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1 TIPS 2011 May Persistence in the WFC3 IR detector Knox S. Long.

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Presentation on theme: "1 TIPS 2011 May Persistence in the WFC3 IR detector Knox S. Long."— Presentation transcript:

1 1 TIPS 2011 May Persistence in the WFC3 IR detector Knox S. Long

2 2 TIPS 2011 May Overview Persistence is a residual image observed in most types of IR arrays There is physical model for this persistence involving traps that are accessed by free electrons or holes when a pixel is near saturation The WFC3 IR detectors exhibit persistence from sources that approach or exceed full well Typically persistence results in signals of 0.3 electrons s -1, 1000 s after a saturated exposure. The persistence is primarily a function of the amount of saturation of a pixel and the time since saturation Persistence decays as a power law of time (  ~1) In most cases, post-processing can remove about 90% of the persistence signal with algorithms that track the history of the stimulus in the preceding 6 hours

3 3 TIPS 2011 May Basic reason for persistence is understood - - - - - + + + + + next dark exp. (small bias reduction) The released charge reduces the bias voltage. persistence - - - + + + - - - - - + + + + + high flux signal (low bias) As signal accumulates the depletion width is reduced. Traps newly exposed to charge can capture some mobile carriers. Trapped holes Trapped electrons - - - + + + + + + + + - - - - - reset (large reverse bias) At “reset” the wider depletion region is restored, but trapped charge stays behind. Depleted Mobile electrons Mobile holes dark idle (large reverse bias) All traps have released their charge in depletion region + + + + + - - - - - -+ P N R.Smith, SPIE 7021-22, Marseille 2008-06-24

4 4 TIPS 2011 May Persistence Examples Easy case Look for obvious patterns Look for objects that appear mushy Hard case Use multidrizzle to find residuals Subtract the last single science image from the first If you suspect persistence, use MAST search to see if there were IR observations that preceded yours Ex. 1 Ex. 2 http://archive.stsci.edu/hst/history_search.html

5 5 TIPS 2011 May Cycle 18 Calibration - Omega Cen 3 visits all consisting of an undithered Omega Cen exposure followed by a sequence of darks Two visits successful, and the third to be repeated in a few weeks Dark current measured from 234 s to 5800 s after the stimulus

6 6 TIPS 2011 May Persistence follows a Fermi-like distribution Note – Not individual pixels but the mean persistence at different stimulus levels. WFC3 nominal saturation value is 70,000 e Persistence (e s -1 ) 230 s 5800 s

7 7 TIPS 2011 May Persistence is ~ a power law function of time

8 8 TIPS 2011 May Persistence Model Where q and t are the stimulus (in electrons) and time (in seconds) N is the normalization factor (at 1000 s) q o is the “Fermi energy” at which the stimulus is “half”  q is the “Fermi kT”  is the power law slope correction to the Fermi function.  defines the power slope for the decay with time

9 9 TIPS 2011 May Results (Visit 1) Global fits good with systematic departure near knee “Mean value” of persistence 1.43  0.05 e/s RMS error 0.02  0.0052 e/s Maximum error 0.04  0.02 e/s Visit 3 similar

10 10 TIPS 2011 May Persistence subtraction S/W HST archive does not currently provide an automated way to subtract persistence from images However, WFC3 group is providing persistence subtracted images to users on request Implements the model described above with a set of Python scripts Provides Persistence image External – generated by early visits Total – internal + external persistence Corrected flt file Original External Persistence Total. Persistence Corrected

11 11 TIPS 2011 May Open item - Persistence is not completely uniform Tungsten lampDark after Tungsten lamp Tungsten lamp is brightest in lower right quadrant Persistence is brightest in upper left quadrant

12 12 TIPS 2011 May Persistence is not completely uniform Omega Cen Dark after model subtraction

13 13 TIPS 2011 May Open item – Persistence may be a function of time saturated Cycle 18 test – turn the tungsten lamp off at mid-exposure At 80,000 e, there seems to be a correlation of persistence with hold time At 140,000 e, the small amount of data in hand is not easily understood Smith et al. model predicts persistence is a function of time a pixel held at saturation

14 14 TIPS 2011 May Summary – Persistence is not a virtue, but … Today IR observations prohibited after some “bad actors” Substantial Cycle 18 calibration program underway A working model exists for persistence Based on prior history of illumination A tool exists to mitigate persistence Results have been provided to individual users on a case by case basis Tool has been tested on a large fraction of the data Future Ready to run existing persistence subtraction tool on al the WFC3/IR data and then to advertise the existence of the persistence images There are additional effects that may be able to improve the model Persistence as a function of position Add effects including dependency of the decay on illumination and time at saturation


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