A very obvious example of persistence is shown in Figure 8.1
. The image shown is of a high galactic latitude field; the observation was taken to search for the optical counterpart to a γ
-ray burst. However, two observations of a bright field near the galactic plane had preceded the image shown here by 2 to 5 hours, and the imprint of those dithered observations is clearly visible in current exposure.
Different HgCdTe IR detectors have different persistence characteristics. In WFC3, a pixel exposed to an effective fluence level of 105
electrons produces a signal of about 0.3 e-/sec 1000 s after the exposure. The signal decays with time as a power law with a slope of about -1. Thus at 10,000 s, the flux will be about 0.03 e-/sec, compared to the dark current of 0.048 e-/sec (median). As shown in the left panel of Figure 8.2
, the amount of persistence in the WFC3 IR detector depends strongly on the fluence of the earlier exposure. This shape of the curve reflects the density of traps in different regions of the pixels (and the fact that once the detector is saturated the voltage levels within the diodes do not change much with increasing fluence). The right panel of Figure 8.2
shows the power law decay of the persistence at different fluence levels.
where x and t are the fluence and the time since the end of the exposure causing the persistence. The other parameters and their nominal values are provided in Table 7.1 (see also Long et al 2012
). An improved model of persistence incorporates the effect of exposure time, and is described in WFC3 ISR 2015-15
. The new parametrizations have been incorporated into the software package used to predict persistence in all WFC3 IR observations.
The WFC3 team has developed a series of tools which allows us to predict the amount of persistence in IR images obtained with WFC3. It currently uses this formula. The model is not a complete description of persistence in WFC3. It ignores the differences in the power slopes evident in Figure 8.2
. It also ignores the fact that persistence actually depends not just on the total fluence, but on the complete exposure history. The traps have finite trapping times (see Long, Baggett & MacKenty 2013a
). A short exposure of a source that results in a fluence of 105
electrons produces less persistence than a longer exposure of a fainter source that reaches the same fluence level. Progress toward a better model of persistence in WFC3 is described by Long (2013
), and this may be incorporated into to the tools that the WFC3 team has developed for modeling persistence. But at present the model being used for predicting persistence in an image is the one described above.
Persistence of the magnitude (and importance) seen in Figure 8.1
is rare. This is in part because contact scientists check phase II submissions to identify programs that are likely to cause large amounts of persistence and mission planners inhibit WFC3 IR observations for 2 orbits after such observations. However, this process is only intended to identify only the worst cases of persistence and the process is not error free. A large proportion of the exposures taken with WFC3 have some saturated pixels and all of these pixels have the potential to generate persistence in the next observation in the schedule. Inhibiting IR observations after all exposures that could generate persistence would make it impossible to schedule the large numbers of IR observations that are carried out with HST, and in most cases, small amounts of persistence do not affect the science quality of the data, as long as observers and data analyzers take time to examine their IR images for persistence.