2018A&A...619A...7V


Query : 2018A&A...619A...7V

2018A&A...619A...7V - Astronomy and Astrophysics, volume 619A, 7-7 (2018/11-1)

Spatial likelihood analysis for MAGIC telescope data. From instrument response modelling to spectral extraction.

VOVK I., STRZYS M. and FRUCK C.

Abstract (from CDS):


Context. The increase in sensitivity of Imaging Atmospheric Cherenkov Telescopes (IACTs) has lead to numerous detections of extended γ-ray sources at TeV energies, sometimes of sizes comparable to the instrument's field of view. This creates a demand for advanced and flexible data analysis methods that are able to extract source information using the photon counts in the entire field of view.
Aims. We present a new software package, "SkyPrism", aimed at performing 2D (3D if energy is considered) fits of IACT data that possibly contain multiple and extended sources. The fits are based on sky images binned in energy. Although the development of this package was focused on the analysis of data collected with the MAGIC telescopes, it can further be adapted to other instruments, such as the future Cherenkov Telescope Array.
Methods. We have developed a set of tools that in addition to sky images (count maps) compute the instrument response functions of MAGIC (effective exposure throughout the field of view, point spread function, energy resolution, and background shape) based on the input data, Monte Carlo simulations, and the pointing track of the telescopes. With this information, the package can perform a simultaneous maximum likelihood fit of source models of arbitrary morphology to the sky images providing energy spectra, detection significances, and upper limits.
Results. We demonstrate that the SkyPrism tool accurately reconstructs the MAGIC point spread function, on- and off-axis performance as well as the underlying background. We further show that for a point source analysis with the MAGIC default observational settings, SkyPrism gives results compatible with those of the standard tools while being more flexible and widely applicable.

Abstract Copyright: © ESO 2018

Journal keyword(s): gamma rays: general - methods: data analysis - techniques: image processing

Simbad objects: 2

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Number of rows : 2
N Identifier Otype ICRS (J2000)
RA
ICRS (J2000)
DEC
Mag U Mag B Mag V Mag R Mag I Sp type #ref
1850 - 2024
#notes
1 M 1 SNR 05 34 30.9 +22 00 53           ~ 6193 1
2 Mrk 421 BLL 11 04 27.3140835504 +38 12 31.798495872   13.50 12.90 8.31   ~ 2675 1

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