Prospects for the use of photosensor timing information with machine learning techniques in background rejection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F21%3A00551835" target="_blank" >RIV/68378271:_____/21:00551835 - isvavai.cz</a>

Výsledek na webu

<a href="https://pos.sissa.it/358/798/pdf" target="_blank" >https://pos.sissa.it/358/798/pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.22323/1.358.0798" target="_blank" >10.22323/1.358.0798</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prospects for the use of photosensor timing information with machine learning techniques in background rejection

Popis výsledku v původním jazyce

Recent developments in machine learning (ML) techniques present a promising new analysis method for high-speed imaging in astroparticle physics experiments, for example with imaging atmospheric Cherenkov telescopes (IACTs). In particular, the use of timing information with new machine learning techniques provides a novel method for event classification. Previous work in this field has utilised images of the integrated charge from IACT camera photomultipliers, but the majority of current and upcoming IACT cameras have the capacity to read out the entire photosensor waveform following a trigger. As the arrival times of Cherenkov photons from extensive air showers (EAS) at the camera plane are dependent upon the altitude of their emission, these waveforms contain information useful for IACT event classification.

Název v anglickém jazyce

Prospects for the use of photosensor timing information with machine learning techniques in background rejection

Popis výsledku anglicky

Recent developments in machine learning (ML) techniques present a promising new analysis method for high-speed imaging in astroparticle physics experiments, for example with imaging atmospheric Cherenkov telescopes (IACTs). In particular, the use of timing information with new machine learning techniques provides a novel method for event classification. Previous work in this field has utilised images of the integrated charge from IACT camera photomultipliers, but the majority of current and upcoming IACT cameras have the capacity to read out the entire photosensor waveform following a trigger. As the arrival times of Cherenkov photons from extensive air showers (EAS) at the camera plane are dependent upon the altitude of their emission, these waveforms contain information useful for IACT event classification.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10303 - Particles and field physics

Projekt

—

Návaznosti

—

Rok uplatnění

2021

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

8

Strana od-do

1-8

Název nakladatele

Sissa Medilab srl

Místo vydání

Trieste

Místo konání akce

Madison, WI

Datum konání akce

24. 7. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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