Naslov: | Pybkgmodel - a background modelling toolbox for the CTA |
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Avtorji: | ID Strzys, Marcel C. (Avtor) ID Bhattacharyya, Saptashwa (Avtor) ID Pérez Romero, Judit (Avtor) ID Stanič, Samo (Avtor) ID Vodeb, Veronika (Avtor) ID Vorobiov, Serguei (Avtor) ID Zavrtanik, Danilo (Avtor) ID Zavrtanik, Marko (Avtor) ID Živec, Miha (Avtor), et al. |
Datoteke: | ICRC2023_894.pdf (1,46 MB) MD5: 5480C5D08B99397D7B5BC09ADC66DD97
https://pos.sissa.it/444
https://pos.sissa.it/444/894/pdf
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Jezik: | Angleški jezik |
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Vrsta gradiva: | Neznano |
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Tipologija: | 1.08 - Objavljeni znanstveni prispevek na konferenci |
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Organizacija: | UNG - Univerza v Novi Gorici
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Opis: | Despite the advancement in background rejection techniques, observation of the very-high-energy gamma-ray sky by imaging atmospheric Cherenkov telescopes (IACTs) are subject to an irreducible background from gamma-like hadron- or electron-induced air showers. The determination of this residual background is crucial for accurate spectral and spatial measurements.
The Cherenkov Telescope Array (CTA) will become the next generation of IACTs. To unveil its full potential, the improved reconstruction performance of CTA needs to be coupled with a reliable background estimate across the entire field of view. This may become especially important in the case of the planned surveys of large areas of the sky.
In this contribution we will present pybkgmodel, an open-source python software package de-veloped for CTA. It aims at providing in a consistent way the various background modelling methods, based on the experience from current IACTs such as H.E.S.S, MAGIC, and VERITAS. It is designed as a toolbox allowing a user to easily choose the optimal reconstruction approach for various target regions or a combination of several algorithms. We will introduce the design of the package as well as demonstrate its functionality using data for the CTA Large-Sized Telescope prototype (LST-1). |
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Ključne besede: | Cherenkov Telescope Array, CTA, dark matter, standard model, dwarf spheroidal galaxies |
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Status publikacije: | Objavljeno |
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Verzija publikacije: | Objavljena publikacija |
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Datum objave: | 01.01.2023 |
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Leto izida: | 2023 |
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Št. strani: | str. 1-17 |
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PID: | 20.500.12556/RUNG-8458-a458b7c3-c1b9-88c2-7ce7-709d45154870 |
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COBISS.SI-ID: | 165840131 |
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UDK: | 539.1 |
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ISSN pri članku: | 1824-8039 |
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NUK URN: | URN:SI:UNG:REP:VI9LL3KG |
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Datum objave v RUNG: | 26.09.2023 |
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Število ogledov: | 1938 |
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Število prenosov: | 8 |
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Metapodatki: | |
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