cssens

Computes differential or integrated CTA sensitivity.

Synopsis

This script computes the differential or integrated CTA sensitivity using maximum likelihood fitting of a test source. The differential sensitivity is determined for a number of energy bins, the integral sensitivity is determined for a number of energy thresholds. The test source is fitted to simulated data using ctlike to determine it’s detection significance as a function of source flux. The source flux is then varied until the source significance achieves a given level, specified by the (hidden) significance parameter sigma. To damp variations between individual Monte Carlo simulations, a sliding average is applied in the significance computation (controlled by hidden num_avg parameter).

The significance is estimated using the Test Statistic value, defined as twice the log-likelihood difference that is obtained when fitting the simulated data with and without the test source. The simplified assumption is made that the significance (in Gaussian sigma) is the square root of the Test Statistic.

cssens will generate an ASCII file in comma-separated value (CSV) format containing the sensitivity as function of energy. The first row is a header row providing the column names. The following rows provide the mean logarithmic energy and the boundaries of the energy bin for which the sensitivity was computed. They also provide the flux within the energy bin in Crab units, in photons (ph/cm2/s) and in energy (erg/cm2/s). Finally, the sensitivity is given as the test source spectrum evaluated at the mean logarithmic energy multiplied by the energy squared (erg/cm2/s).

The sensitivity can be displayed using the show_sensitivity.py script in the example folder. Matplotlib is required to execute the script.

General parameters

(inobs = NONE) [file]

Input event list, counts cube or observation definition XML file.

inmodel [file]

Input model XML file.

srcname [string]

Name of the source in the source model XML file which should be used for sensitivity computation.

(offset = 0.0) [real]

Offset angle of source in field of view (in degrees).

caldb [string]

Calibration database.

irf [string]

Instrumental response function.

(deadc = 0.95) [real]

Average deadtime correction factor.

outfile [file]

ASCII file containing the sensitivity values.

duration [real]

Effective exposure time (in seconds).

rad [real]

Radius of Region of Interest (RoI) (in degrees).

emin [real]

Lower energy limit for sensitivity computation (in TeV).

emax [real]

Upper energy limit for sensitivity computation (in TeV).

bins [integer]

Number of energy bins for sensitivity computation.

(enumbins = 0) [integer]

Number of energy bins (0=unbinned).

(npix = 200) [integer]

Number of pixels for binned analysis.

(binsz = 0.05) [real]

Pixel size for binned analysis.

(type = Differential) <Differential|Integral> [string]

Sensitivity type.

(sigma = 5.0) [real]

Significance threshold.

(max_iter = 50) [integer]

Maximum number of iterations.

(num_avg = 3) [integer]

Number of iterations for sliding average.

Standard parameters

(chatter = 2) [integer]

Verbosity of the executable:

chatter = 0: no information will be logged

chatter = 1: only errors will be logged

chatter = 2: errors and actions will be logged

chatter = 3: report about the task execution

chatter = 4: detailed report about the task execution

(clobber = yes) [boolean]

Specifies whether an existing output file should be overwritten.

(debug = no) [boolean]

Enables debug mode. In debug mode the executable will dump any log file output to the console.

(mode = ql) [string]

Mode of automatic parameters (default is “ql”, i.e. “query and learn”).

(logfile = cssens.log) [filename]

Log filename.

Related tools or scripts

ctlike