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Introduction
The thread explains how to process OM fast mode data to obtain light curves of
the source(s) present in the fast mode observing window.
Expected Outcome
OM threads describe how to process OM data using the corresponding chains
within SAS. They give also some advice and hints on the checkings to be done on
output SAS products to assess the quality of these output products.
SAS Tasks to be Used
Prerequisites
Before running any of the OM chains users should check in the ODF what type
of data they have: images, fast mode, and/or spectral images obtained with
the grisms. Then the corresponding chain(s) can be run. Running a chain that
does not correspond to the type of data will give a fatal error and it may
produce some confusion to the user. A proper set up of SAS is mandatory.
Useful Links
Caveats
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Procedure
OM data processing from A to Z is performed by "chains":
omichain,
omfchain and
omgchain
for image, fast mode data and grism spectra respectively. These are
perl scripts which start the different tasks at the proper time using the adequate
parameters. The tasks can be run separately, out of the chain, however
this may be cumbersome and prone to errors because each individual task
needs input data generated by a previous one.
A detailed description of the processing chains
(
omfchain)
as well as of each task can be found in the
SAS
documentation, both in HTML and Postscript format. A step by step description
of the fast mode chain and examples of the processing by individual execution
of all tasks is given in the
SAS
User's Guide and also at
this location.
OM fast mode data are fully processed by the XMM-SAS Pipeline: for each
exposure of a given observation all necessary corrections are applied to
the data files. Then a pseudo-image is built from the corrected event list
and a source detection algorithm is used to find the source (or sources)
present in the fast window. The source found is then tracked throughout
the event list to compute the count rates as a function of time for both
source and background. A light curve will be derived for each source found
in the fast window in each exposure.
In principle there is no need for further data reduction. The light
curves produced by the Pipeline have a default sampling time of 10
seconds.
The whole data processing can be repeated easily by any Guest Observer
or Archives User, should any calibration file be updated, and what is more
important, in case of doubtful results: the pipeline applies default options
in all SAS tasks which eventually can be changed by the GO in order to
improve the quality of the results. In particular, the source detection
is very sensitive to the artifacts which very are common in OM. Changing
the sampling time will require also a reprocessing of the data using better
parameters.
When comparing the data files obtained from the standard SSC pipeline
with those obtained by running
omfchain, the user will notice two
differences, the PPS files are compressed while the products from
omfchain
are not, and in addition some intermediate files, with name starting with
F, are preserved.
We outline here the checking that any User should perform on OM fast
mode processed data (by the standard Pipeline or by running SAS)
and the use of one of the tasks,
omdetect,
where the user can modify parameters affecting the source detection and
therefore the overall results of the data analysis.
- 1. Checking
omfchain
output products:
- Inspection of the light curves:
One can look at the pdf files containing the light curves to check that
there is some signal detected and measured (both in the source and the
background). These files can be recognized by the string 'TIMSR' and the
extension '.PDF' in the PPS products. If one has run omfchain, then
there are equivalent files in PostScript format (extension '.PS').
- Checking the presence of source(s) in the fast window pseudo-image.
This can be done easily by displaying this image with SAOImage or fv.
Another possibility is to overlay the detected sources onto the
pseudo-image.
The task
implot
will do it:
implot set=P0125320701OMS002SIMAGF1000.FTZ \
withsrclisttab=y \
srclisttab=P0125320701OMS002SWSRLI1000.FTZ \
itf=1 \
device='/XW'
This will overplot the detected sources on the corresponding image,
and it will allow us to check that there is something within the fast
window.
Pseudo image representing the fast mode window in sky coordinates
- 2. Improving the source detection and background determination:
- If there are more than one sources in the fast window, then the detection
will be affected and therefore the whole light curve too. In
this case the background determination will be critical. We have to change
some parameters as
nsigma
(sigma above background for detection). The size and
position of the source and background extraction areas can be modified
using the parameters
srcradius,
bkginner and
bkgouter.
Invoking
omdetect
with regionfile=your_region.asc will
allow you a fast checking by overlaying the currently detected sources
positions
on the image with SAOImage using the created region file. In the above
example:
ds9 P0125320701OMS002IMAGE_1000.FIT
and then load your_region.asc.
Note that PPS products have a slightly different naming convention than
the products of running the chains manually.
- In case of moderately bright or multiple sources in the fast window,
SAS 10 allows the user to measure the background in the asociated image data
obtained at the same time that the fast mode data. Using the parameter
bkgfromimage=yes will do that.
Last Updated: 16 April 2010
