OM data reduction with SAS: fast mode data processing chain

A detailed description 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.

Furthermore, the fast mode processing chain has experienced continuous improvements along the successive SAS versions. The forthcoming SAS version 6 will be considered as the final stable one with respect to omfchain. Therefore it is strongly recommended to reprocess all fast mode data.

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:

• If there are more than one sources in the fast window, then the detection will be affected and therefore the whole light curve too. We have to change some parameters in omdetect: as nsigma , (sigma above background for detection), or minsignificance (minimum significance of source for its inclusion in the source list) (see SAS documentation, or run omdetect -h for details).
 
Invoking omdetect with regionfile=your_region.ascwill allow you a fast checking by overlaying the 7.0.0ly 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.