TIPS/JIM
May 19, 2011
Agenda:
INS Division News (Danny Lennon)
Persistence in WFC3/IR (Knox Long)!
Progress Modelling the CTE in ACS at the Low-Background End (Jay
Anderson)!
TFI NRM Observing Strategies and Algorithms for Extended Sources
(galaxies, AGN, ….) (Anand Sivaramakrishnan)!
!
Next TIPS/JIM: June 16, 2011
This page is being held for INS Status page. TIPS/JIM
May 19, 2011
Agenda:
INS Division News (Danny Lennon)
Persistence in WFC3/IR (Knox Long)!
Progress Modelling the CTE in ACS at the Low-Background End (Jay
Anderson)!
TFI NRM Observing Strategies and Algorithms for Extended Sources
(galaxies, AGN, ….) (Anand Sivaramakrishnan)!
!
Next TIPS/JIM: June 16, 2011
Persistence in the WFC3 IR detector!
Knox S. Long!
TIPS 2011 May!
1!
Overview !
l  Persistence is a residual image observed in most types of IR arrays!
l  There is physical model for this persistence involving traps that are
accessed by free electrons or holes when a pixel is near saturation!
l  The WFC3 IR detectors exhibit persistence from sources that approach or
exceed full well!
n
Typically persistence results in signals of 0.3 electrons s-1 , 1000 s after a saturated
exposure."
n
The persistence is primarily a function of the amount of saturation of a pixel and the
time since saturation"
n
Persistence decays as a power law of time (γ~1)"
l  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!
TIPS 2011 May!
2!
Basic reason for persistence is understood!
Trapped Trapped
electrons holes
Mobile
electrons"
Depleted"
Mobile
holes"
- - - --+
- - - -- - -
- - - -- - -
++ +
+ +
+ ++
++ +
+ +
+ ++
++ +
+ +
high flux
signal
reset
dark idle
(large reverse bias)
All traps have released
their charge in depletion
region
R.Smith, SPIE 7021-22, Marseille 2008-06-24
(low bias)
As signal
accumulates the
depletion width is
reduced. Traps
newly exposed to
charge can
capture some
mobile carriers.
TIPS 2011 May!
(large reverse
bias)
At reset the
wider depletion
region is restored,
but trapped charge
stays behind.
- - - -++ +
+ +
N
P
next dark exp.
(small bias
reduction)
The released charge
reduces the bias
voltage. persistence
3!
Persistence Examples!
l  Easy case!
n
Look for obvious patterns"
n
Look for objects that
appear mushy"
Ex. 1"
l  Hard case!
n
Use multidrizzle to find
residuals"
n
Subtract the last single
science image from the
first"
Ex. 2"
l  If you suspect persistence,
use MAST search to see if
there were IR observations
that preceded yours!
http://archive.stsci.edu/hst/history_search.html
TIPS 2011 May!
4!
Cycle 18 Calibration - Omega Cen!
l  3 visits all consisting of an
undithered Omega Cen
exposure followed by a
sequence of darks!
n
Two visits successful, and the third to
be repeated in a few weeks"
l  Dark current measured from
234 s to 5800 s after the
stimulus!
TIPS 2011 May!
5!
Persistence follows a Fermi-like distribution!
Persistence (e s-1)"
230 s"
5800 s"
Note – Not individual pixels but the mean"
persistence at different stimulus levels. "
WFC3 nominal saturation value is 70,000 e "
TIPS 2011 May!
6!
Persistence is ~ a power law function of time!
TIPS 2011 May!
7!
Persistence Model!
"
!#
"
%
"
% q " t %
1
P(q, t) = N $ (q!qo )/!q '$ ' $
'
#e
+1 &# qo & # 1000s &
l  Where q and t are the stimulus (in electrons) and time (in seconds)!
n
N is the normalization factor (at 1000 s)"
n
qo is the “Fermi energy” at which the stimulus is “half”"
n
δq is the “Fermi kT” "
n
α is the power law slope correction to the Fermi function."
n
γ defines the power slope for the decay with time"
TIPS 2011 May!
8!
Results (Visit 1)!
l  Global fits good with
systematic departure
near knee!
l  “Mean value” of
persistence!
n
1.43à 0.05 e/s"
l  RMS error !
n
0.02 à 0.0052 e/s"
l  Maximum error!
n
0.04 à 0.02 e/s"
l  Visit 3 similar!
TIPS 2011 May!
9!
Persistence subtraction S/W!
l  HST archive does not currently
provide an automated way to
subtract persistence from images!
Original"
Total. Persistence"
l  However, WFC3 group is providing
persistence subtracted images to
users on request!
l  Implements the model described
above with a set of Python scripts!
l  Provides!
n
Persistence image"
•  External – generated by early
visits"
•  Total – internal + external
persistence"
n
Corrected flt file"
Corrected"
TIPS 2011 May!
External Persistence"
10!
Open item - Persistence is not completely uniform!
Tungsten lamp"
Dark after Tungsten lamp"
Tungsten lamp is brightest in lower right quadrant"
Persistence is brightest in upper left quadrant"
TIPS 2011 May!
11!
Persistence is not completely uniform!
Omega Cen Dark after model subtraction"
TIPS 2011 May!
12!
Open item – Persistence may be a function of time saturated!
Smith et al. model predicts persistence is a function of time"
a pixel held at saturation"
•  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"
TIPS 2011 May!
13!
Summary – Persistence is not a virtue, but …!
l Today!
l Future!
n
IR observations prohibited
after some bad actors "
n
Substantial Cycle 18
calibration program underway"
n
A working model exists for
persistence"
•  Based on prior history of
illumination"
n
A tool exists to mitigate
persistence "
n
Ready to run existing
persistence subtraction tool
on al the WFC3/IR data and
then to advertise the
existence of the persistence
images"
n
There are additional effects
that may be able to improve
the model"
•  Persistence as a function of
position"
•  Results have been provided to
individual users on a case by
case basis"
•  Tool has been tested on a large
fraction of the data"
TIPS 2011 May!
•  Add effects including
dependency of the decay on
illumination and time at
saturation"
14!
TIPS/JIM
May 19, 2011
Agenda:
INS Division News (Danny Lennon)
Persistence in WFC3/IR (Knox Long)!
Progress Modelling the CTE in ACS at the Low-Background End (Jay
Anderson)!
TFI NRM Observing Strategies and Algorithms for Extended Sources
(galaxies, AGN, ….) (Anand Sivaramakrishnan)!
!
Next TIPS/JIM: June 16, 2011
Progress Report on
Modeling CTE in
ACS/WFC
TIPS May 19, 2011
Jay Anderson
CTE in ACS/WFC
Brief review
•  Many many ISRs…
–  Riess, Mack, Chiaberge…
•  Massey et al paper in 2010
–  Modeled WPs in COSMOS images
–  50e- background ; assumed mini-channel
•  Anderson/Bedin 2010 correction
–  Modeled WPs in darks
•  Two parameters:
–  φ(q) - the density of traps at electron level
–  ψ(j;q)-the trail profile for electron level
–  V low background; no mini-channel
–  Implemented into CAL/ACS in Fall.
–  Good job, but…
25%
15%
10%
Limitations to the Implemented
Algorithm
1)  1000s Darks are only so dark
•
•
Could not probe below 30 eACS team took shorter darks: 33s, 100s, 339s
•
•
•
<30 e- WPs more sparse
truth -type constraints on the model
improved model…
2)  Mild deconvolution
•
•
Necessarily amplifies noise
Readnoise in particular causes problems
3)  Pathological cases
•
•
When are more than 50% of e- lost? 90%?
No remedy, but insight…
Updated Model
•  Improvements
–  Constrain low e- traps better
•  Both the trap density (φ) and release profiles (ψ)
–  Do the charge transfer iteratively
•  Old: 2048 transfers in one step
•  New: 2048 transfers in N (~5) steps
•  Optimization
–  Fit model to long and short darks
33s DARK
Life is never easy…
-
5000 e
in deep
1000s DARK * 33/1000
FAR
FROM
READOUT
J~1500
J~1000
CLOSE
TO
READOUT
33s DARK
100s DARK 339s DARK
FAR
FROM
READOUT
J~1500
J~1000
CLOSE
TO
READOUT
33s DARK
100s DARK 339s DARK
FAR
FROM
READOUT
J~1500
J~1000
CLOSE
TO
READOUT
33s DARK
100s DARK 339s DARK
FAR
FROM
READOUT
J~1500
J~1000
CLOSE
TO
READOUT
33s DARK
100s DARK 339s DARK
FIXED…
33s DARK
100s DARK 339s DARK
LOW
WP
The
Trails
HIGH
WP
New Model
•  φ(q) - trap density
–  below 10e-: >99% chance of loss!
•  ψ(j;q) - trail profile for electron level
–  a surprise…
–  Lower e- traps have steeper trails
•  Low trap trails go out to only 19 pixels
•  High trap trails go out to 60 pixels
New Model
•  φ(q) - trap density
–  below 10e-: >99% chance of loss!
•  ψ(j;q) - trail profile for electron level
–  a surprise…
–  Lower e- traps have steeper trails
•  Low trap trails go out to only 19 pixels
•  High trap trails go out to 60 pixels
New Model
•  φ(q) - trap density
–  below 10e-: >99% chance of loss!
•  ψ(j;q) - trail profile for electron level
–  a surprise…
–  Lower e- traps have steeper trails
•  Low trap trails go out to only 19 pixels
•  High trap trails go out to 60 pixels
ACS Team Plans
1) Port to Python / IRAFX
2) How to modify the error array?
3) How best to mitigate readnoise?
4) Column by column fine-tuning?
5) How does CTE impact S/N? (When pathological?)
6) Integrate into pipeline (darks, new products)
7) x-CTE and bias-shift effect
de-striping, too…
8) Time dependency
9) UDF/HDF comparisons
10) Validation against standard tests: recommendations
11) Optimization within Multi-drizzle…
NEXT: UVIS…
MAGIC
SQUARE
PHYSICAL
PRE-SCAN
OVER-SCAN
DEEPLY
EXPOSED
FLAT
Column-by-Column dependency
ACS OVER TIME
WP
P1
JULY 2006 TEMP CHG
BEFORE: -77°
ACSCOVER TIME
AFTER: -81° C
WP
P1
ACS OVER TIME
WP
P1
FAR FROM; UNCORR
FAR FROM AMP; CORR
NEAR AMP; CORR
TIPS/JIM
May 19, 2011
Agenda:
INS Division News (Danny Lennon)
Persistence in WFC3/IR (Knox Long)!
Progress Modelling the CTE in ACS at the Low-Background End (Jay
Anderson)!
TFI NRM Observing Strategies and Algorithms for Extended Sources
(galaxies, AGN, ….) (Anand Sivaramakrishnan)!
!
Next TIPS/JIM: June 16, 2011