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Naslov:Performance update of an event-type based analysis for the Cherenkov Telescope Array
Avtorji:ID Bernete, J. (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:.pdf ICRC2023_738.pdf (1,08 MB)
MD5: F6FA9A0F1D02469B21D57EBDA3920E00
 
URL https://pos.sissa.it/444
 
URL https://pos.sissa.it/444/738/pdf
 
Jezik:Angleški jezik
Vrsta gradiva:Neznano
Tipologija:1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:UNG - Univerza v Novi Gorici
Opis:The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. The traditional approach to data analysis in this field is to apply quality cuts, optimized using Monte Carlo simulations, on the data acquired to maximize sensitivity. Subsequent steps of the analysis typically use the surviving events to calculate one set of instrument response functions (IRFs) to physically interpret the results. However, an alternative approach is the use of event types, as implemented in experiments such as the Fermi-LAT. This approach divides events into sub-samples based on their reconstruction quality, and a set of IRFs is calculated for each sub-sample. The sub-samples are then combined in a joint analysis, treating them as independent observations. In previous works we demonstrated that event types, classified using Machine Learning methods according to their expected angular reconstruction quality, have the potential to significantly improve the CTA angular and energy resolution of a point-like source analysis. Now, we validated the production of event-type wise full-enclosure IRFs, ready to be used with science tools (such as Gammapy and ctools). We will report on the impact of using such an event-type classification on CTA high-level performance, compared to the traditional procedure.
Ključne besede:Cherenkov Telescope Array, CTA, very-high-energy gamma-ray astroparticle physics, instrument response functions, machine learning
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:01.01.2023
Leto izida:2023
Št. strani:str. 1-15
PID:20.500.12556/RUNG-8452-7e59d9fd-33e5-7f59-075b-1a014b15e1b4 Novo okno
COBISS.SI-ID:165800451 Novo okno
UDK:539.1
ISSN pri članku:1824-8039
NUK URN:URN:SI:UNG:REP:UOJOBVWJ
Datum objave v RUNG:26.09.2023
Število ogledov:1078
Število prenosov:7
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
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Gradivo je del zbornika

Naslov:38th International Cosmic Ray Conference [also] ICRC2023
COBISS.SI-ID:162195971 Novo okno

Gradivo je del revije

Naslov:Proceedings of science
Skrajšan naslov:Pos proc. sci.
Založnik:Sissa
ISSN:1824-8039
COBISS.SI-ID:20239655 Novo okno

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P1-0031
Naslov:Večglasniška astrofizika

Licence

Licenca:CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
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