|
Introduction
This thread is a step-by-step recipe to run the source detection chain in
SAS. It shows how to run all the individual SAS tasks constituting the
source detection meta-task
edetect_chain.
Expected Outcome
At the end of this thread, users will be able to generate a single
list of the sources
detected in a EPIC (MOS in the example) image, as well as a number of associated products
such as background and sensitivity maps. The same procedure can be simultaneously
applied to an arbitrary
(but lower then 56) number of images extracted from event lists
of the three EPIC cameras in, e.g., different energy bands. The
last step of this thread shows how the sources in a source list can be
plotted on top of an image.
SAS Tasks to be Used
Prerequisites
Useful Links
This thread makes use of the image display and analysis package ds9.
Caveats
|
Procedure
This thread illustrates a step-by-step recipe to perform EPIC
sources detection. All the individual steps encompassed by the
source detection task
edetect_chain
are here commented individually. We stress that a user does not
need to run these steps separately, as the input parameters of
all the SAS tasks launched by
edetect_chain
can be set as
edetect_chain
input parameters. However, some users - in particular SAS novices -
may find useful to perform each individual step of the
source detection algorithm, to achieve a
better control and understanding of its outcomes.
In this thread, we will assume that a user intends to detect sources
on a single MOS image, extracted in the 0.2-10 keV band.
The event list
MOS.evt is assumed to have been
already cleaned for high-background intervals, following,
e.g., steps 3. to 5. in the
edetect_chain thread.
- set up your SAS environment (following the
SAS
start-up thread)
- produce the MOS image in the 0.2-10 keV energy band from the
calibrated event list (file MOS.evt)
evselect table=MOS.evt:EVENTS imagebinning='binSize' \
imageset='mos_image_full.fits' withimageset=yes xcolumn='X' ycolumn='Y' \
ximagebinsize=80 yimagebinsize=80 \
expression='#XMMEA_EM&&(PI in [200:10000])&&(PATTERN \
in [0:12])&& gti(mos_back_gti.fits,TIME)'
- create an exposure map
eexpmap attitudeset=AttHK.ds eventset=MOS.evt imageset=mos_image_full.fits \
expimageset=MOS_expmap.ds pimin="200" pimax="10000"
where AttHK.ds is the attitude history file (file *ATT*FIT
in the PPS products). An example of exposure map is shown in Fig.1
Fig.1: Example of MOS exposure map
- create a detection map (masking the areas of the field of view
where source detection shall not not be performed)
emask expimageset=MOS_expmap.ds threshold1=0.25 detmaskset=MOS_mask.ds
where threshold1 indicates the maximum exposure fraction for a
masked pixel (see the
emask parameters description).
In this specific example all pixels whose exposure time is
lower than 0.25 times the maximum exposure are given value "0" in the mask,
and excluded from the area where the source detection is performed.
Users may relax this choice after a careful
look at the exposure map, if they want to seek sources
on a larger area.
An example of MOS mask is shown in Fig.2
Fig.2: Example of MOS mask
- perform a sliding box detection, using locally estimated background
eboxdetect usemap=no likemin=8 withdetmask=yes detmasksets=MOS_mask.ds \
imagesets=mos_image_full.fits expimagesets=MOS_expmap.ds pimin=200 \
pimax=10000 boxlistset=eboxlist_local.fits
where likemin is the
minimum detection likelihood
(see the eboxdetect
parameters description as well).
- creating a background map, after masking the sources detected
during the previous step:
esplinemap bkgimageset=MOS_bkg.ds scut=0.005 imageset=mos_image_full.fits \
nsplinenodes=16 withdetmask=yes detmaskset=MOS_mask.ds withexpimage=yes \
expimageset=MOS_expmap.ds boxlistset=eboxlist_local.fits
where nsplinenodes is the number of nodes employed in the background
map interpolation and scut the source surface brightness level (in
counts per arcseconds squared), above which a source is masked
(see the esplinemap
parameters description). Particular care needs
to be used in the choice of nsplinenodes. A small number of nodes
may fail to accurately reproduce the background spatial distribution; an
excessive number of nodes may create faked structures. The optimal
compromise depends on the spatial pattern of the X-ray emission
(background+sources) in a
given field of view. Users are encouraged to try different choices
for this parameter, and compare the resulting maps with the observed
background spatial distribution pattern. The parameter scut
mainly drives the amount of source contamination
to the interpolated background map, due to the broad wings of the
Point Spread Function. The best value of scut is determined by the optimal
balance between background integration area and acceptable
source contamination level. This is obviously dependent on the
amount of background and the on how crowd the field is. Users are
encouraged to check the background maps produced by
esplinemap
for short-scale fluctuations, and tune the scut value accordingly.
An example of MOS background map is shown in Fig.3.
Fig.3: Example of MOS background map
- perform a second run of source detection, using the background map
calculated during the previous step
eboxdetect usemap=yes bkgimagesets=MOS_bkg.ds likemin=8 withdetmask=yes \
detmasksets=MOS_mask.ds imagesets=mos_image_full.fits \
expimagesets=MOS_expmap.ds pimin=200 pimax=10000 boxlistset=eboxlist_map.fits
- maximum likelihood fitting on the sources detected in the previous step, to:
- optimise source centring (constrained to be the same for all
the cameras and/or energy bands, if source detection is
performed on multiple images)
- determine source extend by fitting the local Point Spread Function
emldetect imagesets=mos_image_full.fits expimagesets=MOS_expmap.ds \
bkgimagesets=MOS_bkg.ds boxlistset=eboxlist_map.fits ecf=2.0 \
mllistset=emllist.fits mlmin=10 determineerrors=yes
The ecf is the Energy Correction Factor
to convert count rates (counts/s) to fluxes (10-11 erg/s/cm2)
in a given energy band (a standard definition is reported in Section 6.2.1
of the
2XMM EPIC Source Catalogue User Guide).
- create sensitivity maps, i.e. a pixel-by-pixel detection upper limit map.
esensmap expimagesets=MOS_expmap.ds bkgimagesets=MOS_bkg.ds \
detmasksets=MOS_mask.ds mlmin=10 sensimageset=MOS_sens_map.fits
An example of MOS sensitivity map is shown in Fig.4.
Fig.4: Example of MOS sensitivity map
- Display the location of the detected sources on the MOS image
srcdisplay boxlistset=emllist.fits imageset=mos_image_full.fits
sourceradius=0.01
Last Updated: 8 June 2010
