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XMM-Newton Science Analysis System Page: 1
ommodmap
July 2, 2008
Abstract
Creates and applies a `modulo-8' xed pattern noise tile.
1 Instruments/Modes
Instrument Mode
OM FAST
OM IMAGING
2 Use
pipeline processing yes
interactive analysis yes
3 Description
This task corrects a given OSW image for `modulo-8' spatial xed-pattern noise that results from the OM
centroiding algorithm. If there are suфcient counts in the OSW image the mod-8 tile can be constructed
and applied to the OSW. Both the mod-8 corrected OSW image and the mod-8 map are outputs of the
task.
The following functionality is currently not available:
If the s/n of the OSW image is too poor (typically because the OSW image was obtained in FAST mode
and is too small to provide good statistics), then an alternative IMAGE mode image that encompasses
the FAST mode window is used to construct the mod-8 tile. If no such alternative image is available then
the task is aborted.
3.1 The origin of the mod-8 xed pattern noise
The useable imaging area of the OM CCD detector is 256 by 256 physical (detector) pixels. Individual
photon events are centroided to one eighth of a physical CCD detector pixel by the OM electronics.
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The resulting OM imaging area is therefore 2048 by 2048 pixels. However, the centroiding algorithm
distributes the photons unevenly within each physical CCD pixel, corresponding to 8 by 8 unbinned
image pixels or a single mod-8 tile, as though the pixels are smaller near the edge of the tile.
3.2 Creating the mod-8 map
A box of size nbox is rst stepped across the image and within the box a sigma clipping algorithm is
used to mask out sources and any surrounding pixels aected by coincidence loss. Then the average of
all remaining mod-8 tiles within a sliding box of size nbox is computed and used to produce the mod-8
map.
3.3 Correcting the image
The problem relates to the distribution of events, not to changes in the sensitivity, and so dividing the
science image by the mod-8 map, whilst providing a simple cosmetic solution, would compromise the
photometry of the image. Instead the algorithm resamples the image to give each image pixel equal area
within a mod-8 tile.
For each mod-8 tile in the mod-8 map, the pixel x-boundaries are determined such that within each row of
pixels the counts/unit pixel area is the same for each pixel, as illustrated in the left hand panel of Figure
1. This is then taken as the spatial layout of the pixel x-boundaries in the same mod-8 tile in the science
image and the science image is resampled to a grid of evenly spaced pixels. Then the y-boundaries of
each row are determined such that each row has the same number of counts/unit pixel area, as illustrated
in the right hand panel of Figure 1. This is then taken as the spatial layout of pixel y-boundaries in the
same mod-8 tile in the science image, which is then resampled to a grid of evenly spaced rows.
The same procedure is then repeated with the order reversed (remapping in y followed by remapping
in x) and the nal corrected science image is made from an average of the two resamplings. This is to
ensure that the redistribution of photons is performed in an identical fashion in x and y.
Figure 1: Schematic of the pixel boundary determination and resampling in x and y
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The threshold for applying the mod-8 mapping algorithm is currently established to be 1000 mean
background counts from the nBox * nBox area, i.e. the mean background value times nBox 2 must exceed
1000 counts. The motivation for doing that was due to the fact that the mod-8 noise up to 10 to 20%
assumes that in order to improve the image we have to have an accuracy of about 3%, which corresponds
to mean*nBox 2 > 1000 counts. The algorithm is not applied to images with poor statistics.
4 Parameters
This section documents the parameters recognized by this task (if any).
Parameter Mand Type Default Constraints
set yes string none
Name of OM OSW FITS image le
mod8product yes logical false
Create an output image of the modulo-8 map.
mod8set yes string none
Name of output product OM OSW modulo-8 tile
outset yes string none
Name of modulo-8 noise corrected OM OSW FITS image le
nbox no integer 16
Size of sliding box in units of 8 (unbinned) image pixels (corresponding to one CCD pixel)
nsig no integer 3
Signicance level for sigma clipping
5 Errors
This section documents warnings and errors generated by this task (if any). Note that warnings and
errors can also be generated in the SAS infrastructure libraries, in which case they would not be docu-
mented here. Refer to the index of all errors and warnings available in the HTML version of the SAS
documentation.
allocError (fatal)
Can't allocate memory for internal array
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badFileMode (fatal)
Invalid datamode 'xxxxxx' in set 'xxxxxx' - the value of the datamode keyword is not as
expected
paramError (fatal)
Mod 8 product requested but no lename provided for output product
deAllocError (warning)
Failed to release memory for
corrective action:
noMod8Noise (warning)
The binning factor for the image equals or exceeds the scale of the mod-8 noise pattern and
so it is averaged out - the image contains no mod-8 noise pattern.
corrective action: No mod-8 noise correction is necessary or applied
lowMod8Noise (warning)
Too few counts in image to determine and thus remove mod8 noise
corrective action: No mod-8 noise correction is applied
6 Input Files
1. Intermediate FITS image le (Output from omflatfield)
7 Output Files
1. OM OSW modulo-8 map (if requested)
2. Modulo-8 corrected OSW FITS image (goes to omdetect)
8 Algorithm
subroutine ommodmap
read in task parameters
open OM OSW Image file
determine file type from datamode in primary header
read in the science window keywords from the primary header
calculate the image binning
extract window data from MODES binary table extension
extract quality array
extract OM OSW Image
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if modulo-8 noise is not lost in binning
calculate good pixels to be used in producing the mod8 Tile Map using a
sigma clipping method
calculate size of modulo-8 tile
calculate size of sliding box
loop over OM OSW Image in steps of modulo-8 tile
loop over each pixel in modulo-8 tile
use sliding box to calculate mean pixel values
end loop
use mean pixel values to calculate modulo-8 tile
insert modulo-8 tile into modulo-8 map
end loop
end if
correct OM OSW Image for modulo-8 noise
create output OM OSW Image file
end subroutine ommodmap
9 Comments
10 Future developments
 Cases involving poor statistics need to be dealt with more rigorously.
 Use of an alternative image for reduction of cases with poor statistics needs to be imple-
mented.
References
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