Extraction of the muon signals recorded with the surface detector of the Pierre Auger Observatory using recurrent neural networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F21%3A00550820" target="_blank" >RIV/68378271:_____/21:00550820 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/21:10439713 RIV/61989592:15310/21:73608957

Výsledek na webu

<a href="https://doi.org/10.1088/1748-0221/16/07/P07016" target="_blank" >https://doi.org/10.1088/1748-0221/16/07/P07016</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1748-0221/16/07/P07016" target="_blank" >10.1088/1748-0221/16/07/P07016</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Extraction of the muon signals recorded with the surface detector of the Pierre Auger Observatory using recurrent neural networks

Popis výsledku v původním jazyce

The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from 10(17) eV up to more than 10(20) eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightforwardly separate the contributions of muons to the SD time traces from those of photons, electrons and positrons. In this paper, we present a method aimed at extracting the muon component of the time traces registered with each individual detector of the SD using Recurrent Neural Networks.n

Název v anglickém jazyce

Extraction of the muon signals recorded with the surface detector of the Pierre Auger Observatory using recurrent neural networks

Popis výsledku anglicky

The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from 10(17) eV up to more than 10(20) eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightforwardly separate the contributions of muons to the SD time traces from those of photons, electrons and positrons. In this paper, we present a method aimed at extracting the muon component of the time traces registered with each individual detector of the SD using Recurrent Neural Networks.n

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10303 - Particles and field physics

Projekt

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

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Journal of Instrumentation

ISSN

1748-0221

e-ISSN

1748-0221

Svazek periodika

16

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

22

Strana od-do

P07016

Kód UT WoS článku

000702560000001

EID výsledku v databázi Scopus

2-s2.0-85110748213