The effect of hot pixels, about 1000 new/day/chip using a threshold of 54e-
/hr/pix, is addressed with anneal procedures, dark calibration files, and dithering. The anneal procedures, performed monthly, warm the detectors to +20°
C and restore 20-30% of the hot pixels to their original levels. Dark calibration files (running averages of daily dark images) can provide reasonable identification of hot pixels as well as a calibration for overall dark current (see Section 5.4.8
for the median level and growth rate). The calibration darks allow hot pixels and dark current to be subtracted from science images in the calibration pipeline. Due to the time-variable behavior, the corrections are imperfect, but the dark current levels are low and dithering can help reduce any residual impact of hot pixels in final image stacks.
1) Consider the placement of the target within the field of view
. For example, when possible, place a target close to a readout amplifier - a viable option when the target is small. This reduces the number of transfers during readout, thereby minimizing CTE losses. Naturally, this will only be appropriate for a small subset of programs but should also be considered e.g. for observations of compact targets where the scientific interest in the surrounding field is limited or where inferior CTE for those surrounding observations is acceptable. If the region of interest is sufficiently small, a subarray aperture can be used. (See Figure 6.2
.). Subarray apertures UVIS2-C1K1C-SUB and UVIS2-C512C-SUB (see Table 6.1
) place the target 512 and 256 pixels, respectively, from the edges of the UVIS detector near amplifier C. However, where possible, observers should use full frame exposures for the value they can add to the observing program and the archive. Note that the observing efficiency of full frame exposures greatly increases for exposure times longer than 347 sec, since data dumping can then be done in parallel to taking exposures (see Section 10.3.1
). Starting in cycle 23, observers can use the apertures UVIS2-C1K1C-CTE and UVIS2-C512C-CTE to place the target at the same reference positions as UVIS2-C1K1C-SUB and UVIS2-C512C-SUB, respectively, and read out the full detector. POS TARGs can also be used to move the target to the lower part of the C quadrant (e.g., negative POS TARG X and negative POS TARG Y in aperture UVIS-CENTER) to reduce CTE losses. (See Section 6.4.4
for reasons to prefer quadrant C over the other quadrants.)
2) Increase the image background by lengthening exposure times, using a broader filter, and/or applying an internal background (post-flash)
. Ensuring that images with faint sources contain a minimum of 12e-/pix background is expected to be a key CTE mitigation strategy for many WFC3/UVIS science proposals in 2012 and beyond. Starting in Cycle 23, APT has provided a quantitative warning message in the Diagnostic Report if more or less FLASH appears to be needed on an exposure.
On-orbit testing has shown that CTE losses are a non-linear function of both the source and image background signals: a faint source in a low-background (<12 e-
) image will lose a significantly larger proportion of signal than a similar source in a high-background image. In some cases, faint sources can even disappear completely during the readout transfers, as illustrated in Figure 6.18
(Anderson et al. 2012
). The left panel is the result of a stack of long exposures minimally impacted by CTE losses, i.e., effectively truth’ image. The middle panel presents the result of a stack of short, very low background exposures; the CTE trails are clearly visible above each source and the charge traps have completely smeared out the signal from the faintest sources (e.g., A and D). The right panel is a stack of short exposures where each image had ~16 e-
total background. The CTE trails have been reduced considerably and stars lost in the stack of very low background images are recovered in the stack of higher-background images, a clear qualitative demonstration of how a small amount of background can preserve even small charge packets of signal.
A more qualitative measure of how relatively low levels of background can significantly improve the CTE and increase the S/N of very faint sources is presented in Figure 6.19
. Shown are aperture photometry results for faint stars in very low background (top row) and higher-background data (bottom row), as a function of the number of transfers, i.e., distance from the amplifier. The target sources are faint: 100, 50, and 10e-
total in a 3x3 pixel aperture from left to right. Sources far from the amplifiers (~2000 on the x-axis) in images with little background (top row) effectively disappear. The same faint sources embedded in images with slightly higher background are detectable at the 50-75% level (Anderson et al. 2012
The required increase in background necessary to provide effective CTE-loss mitigation can sometimes be obtained simply by lengthening exposure times or by using as broad a filter as possible. Sky levels in the UVIS filters are such that with exposure times of 2000 sec or longer, about half the filters will have natural background levels >10e-
(WFC3 ISR 2012-12
). The remaining filters, mostly UV and narrowbands plus some medium band filters, will have relatively low backgrounds and a post-flash is recommended as a means of boosting the total background. While using a post-flash to increase the underlying background in images may seem counter-productive from a S/N perspective, it will significantly increase the CTE for low-level sources and as a result, source signal will accumulate much faster than the noise will increase. Observers with faint sources in e.g. narrowband or UV filters or with science programs requiring the coaddition of multiple images to reach very faint limits should plan to achieve a total
background level of ~12 e-
per exposure. This recommendation represents the optimum value as of late 2012: a balance between the level of CTE mitigation achieved and the additional noise penalty incurred from adding extra background. Note that once backgrounds exceed ~12 e-
/pix, there is minimal improvement in retaining charge from faint sources (Anderson et al., 2012
In order to determine the necessary post-flash level to use for mitigating CTE losses, observers will first need to estimate the expected natural backgrounds. The Exposure Time Calculator
provides such estimates, including contributions from sky, dark, zodiacal light, earthshine, airglow, and a selected level of post-flash. In addition, empirical backgrounds as measured on all WFC3/UVIS frames in the archive are summarized in the Appendix of WFC3 ISR 2012-12
. If the natural background of the exposure will be higher than 12 e-
/pix then there is no need to add post-flash. For images with very low background levels, enough post-flash should be applied to achieve ~12 e-
/pix total background (natural+post-flash).
Observers invoke post-flash in APT by choosing the exposure optional parameter ‘FLASH’ and specifying the desired number of electrons per pixel to be added to the image using the LED post-flash lamp. (See Section 13.2.4 in the Phase II Proposal Instructions
.) The additional overhead times required for post-flash are generally very small (typically ~ 6 sec). The flash is performed on WFC3 after the shutter has closed at the end of the exposure: an LED is activated to illuminate the side of the shutter blade facing the CCD detector (WFC3 TIR 2012-01
). The experience so far with these lamps (corroborated by the design analysis) indicates that the illumination pattern is very repeatable (to <<1%); it is similar for the two sides of the shutter blade. The intensity is likewise very repeatable, as expected. The brightness of the flash has shown fluctuations of rms~1.2%; the long-term stability is ~0.1%. Calibration reference files have been delivered to CDBS for the calibration of exposures using post-flash. (See WFC3 ISR 2013-12
The main disadvantage of post-flash is, of course, the increase in the background noise. In the worst case, a short exposure with low background and dark current would require the addition of about 12 e-
/pix of post-flash. Thus the original readout noise of ~3.1 electrons is effectively increased to 4.6 e-
in un-binned exposures. (See Section 9.6
for S/N equations.) For a noise-limited observation, the exposure time would need to be increased by more than a factor of 2 to retain the same noise floor. In most cases, however, the impact will be significantly less severe as exposures will generally contain some natural background already and will not require a full 12e-
3) Use charge injection.
For completeness, this mode is included as an observing strategy option for CTE-loss mitigation but, in practice
, it is not considered as useful as e.g. increasing image backgrounds or applying corrections during image processing. Its use will be permitted only in exceptional cases where the science requires it. Observers who wish to use this mode are advised to consult their Contact Scientist or e-mail email@example.com
Charge injection is performed by electronically inserting charge as the chip is initialized for the exposure, into either all rows or spaced every 10, 17, or 25 rows. Only the 17 row spacing is supported as of mid-2012. The injected signal is ~15000 electrons (not adjustable) and results in about 18 electrons of additional noise in the injected rows (Baggett et al., 2011
). The rows adjacent to the charge-injected rows have between 3 and 7 electrons of effective noise due to CTE effects. The charge injection capability was supported in Cycle 19, but experience has demonstrated that it is useful for very few types of observations. Its primary drawbacks are the uneven degree of protection from charge trapping in the rows between the injected charge rows, an increase in noise in the rows closest to the injected charge, and a very difficult calibration problem posed by the combination of sources in the field and the injected rows, which give rise to different levels of CTE at different places within the image. Furthermore, the strong dependence of CTE losses on image backgrounds makes it challenging to produce a suitable calibration, as typically there will be a mismatch in image backgrounds between the charge injected calibration and science frames (i.e., differing levels of CTE losses).
1) Apply formula-based corrections for aperture photometry.
One way to correct CTE losses after the images have been acquired is to apply an empirical photometric calibration. The current model, based on stellar aperture photometry results, provides corrections for CTE losses as a function of observation date, image background, source flux, and source distance from the amplifiers. Figure 6.20
illustrates the necessary corrections for low, intermediate, and high background images. As expected, larger corrections are required for fainter sources and/or lower image backgrounds. The top left panel represents the worst-case scenario: in short exposures in the narrowband F502N filter, with effectively zero background, losses exceeded 1 mag for the faintest sources farthest from the readout amplifiers by July 2014. The top right panel shows the that even a background ~1-2 electron per pixel produces a noticeable improvement. Observations were made with the F606W filter until July 2012. A modest increase in the background level (to 2-3e-, bottom left panel) produced a significant improvement in CTE, with corrections of ~25% required for the faintest sources, vs ~55% for a background level of 1 e- on the same date. The losses for high background data (20-30 e-) slowly rose to ~10% for the faintest sources by July 2012 (lower right panel). Losses for the brightest sources are <6% regardless of background level. More details on how the analysis was performed can be found in WFC3 ISR 2015-03
. Note that these results are for small apertures; corrections for larger apertures will be smaller as more of the trailed charge is included in the aperture.
2) Apply the empirical pixel-based correction algorithm.
The ACS team recently developed and implemented a post-observation correction algorithm employing the Anderson and Bedin methodology (2010; PASP 122 1035
). A similar capability has been available for WFC3 from the WFC3 CTE webpage
since mid-2013 and is expected to be implemented in the MAST pipeline in 2016, possibly in the first quarter. (See the article on calwf3
version 3.3 in WFC3 STAN issue 22
.) The algorithm is calibrated using the behavior of hot pixels and their charge trails. In the absence of CTE losses, the full charge of a hot pixel is entirely contained within a single pixel and its noise is the combination of its shot noise and the noise due to readout and background in that one pixel. If some of the hot pixel charge is lost due to imperfect CTE, there will be fewer electrons in the hot pixel itself, and more in the trailing pixels. (see Figure 6.17
.) To obtain the original value of the hot pixel, the correction algorithm must determine how many electrons the original hot pixel would have to have in order to be read out as the observed number, given the number of traps left full and empty by the preceding pixels. The resulting correction essentially redistributes the counts in the image, “putting the electrons back where they belong”, i.e., undoing the effects of degraded CTE (Anderson et al., 2012
While the pixel-based algorithm has been successful at removing trails behind stars, cosmic rays, and hot pixels, it has one serious and fundamental limitation: it cannot restore any lost S/N in the image
. Faint sources, and faint features of extended sources, may be so strongly affected by CTE losses that they become undetectable and cannot be recovered (e.g., see Figure 6.18
and Figure 6.19
). In addition, this pixel-based method is effectively a deconvolution algorithm, and it can amplify noise or sometimes generate artifacts. Even so, despite the limitations, the reconstruction algorithm provides the best estimate of the original image before it was read out and also aids in understanding how the value of each pixel may have been modified by the transfer process.
The pixel-based correction algorithm does not correct for sink pixels, which contain a number of charge traps (WFC3 ISR 2014-19
). They comprise about 0.05% of the UVIS pixels, but can affect up to 1% of the pixels when the background is low. A calibration program to identify sink pixels and pixels impacted by them has been carried out. The strategy for flagging these pixels is presented in WFC3 ISR 2014-22
. Since February 23, 2016, when calwf3
version 3.3 was implemented in the pipeline, sink pixels and their trails have been identified in the DQI array with value 1024 (see Table E.2
Serial CTE losses (along the X direction on the detector) can easily be seen in deep exposures of the point spread function (see Figure 1 in WFC3 ISR 2013-13
). The pixel-based correction algorithm currently corrects only for parallel CTE losses (along the Y direction on the detector). Serial CTE losses affect the X coordinate of bright stars and faint stars at the level of 0.0015 pixels and 0.004 pixels, respectively (WFC3 ISR 2014-02