persistence in the IR Full-well (~75ke-) Fig 7b. An estimate of persistence for every science image is in MAST. Results are based on a model of persistence as a function of time since, and exposure level of, the brightest preceding exposure (Long et al., 2012). Products include a list of prior exposures, the number of saturated pixels they contain, a map of the persistence, and a persistence-corrected flt file. Check persistence products Make use of the persistence output files. The model may not work well in all situations. Rescaling the persistence map and subtracting it from the pipeline flt file can improve the results. For assistance please email help@stsci.edu. WFC3/UVIS CTE losses especially for faint targets can be significantly reduced by ensuring images contain a minimum of 12 e- total background (dark + sky + post-flash if needed). Hot pixels in dark frames are used to empirically model CTE losses on a pixel-by-pixel basis (Massey 2010; Anderson & Bedin, 2010). The model is applied to science images to restore charge to its original location within the image.