This task operates in conjunction with the tasks econvolverprep and sensitivity; users should consult the documentation for all three of these tasks together.
esensitivity
is, in a sense, the inverse of eboxdetect, which, as most users know, searches for point sources in XMM EPIC images. eboxdetect
finds sources by comparing the number of x-ray events 
which fall within a square sliding box with the expected number of background events
expected to occur within the same box. At locations where the detection likelihood 
, which is minus log of the probability that the detected counts is due to a Poissonian statistical fluctuation of the background, exceeds a certain limit, the software reports the occurrence of a point source. At any given pixel of the input image there is, therefore, a fixed relationship between ,
and . The essential task of esensitivity
is to invert this relationship, ie to answer the question: given a cutoff value of detection likelihood
and the expected background counts
, to what value of detected counts 
do these numbers correspond. thus represents the minimum value of counts which will be classified by eboxdetect
as a source.
The above description assumes that source detection is carried out on a single image. However eboxdetect is far more commonly employed to search for point sources on several images in parallel. These images are assumed to be of the same part of the sky but in different energy bands. In this case the recipe for calculating likelihood is a little more complicated. esensitivity can invert this style of source detection too but the reader is referred to the task documentation of sensitivity for details of the algorithm. sensitivity is the task which actually performs the inversion.
esensitivity is a perl script which calls firstly asmooth in order to convolve the background maps with the detection box; then a task called econvolverprep which calculates the relationship at each image pixel between total counts beneath the point spread function (PSF) and the counts falling within the detection box; finally sensitivity is called. The output is a series of images, 1 per energy band, which map the value of source count rate which would just be large enough to be detected on average as a point source in the corresponding input image.
XMM-Newton SOC/SSC -- 2005-08-16