The conversion from XMM-RGS spectra is a bit more complicated and requires
a few more steps. The reason is that the output from XMMSAS does not provide
wavelengths and counts in one file but either fluxes versus wavelengths or
counts versus channels. However, if fluxes are imported, then we loose
the Poissonian statistics.
With Cora we provide scripts that start with the original odf files, applying the XMMSAS tool rgsproc and then converting the output into the Cora format.
The shell script cora_rgspipe.sh does the complete reduction from odf data to reduced RGS data. The first block can be modified by the user, providing the location where XMMSAS is installed, the location of the odf files and the observation identification number. There is also an exposure number for RGS1 and RGS2, which in most cases is 004 and 005, respectively, however, it may in some cases be different and can also be provided. The output files will be written into a directory that can be specified with the environment variable outdir. Also the name of a text file must be given in which a number of commands to be carried out in xspec later on will be stored. When completed the script can be executed from the command line with ./cora_rgspipe.sh.
The next step will be to convert the output into the Cora format which has to be done in two steps. The script cora_rgspipe.sh has produced a text file with xspec commands that is adapted to the naming convention of the specific case. First, xspec has to be set up by initializing the heasoftware. Then the commands given in the script have to be carried out in an X-terminal (that is setup for the heasoftware). They can certainly be typed, but copy-and-paste is much easier, as one can copy the complete content of this file into the buffer memory and drop it into the terminal. The second step is to run the IDL script read_rgs.pro as also included in the generated script file. The IDL script requires the astrolib library to be installed. The output consists of two files, rgs1_m1.spec and rgs2_m1.spec, for RGS1 and RGS2 in first dispersion order, respectively. Higher dispersion orders can also be produced by editing read_rgs.pro and the generated script.
We summarize the required steps below.
We found the Lorentzian profile to optimally fit the instrumental line profiles. This can be seen from Fig. 1 were an XMM-RGS spectrum of Capella is shown as an example.