THE NEW CALACS!
Pixel-based CTE Correction of ACS/WFC:!
Column Dependency!
Sara Ogaz, Jay Anderson, and the ACS Team!
Space Telescope Science Institute, Baltimore MD!
ABSTRACT!
In the presence of a high electric field, the dark current of a single pixel can be greatly
enhanced. These hot pixels accumulate as a function of time on orbit; however, the
reduction
of thelosses
operating
of the Channel
WFC CCDs(WFC)
has dramatically
reduced
In 2010 Anderson and Bedin created an algorithm to correct the charge transfer
efficiency
in temperature
the Wide Field
of
the into
dark current
the hot pixels.
ACSreduction
devices undergo
monthly annealing process
the Advanced Camera for Surveys (ACS). This algorithm has since been put
a newof version
of the
and acalibration
which greatly reduces the population of hot pixels and does not affect the normal
pipeline, CALACS. The current version of the algorithm treats all columns the
same, even though we know that because of the
pixels.!
Putting the electrons back where they belong!
stochastic nature of trap creation, some columns will have more traps and therefore more CTE losses, than other columns. To adjust
for this variability we have measured the value of the CTE trails in each column using the virtual overscan region of multiple flat field
images. The first few pixels of the virtual overscan contain a trail produced by the flux pixels on the edge of the image. As these flux
pixels are read out they pass every trap present in the column, making their trail an accurate reflection of the number of traps in that
column. For WFC we have found that 81% of columns fall within 10% of the average, and 96% fall within 20%. These column specific
measurements will be incorporated into the new version of CALACS.!
DATA!
!   We started with somewhere between 3 to 30 raw flat field images
for each year, from 2002 to 2011. From each of these flat field
images we pulled out a measurement of the CTE trail for each
column. !
COLUMN VARIATION WITH TIME!
!   The first step of our data reduction after subtracting the bias was
to combine the multiple data points within each year into an average
for that year. Figure 3 shows the average distribution of points for
the year 2009.!
!   We identified the first pixel of the virtual overscan region (see
RESULTS!
!
Figure 5 presents our final results. 96% of the columns lie
between 1.2 and 0.8 for both CCDs, meaning a typical column does
not vary from the average by more than 20%.!
!   These final values will scale the level of CTE correction for each
column with the number of traps in each column. !
!
!   Outliers have been confirmed as hot columns.!
!
!   This has been implemented in CALACS by creating a look up
table that will adjust the CTE correction by the final column
dependence values.!
!   We are currently testing the column to column adjustment to the
Figure 1) as an ideal place to measure a CTE trail as the only other
contributing signal to these pixels is the applied bias.!
CTE code to ensure it is improving the CTE correction.!
!   We subtracted the bias by taking an average of the first 11 pixels
of the virtual overscan region in each column and subtracting this
from the remaining column. This means we attained a column
specific bias. !
Final Column to Column Variation: CCD 2
!
!   For
our final measurement we compared the CTE trail in one
column, to the CTE trail in the surrounding columns using a 50 pixel
wide boxcar average. !
Figure 3: This graph shows column number versus the percent difference between
one column and the boxcar average. Data for each column is taken from the six 2009
flat images, so that each column is composed of six data points. !
!   For each column we took an average of all points in one year,
using the standard deviation as the error value. This average was
then compared to the boxcar average, and a percent difference was
taken.!
Column
!   Figure 4 shows the results of this for a standard column in the
WFC2 CCD, column 2603 for the years 2002 - 2011.!
!
Column 2603
Figure 1: Schematic of CCD 2 of WFC on ACS, each trail pixel has been bias
subtracted using the average of the bias pixels shown, and is compared to the 25
columns to either side of the column being measured.!
Figure 4: Year (2002 2011) versus percent
d i ff e r e n c e b e t w e e n
column 2603 and the
boxcar average.!
Column
Year
Figure 5: The top graph shows the final column to column variation for CCD 2 on
WFC. These points are the average of the values calculated from 2009-2011. The
error bars represent the standard deviation of the measurements taken from each flat
field added in quadrature. The bottom graph shows an enlargement of column 2650 to
column 2700!
!   The next step in our reduction was to condense the data from all
146 pixels
Figure 2: Cut out of a raw flat image, taken from the top overscan region of columns
2874-3020. White represents high intensity, black represents low intensity. At this
stretch it is possible to see the various amounts of trailing in the virtual overscan.!
years into one final data point per column.!
!
!   By visual inspection we determined that the trail values for years
2002 – 2007 had large error bars and large variation over time. This
is expected as the column variations due to CTE loses should not be
significant over this time period. To obtain our final values we took an
average of the 2009 – 2011 data.!
REFERENCES!
!   Anderson, J. & Bedin, L. R. 2010, PASP, 122, 1035–1064
!