NIRSpec: from Ramps to
Slopes
Bernard J. Rauscher
for the NIRSpec Detector Subsystem
Team
NASA Goddard Space Flight Center
31 March 2009
STScI Calibration Summit
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Topics
• Data Format
• Pipeline processing
• Detector artifacts and pipeline
processes needed to correct them
• IDL procedures
31 March 2009
STScI Calibration Summit
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Data Format
•
NIRSpec used JWST MULTIACCUM
(AKA “MULTI-nxm”) sampling
– n up-the-ramp groups
– m frames averaged per group
– Baseline science integration is
MULTI-22x4
•
Total noise averages down
approximately as,
•
•
Where f is total photonic current including dark current
Eqn. 1 neglects 1/f noise, which NIRSpec testing has shown
to be significant with the SIDECAR ASIC. It therefore slightly
underestimates the noise of JWST flight systems.
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Set of
Dark
Ramps
Example: GSFC Pipeline
Processing
Pixel-toPixel
Crosstalk
MKMULTI
REFSUB
NOTE: REFSUB is
frequently called by
MKMULTI to do both
boxes in one step
Slope
Images
Mean
Image
ITERCOMBIN
E
Sigma
Image
HOT_PIXEL_
CROSSTALK
IMHI2
Dark
Rate
Other
31 March 2009
Analysis
STScI Calibration Summit
IMHI
2
Total
Noise
4
Dark
Ramps
Other Data Products Derived from Dark
Ramps
POWSPEC_S
CA,
DINO
FFT Noise
Analysis
SNOW BALL
Snowball
Analysis
FIND_COSMIC_RA
YS,
CR_CROSSTALK
BIAS_DRIFT
31 March 2009
Pixel-toPixel
Crosstalk
Bias Drift
Outputs
Correlations
STScI Calibration
Summit
CDS Noise
5
Slope Fitting Using MKMULTI
(This IDL Procedure is included in the deliverable FPQLA
Software)
• MKMULTI computes integrated signal per
pixel,
• Pixel slopes computed using standard 2parameter least-squares fitting. For each
pixel,
• The standard equations (see e.g.
“Numerical Recipes in C the Art of
Scientific Programming”) are,
31 March 2009
STScI Calibration Summit
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Reference Pixel Correction using
REFSUB (1)
•
(This IDL Procedure is included in the deliverable FPQLA
NIRSpec’s HAWAII-2RG Software)
SCAs include 2 types of
reference pixel
0.0
e-/s/pixel
+0.010
Reference pixels in rows
• Available on all outputs
• These are always used!
31 March 2009
0.0
e-/s/pixel
+0.010
Reference pixels in columns
• Available on outputs #0 and #3 only
(2 of the 4 outputs)
• These are sometimes used
• Should be treated with caution
because their use involves making
assumptions about noise correlations
across outputs
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Reference Pixel Correction using
REFSUB (2):
Using Reference Pixels in Rows
•
In the IDL zero-offset array indexing convention, these are
pixels,
[*,0:3] & [*,2044:2047].
•
•
Each output is treated independently
For each output, the horizontal reference pixels are used in
one of two
ways.
“Reference Rows Only”
“Simple”
•For each output, we compute the mean
•For each output, we compute
[or median] of the reference pixels in
the mean [or median] of the
rows; (“bottom”) 0:3 & (“top”)
2044:2047
reference pixels in rows
- If computing means, we use
2044:2047
DJS_ITERSTAT to implement
- If computing means, we
iterative sigma clipping
- If computing medians, we use
use DJS_ITERSTAT to
the IDL median function
implement iterative sigma
-For each output and using the “top” and
clipping
“bottom” reference pixel values,
- If computing medians, we
interpolate a reference pixel value for
each row
use the IDL median
•The model value for each row is
function
subtracted from every pixel in the row.
•31The
mean
(or
median)
value
is
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subtracted from every pixel in
Reference Pixel Correction using
REFSUB (2):
Using Reference Pixels in Columns
•
Because only 2 of the 4 outputs actually have reference
columns, the reference columns should be used only if there
is significant (>~50%) output-to-output noise correlation
–
–
For NIRSpec, it is not clear yet whether this condition will be satisfied
For our “Pathfinder Detector Subsystem”, this condition was not
clearly satisfied
“Teledyne Imaging Sensors (TIS)
Baseline”
“GSFC Approach”
•Testing shows this to be slightly (1%2%) more powerful than the TIS
•Needs to be done after applying
approach
a reference pixel correction using
•Each half of SCA treated
reference pixels in rows.
independently
•For each row, subtract a rolling
•All 4 reference columns on one half
average of 4 reference rows on
averaged together to form a mean
either side of the current row.
reference column for that half
•Optionally, the two halves of the
•Mean reference column is smoothed
SCA can be treated
using either a Savitzky-Golay filter or
Gaussian smoothing kernel.
independently.
•Smoothed mean reference value
subtracted from every pixel in the
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Summitrow
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current
IDL Procedures
• The NIRSpec Detector Subsystem Team
at GSFC works mostly in IDL
• We have delivered a Focal Plane Quick
Look Analysis (FPQLA) package to ESA
• The FPQLA implements much of what we
have discussed; slope fitting, reference
pixel correction, etc.
• We are willing to share this software on
a best-effort basis with others in JWST
• The FPQLA software runs on Red Hat
Linux
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