Soft Proton Background

Many, if not most, observations have some residual SPF contamination after light curve screening. To determine the level of the residual contamination, if any, and to remove it first requires spectral fitting of the data. In the spectral fitting process, a power law (or broken power law) which is not folded through the instrumental effective areas is added to the model. See §6.3 and §6.6.

After the spectral parameters for the SPF contamination have been derived, the task proton can be run. If there is no additional normalization applied to the Xspec model, the SPF spectral parameters as displayed by Xspec for the full FOV (normalization: counts keV$^{-1}$ s$^{-1}$, power law index: the negative photon index) can be input into proton. The proton routine produces an image in detector coordinates. The following is an example of a call of proton and rotdet2sky for the MOS:

proton imagefile=mos2S002-fovimdet-350-1100.fits
specfile=mos2S002-fovt.pi elow=350 ehigh=1100
speccontrol=1 pindex=0.1 pnorm=2.208e-2


proton imagefile=mos2S002-fovimdet-350-1100.fits
specfile=mos2S002-fovt.pi elow=350 ehigh=1100
speccontrol=2 bindl=0.1 bbreak=1.0
bindh=1.0 bnorm=2.208e-2

where imagefile is the image for the appropriate detector in detector coordinates. specfile=mos2S002-fovt.pi provides a file for the extraction of the EXPOSURE keyword, and must be the spectrum used in the spectral fits where the magnitude of the residual SPF contamination was determined. The values of elow, and ehigh are as defined above and must be the same values as used in mosspectra, pnspectra, mosback, and pnback. The spectrumcontrol flag controls the spectrum mode: spectrumcontrol=1 for a power-law spectrum and spectrumcontrol=2 for a broken power-law spectrum. pindex is the power-law index and pnorm is the power-law normalization taken directly from the Xspec fit for entire FOV for which the image is to be created. bindl, bindh, bbreak, and bnorm are the low and high energy spectral indices, the break energy (in keV), and the broken power law normalization taken from the spectral fit.

Figure 26 (upper panel) shows the MOS1 SPF background image for the Abell-1795 observation for the $0.4-1.25$ keV band in detector coordinates. rotdet2sky is run to convert the image from detector to sky coordinates (shown in Figure 26, lower panel).

As for the particle background maps, after proton has been run, rotdet2sky must be run to recast the SPF image from detector coordinates to sky coordinates.

rotdet2sky intemplate=mos2S002-fovimsky-350-1100.fits

In cases where there is strong emission from the extended source, as there can be for clusters of galaxies, the fitted parameters for the SPF component can be significantly over or under estimated. In such cases it can be helpful to fit a spectrum extracted from the lower surface brightness regions in the field. For clusters of galaxies an outer annulus in the FOV can serve this purpose. However, in this case, the fitted normalization must be scaled from the limited region to the full FOV, which can be done by the routine sppartial:

sppartial fullimage=ffov/mos1S001-fovimspdet.fits

where fullimage=ffov/mos1S003-sp-full.fits is the SPF image template for the full FOV, fullspec=ffov/mos1S003-obj-all.pi is the spectrum for the full FOV, regionimage=annu/mos1S003-sp-ann.fits is the SPF template image for the restricted region, regionspec=annu/mos1S003-obj-ann.pi is the spectrum for the restricted region, and rnorm=0.03 is the fitted SPF normalization for the restricted region. (Here I've assumed that the extraction from the full FOV has ended up in a subdirectory named ffov while the extraction from the partial FOV has ended up in a subdirectory named annu.) In the proton call use the fitted spectral index from the restricted region and the scaled value for the normalization.

Figure 26: Images of the model SPF background in detector coordinates (upper panel, the output of proton) and in sky coordinates (lower panel, output of rotdet2sky). Note that values are both negative and positive due to the method for creating the instrument maps. On average the values are positive and the count images are sparse requiring averaging on angular scales where the SPF values provide good information.