Improved Attitude Correction and Pileup Estimation for Suzaku Data
unix% ./aeattcorr.sl [options] evtfile inattfile outattfile evtfile: The name of the event file inattfile: The input attitude file. outattfile: The output attitude file. Options: --ds9 Display before/after PSF images using ds9 --dt=val Time bin size (secs)  --cel=RA,DEC,R Extraction region with R in arc-seconds --sky=X,Y,R Extraction region in sky pixel coordinates --gtifile=val File with GTIs (default is to use evtfile) --lcfile=FILE Write light-curve info to this file --radius=val Extraction radius (pixels)  -q, --quiet Run quietly -v, --version Print version -h, --help This message Note: The extraction regions are circular and specified as a center and radius. If an extraction region (--cel or --sky) is not given, then ds9 will be used to obtain one interactively.Overview
aeattcor.sl will take a given Suzaku event file and attitude file, and based upon the user's choices, will create a new attitude file that attempts to shift the (time-dependent) mean image position to a new specified, fixed position. The tool presumes that there are no intrinsic variations in the time-dependent image. (Two possible counter examples come to mind: an image with two or more time varying sources of comparable flux, or a highly variable and piled up source where an "image crater" appears and disappears over the course of the observation. Such cases may cause problems for the tool.) The bin time over which the tool searches for and shifts the image peak is a user selectable parameter (--tbin, with the default being 100 seconds). The extraction radius within which the tool calculates the mean image position is also user selectable (via the --cel or --sky options).
The user has three choices for the fixed position to which the time-dependent mean image position will be shifted. The user can specify on the command line an RA & DEC or a sky pixel X & Y, or can use DS9 to graphically determine a location. We present a demonstration of the latter.
The following set of images were generated with the command:
unix% ./aeattcor.sl xis1_3x3.evt ../../auxil/ae402072020.att.gz new.attA DS9 window was created, and an image was extracted from the event file and displayed. The figure below shows the level of the attitude jitter present in these data, even after the standard Suzaku corrections had been applied.
A Suzaku image, where the standard Suzaku attitude correction has already bin applied.
Since no coordinates were specified, the tool prompts for a DS9 region to be selected. The mean image positions will be shifted to the Sky X & Y coordinates of the center of the DS9 region. (Note that the aeattcor.sl tool can also be used to register the Suzaku image to a specific RA & DEC.)
The Suzaku image showing the DS9 selected region within which the tool will search for the time-dependent mean image position.
After the user chooses a region, the tool calculates and saves the new attitude file. (The input attitude file remains unchanged.) It internally applies the correction to the previously read positions from the event file and displays the corrected image, as shown below.
The aeattcor.sl corrected image.
Note, however, that the above corrected image is for display purposes only. If the user wishes to have this correction applied to the event file and have it incorporated into extracted spectra and their generated response files, the user must apply the xiscoord tool. That is, on the command line, one needs to run:
unix% xiscoord infile=xis1_3x3.evt outfile=xis1_fixed.evt \ attitude=new.attLikewise, the corrected attitude file needs to be passed to the xissimarfgen tool in order to be properly accounted for in the generated ARF.
As for the pile_estimate.sl tool, inaccurate results
will be obtained if the event file under analysis contains data
dropouts or periods of telemetry saturation that are not first
removed. (As always, the event file GTI table must also be updated to
reflect any such time filters.) The tool assumes that each image it
creates within a given time interval is `complete'. Telemetry
saturation can lead to data dropouts that result in incomplete images,
as seen in this example:
A Suzaku observation that was affected by data dropouts due to telemetry saturation. Notice the partial images within the integrated image.
These partial images skew the calculations of the mean image location, and hence lead to inaccurate attitude corrections. Such inaccurate attitude corrections should be obvious based upon the final image generated by the tool.
Note, however, that the tool does not apply any attitude corrections directly to the data. The user must apply the corrections via the standard xiscoord command. Thus, no harm will happen to any of the input files, even if the attitude correction tool fails.
This page was last updated Apr 26, 2010 by Michael Nowak. To comment on it or the material presented here, send email to email@example.com.