{"title":"A background-estimation technique for the detection of extended gamma-ray structures with IACTs","authors":"Tina Wach, Alison Mitchell, Lars Mohrmann","doi":"arxiv-2409.02527","DOIUrl":null,"url":null,"abstract":"Estimation of the amount of cosmic-ray induced background events is a\nchallenging task for Imaging Atmospheric Cherenkov Telescopes (IACTs). Most\napproaches rely on a model of the background signal derived from archival\nobservations, which is then normalised to the region of interest (ROI) and\nrespective observation conditions using emission-free regions in the\nobservation.This is, however, disadvantageous for the analysis of large,\nextended $\\gamma$-ray structures, where no sufficient source free region can be\nfound. We aim to address this issue by estimating the normalisation of a\n3-dimensional background model template from separate, matched observations of\nemission-free sky regions. As a result, the need for a emission-free region in\nthe field of view of the observation becomes unnecessary. For this purpose, we\nimplement an algorithm to identify observation pairs with as close as possible\nobservation conditions. The open-source analysis package Gammapy is utilized\nfor estimating the background rate, facilitating seamless adaptation of the\nframework to many $\\gamma$-ray detection facilities. Public data from the High\nEnergy Stereoscopic System (H.E.S.S.) is employed to validate this methodology.\nThe analysis demonstrates that employing a background rate estimated through\nthis run-matching approach yields results consistent with those obtained using\nthe standard application of the background model template. Furthermore, the\ncompatibility of the source parameters obtained through this approach with\nprevious publications and an analysis employing the background model template\napproach is confirmed, along with an estimation of the statistical and\nsystematic uncertainties introduced by this method.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.02527","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Estimation of the amount of cosmic-ray induced background events is a
challenging task for Imaging Atmospheric Cherenkov Telescopes (IACTs). Most
approaches rely on a model of the background signal derived from archival
observations, which is then normalised to the region of interest (ROI) and
respective observation conditions using emission-free regions in the
observation.This is, however, disadvantageous for the analysis of large,
extended $\gamma$-ray structures, where no sufficient source free region can be
found. We aim to address this issue by estimating the normalisation of a
3-dimensional background model template from separate, matched observations of
emission-free sky regions. As a result, the need for a emission-free region in
the field of view of the observation becomes unnecessary. For this purpose, we
implement an algorithm to identify observation pairs with as close as possible
observation conditions. The open-source analysis package Gammapy is utilized
for estimating the background rate, facilitating seamless adaptation of the
framework to many $\gamma$-ray detection facilities. Public data from the High
Energy Stereoscopic System (H.E.S.S.) is employed to validate this methodology.
The analysis demonstrates that employing a background rate estimated through
this run-matching approach yields results consistent with those obtained using
the standard application of the background model template. Furthermore, the
compatibility of the source parameters obtained through this approach with
previous publications and an analysis employing the background model template
approach is confirmed, along with an estimation of the statistical and
systematic uncertainties introduced by this method.