Review
Version 1
Preserved in Portico This version is not peer-reviewed
Statistical Tools for Imaging Atmospheric Cherenkov Telescopes
Version 1
: Received: 22 January 2022 / Approved: 24 January 2022 / Online: 24 January 2022 (11:30:19 CET)
A peer-reviewed article of this Preprint also exists.
D’Amico, G. Statistical Tools for Imaging Atmospheric Cherenkov Telescopes. Universe 2022, 8, 90. D’Amico, G. Statistical Tools for Imaging Atmospheric Cherenkov Telescopes. Universe 2022, 8, 90.
Abstract
The development of Imaging Atmospheric Cherenkov Telescopes (IACTs) unveiled the sky in the teraelectronvolt regime, initiating the so-called “TeV revolution” at the beginning of the new millennium. This revolution was also facilitated by the implementation and adaptation of statistical tools for analyzing the shower images collected by these telescopes and inferring the properties of the astrophysical sources that produce such events. The image reconstruction techniques, the background discrimination and the signal-detection analyses are just a few of the pioneering studies applied in the last decades in the analysis of IACTs data. This (succinct) review has the intent of summarizing the most common statistical tools that are used for analyzing data collected with IACTs, focusing on their application in the full analysis chain, giving references to the past literature for a deepened examination.
Keywords
Statistical analysis; gamma-rays; IACTs; likelihood; Bayes.
Subject
Physical Sciences, Astronomy and Astrophysics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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