Pybkgmodel - a background modelling toolbox for the CTA

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985815%3A_____%2F24%3A00636923" target="_blank" >RIV/67985815:_____/24:00636923 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68378271:_____/24:00636923

Výsledek na webu

<a href="https://pos.sissa.it/444/894/pdf" target="_blank" >https://pos.sissa.it/444/894/pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.22323/1.444.0894" target="_blank" >10.22323/1.444.0894</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Pybkgmodel - a background modelling toolbox for the CTA

Popis výsledku v původním jazyce

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 developed 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 performance using simulations for the CTA Large-Sized Telescope prototype (LST-1).

Název v anglickém jazyce

Pybkgmodel - a background modelling toolbox for the CTA

Popis výsledku anglicky

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 developed 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 performance using simulations for the CTA Large-Sized Telescope prototype (LST-1).

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10308 - Astronomy (including astrophysics,space science)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of Science

ISBN

—

ISSN

1824-8039

e-ISSN

—

Počet stran výsledku

17

Strana od-do

894

Název nakladatele

Sissa Medilab srl

Místo vydání

Trieste

Místo konání akce

Nagoya

Datum konání akce

26. 7. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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