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Following the Photons…

Following the Photons…. Back-Tracking the Electrons. Empirical, Pixel-Based Corrections for CTE. Jay Anderson STScI October 12, 2011. 30s, 47 Tuc Outer field. Shuffle. Plan for the Talk. Introduce the CTE problem Brief history Version 1.0: My initial solution

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Following the Photons…

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  1. Following the Photons… Back-Tracking the Electrons Empirical, Pixel-Based Corrections for CTE Jay Anderson STScI October 12, 2011

  2. 30s, 47 Tuc Outer field Shuffle

  3. Plan for the Talk • Introduce the CTE problem • Brief history • Version 1.0: My initial solution • Version 2.0: Soon-to-be-pipelined solution • WFC3/UVIS • Version 3.0: Additional needed improvements

  4. readout readout readout readout readout observed CTE=Charge-Transfer Efficiency CTI = Charge-Transfer Inefficiency The Problem:CTE/CTI Steadily increasing problem for: • STIS, ACS’s WFC, … WFC3? • Is also bad for archival WFPC2, HRC • Symptoms: • Loss of flux in source • Increase of flux in trails • Cause: • Traps within silicon pixels that delay individual electrons • Number of traps increases over time

  5. up-shifted flat image pixels (flat) parallel overscan FPR readout EPER A Brief HistoryMany Approaches charge grabbed charge let go • Laboratory work: • 55Fe 1620 e events ; FPR ; EPER  two trap species • Also computer modeling of distribution within pixel • Limited array of tools used, incomplete picture • Post-hoc corrections • Common wisdom: CTE worst for faint sources on low background • Empirical photometric corrections (Riess, Mack, Ciaberge, Goudfrooij, … ) • Problem 1D: Observed flux + sky, time, location  initial flux • What about astrometry? Shape? • Pixel-based corrections/reconstructions • The holy grail • STIS: Bristow, Alexeev • WFPC2: Riess • ACS: Massey et al 2010 on COSMOS data • Limited focus (medium/high backgrounds) • Proof of concept: generated renewed excitement at ST

  6. INPUT MODEL OBS’N = 0.01% chance My Model 1.0 • Previous: • Bristow: Sources • Riess: CRs • Massey: WPs in science frames • Trail data from lab tests • Assume mini-channel from manufacturing expectations • Modeled specific representative trap locations • Model 1.0: WPs in dark images • Explore lower backgrounds than GOODS sky (50 e) • Purely empirical: Just look-up tables • Trap density: (q)  traps per marginal electron • Trap release: (n;q)  short + long trails • Trap and release assumptions • Trapping deterministic • Release probabilistic • Keep track of state of each trap during transfer • Modeling the pixel array: • continuum of fractional traps in each pixel • code economizing for speed: 2048 steps  1 to 5 steps • iterate for to get input distribution (like Massey)

  7. Animationof Model Parameters of Model: Trap density: (q) Trail profile: (t;q)

  8. One Raw Dark, post SM4

  9. Stack of 168 Post-SM4 Darks

  10. CR Tail Measurement

  11. Empirical Trails Faint No “notch” channel apparent! consistent with common wisdom that CTE worse for faint sources Bright

  12. Faint Corrected WP Trail Residuals Adjust by hand the model parameters 1) density: (q) 2) profile: (n;q) Bright

  13. Corrected WP Deep

  14. The tests… • Aesthetic test: trails gone? • Photometry: flux back? • Astrometry: flux in right place? • Shape: flux really in the right place?

  15. 339s, 47 Tuc Outer field

  16. 339s, 47 Tuc Outer field

  17. 30s, 47 Tuc Outer field

  18. 30s, 47 Tuc Outer field

  19. 30s, 47 Tuc Outer field

  20. 30s, 47 Tuc Outer field

  21. The tests… • Aesthetic test: trails gone? • Photometry: flux back? • Astrometry: flux in right place? • Shape: flux really in the right place?

  22. INPUT MODEL OBS’N Not the end of the story… • Limitations of PB approach • Read-noise problem • S/N loss • Limitations of v1.0 • Time dependence (assumed linear) • Temperature dependence of trails • Even darks not dark • Need to explore lowest packets (10 e) +RN

  23. 1000s, 1000 e-  100s, 100 e- Model 2.0 • Will soon be released as standard pipeline product • Compare long darks + short darks • Can see the 10 e WP events • Absolute handle on losses Known WPs! Same WPs?

  24. TOP OF CHIP Creeping CTE FAINT WP BOT OF CHIP BRIGHTER WP

  25. (q) (DN) (DN) Model 2.0 • Will soon be released as standard pipeline product • Compare long darks + short darks • Can see the 10 e WP events • Absolute handle on losses • Truly pathological losses… 15 e < 1 e cross section

  26. WFC3/UVIS • Aging fast • Why? • SBC, mini-channel, etc?! • Maybe, but useless…. • Solar cycle • Different observing regime • Lower background • Narrow filters, UV, low dark current, few WPs • True mitigation available • Charge-injection: every 10, 17, or 25 lines • Benefit, but limited…

  27. WFC3/UVIS • Aging fast • Why? • SBC, mini-channel, etc?! • Maybe, but useless…. • Solar cycle • Different observing regime • Lower background • Narrow filters, UV, low dark current, few WPs • True mitigation available • Charge-injection: every 10, 17, or 25 lines • Benefit, but limited… True mitigation, but add noise model dependence (get better model)

  28. Model 3.0 • Realization that dark current important • Readout ~ 90s, but many WPs… • Even bias frames have 15 e at top! • Do the correction on raw frames • Study everything • Column by column dependence • WPs in all exposures over time • EPER parallel overscan over time • Pin-down UVIS model, using charge-injection • Explore UVIS CI mitigation • Goddard exploring possible injection mitigation…

  29. THE END

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