The processing of OM data is run in pipeline mode at the SSC in Leicester. Two processing chains, omichain and omfchain, are used for image and fast mode data respectively. The process can be repeated by the users by running the same chains at their home institute. The chains are Perl scripts which concatenate the individual SAS tasks so as to go from the input raw data up to the final output results without further interaction. The tasks can also be run one by one having more control on all needed parameters.
The whole processing of image and fast mode data is depicted in Fig. 40 and Fig. 41.
Starting in Version 6, SAS contains also some tasks to process grism data and also a chain, omgchain to extract automatically the spectra from grism data. Fig. 42 gives an overview of the process. It should be noted that grism data processing has not been included up to now in the pipeline run at SSC in Leicester. The general reprocessing of all XMM-Newton data includes OM grisms, which from now on will be processed in the pipeline.
In order to process the OM image data successfully an input dataset is required. Input datasets are not changed during the OM processing with omichain. They are copied to intermediate datasets and keywords. Extensions are added to the FITS data files as needed. Intermediate task products, which are passed from one task to another, are generally not described.
The processing of OM image data can be divided in three parts (see Fig. 40)
This core of the image processing can be divided as well
As it can be seen in the flow chart of the OM processing chain (Fig. 40), the OM tracking information for each exposure is treated before and independently from the image data processing. In the following, for each task description, a reference is given to the analysis step in the processing example.
