CTE in the Dark
43
CTE in the Dark An Empirical Pixel-Based Correction for CTE TIPS/JIM January 21,2009 Jay Anderson Luigi Bedin
description
CTE in the Dark. An Empirical Pixel-Based Correction for CTE. TIPS/JIM January 21,2009 Jay Anderson Luigi Bedin. 30s, 47 Tuc Outer field. Shuffle. CTE/CTI. Steadily increasing problem for: STIS, ACS’s WFC, … WFC3? Was also bad for WFPC2, HRC Symptoms: Charge trails Loss of flux - PowerPoint PPT Presentation
Transcript of CTE in the Dark
CTE in the DarkAn Empirical Pixel-Based
Correction for CTE
TIPS/JIMJanuary 21,2009Jay AndersonLuigi Bedin
30s, 47 Tuc Outer field
Shuffle
Steadily increasing problem for:– STIS, ACS’s WFC, … WFC3?– Was also bad for WFPC2, HRC
Symptoms: – Charge trails– Loss of flux
Cause:– Traps within pixels that delay readout– Trap density increases linearly over time
Traditional mediation:– Photometric correction ; astrometric?– Experimental pixel-based corrections
• STIS: Bristow 2002+• ACS: Massey et al 2010
– Theoretical plus empirical
• New approach here: purely empirical
CTE/CTI
readout
observed
One Raw Dark, post SM4
Stack of 168 Post-SM4 Darks
“Peak” Map
A Purely Empirical PlanPASP Paper in preparation with L. “R”. Bedin
Inspired by– HVS project (PI-Oleg Gnedin)– Massey et al. (2010): WPs in COSMOS science data
Plan:• Examine WPs in darks• Study two dimensions:
– Profile scale: dependence on WP intensity– Profile drop-off: dependence on n
• Focus: “Just numbers”– Lots of trails– First step: mechanics of measuring the trails
CR Tail Measurement
Empirical TrailsFaint
Bright
No “notch”channel apparent!
Total Power in
Tails
WP INTENSITY
TO
TA
L I
N T
AIL
A Simple, Empirical Model• Different traps affect different electrons
– More traps affect lower-hanging electrons (q): traps per pixel at each chg level
• Different traps may have different release times– Follow release out to 100 pixels– Model: keep track of each trap’s state– All the charge?
• What about shadowing?– Well known background effect– Leading pixels?– How to resolve?
WP
C R
C R
WP~2500
WP~5000What about Shadowing?
?
?
Yes! Shadowing is essentially “perfect” !
X
A Simple, Empirical Model[1] Different traps affect different electrons: (q) = trap density (total number)[2] Different traps may have different release times
(n;q) = release profile[3] Perfect shadowing!
Instantaneous filling of traps
Readout Model’s Four Stages:
(1) Shuffle out current cloud(2) Release trapped charge(3) Shuffle in new cloud(4) Trap new electrons
Correction Scheme
Start with a readout model– Two parameters:
1) Trap density: (q)2) Release profile: (n;q)
– Input PIX(j) output PIX(j)Iterate
– Find source function PORIG(j) that produces POBS(j)
Optimize model:– Minimize trails in darks by varying (q) and (n;q)
Independent tests:(1) Trails (2) Photometry (3) Astrometry (4) Shape
Corrected WP Trail
Residuals
Faint
Bright
Adjust by handthe model parameters1) density: (q)2) profile: (n;q)
Corrected WP Deep
Two Components of the Model
Trap Density - vs - q Trap Profile(q) (n;q)
Detailed Model Example
The tests…
1) Aesthetic test: trails gone?
2) Photometry: flux back?
3) Astrometry: flux in right place?
4) Shape: flux really in the right place?
339s, 47 Tuc Outer field
339s, 47 Tuc Outer field
30s, 47 Tuc Outer field
30s, 47 Tuc Outer field
30s, 47 Tuc Outer field
30s, 47 Tuc Outer field
47 Tuc Calibration Catalog 53,000 stars x,y,m
Photometric Residuals in Deep 339s 47 Tuc Images
BRIGHT
FAINT
Photometric Residuals in Short 30s 47 Tuc Images
BRIGHT: Near Saturation
FAINT: about 50 e- max
Astrometric Residuals in Short 30s 47 Tuc Images
BRIGHT: Near Saturation
FAINT: about 50 e- max
What about
shape?
Bright
Faint
Corrected
Summary
2-component model (q) and (n;q)– Pameters based solely on WPs in darks– Readout model, invert to get original pixels
Tested against stars:– Images with backgrounds of 1.5 DN2 and 15 DN2 – Trails removed– Photometry/astrometry generally restored– Shape surprisingly good
Remaining issues?
Remaining Issues• Reminder: just a proof of concept• When best to do? _flt or _raw?
– Either is ok• Pipeline modifications?
– Use of darks, biases• Improvements:
– Speed: 5 iterations = 10 minutes/exposure– Faint and bright extremes poorly constrained
• Verify linear time behavior (pre SM4…)• Read-noise amplification
– Should apply algorithm only to real structure• X-CTE
– Yes, but…
Ask me!
THE END
Backup Slides
READOUT SCHEMATIC
30s, 47 Tuc Outer field
30s, 47 Tuc Outer field
Original
Decomposition
“Smoothed” RN Component
Actual Change
Original Repaired Original Repaired Modified
Just the change
Change for Original Change for RN-Smoothed
Serial CTE
Serial CTE linear trends
Serial CTE Parameters
