Reconstruction of extensive air shower images of the Large Size Telescope prototype of CTA using a novel likelihood technique

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  • uploaded June 25, 2021

Discussion timeslot (ZOOM-Meeting): 13. July 2021 - 12:00
ZOOM-Meeting URL: https://desy.zoom.us/j/98542982538
ZOOM-Meeting ID: 98542982538
ZOOM-Meeting Passcode: ICRC2021
Corresponding Session: https://icrc2021-venue.desy.de/channel/52-Analysis-Methods-Catalogues-Community-Tools-Machine-Learning-GAD-GAI/64
Live-Stream URL: https://icrc2021-venue.desy.de/livestream/Discussion-04/5

Abstract:
'Ground-based gamma-ray astronomy requires reconstructing extensive air showers initiated by gamma rays impinging on the atmosphere. Imaging atmospheric Cherenkov telescopes collect the Cherenkov light induced by secondary charged particles in extensive air showers, creating an image of the shower in a camera. This image is parametrized and used to evaluate the type, energy and arrival direction of the primary particle that initiated the shower. This contribution shows the results of a novel reconstruction method based on likelihood maximization. The method is applied to observations of the Crab Nebula acquired with the Large Size Telescope prototype (LST-1) deployed at the Northern site of the Cherenkov Telescope Array. The novelty with respect to previous likelihood reconstruction methods lies in the definition of a likelihood per single camera pixel, accounting not only for the total measured charge, but also for its development over time. It considers the waveform acquired by each pixel involved in the reconstruction of the shower. This reconstruction, which considers also the response characteristics of the sensor in the camera pixel, leads to improved reconstruction of shower images and consequently allows for the recovery of the primary particles properties with an improved accuracy.'

Authors: Gabriel Emery | Cyril Alispach | Mykhailo Dalchenko | Luca Foffano | Matthieu Heller | Teresa Montaruli | For the CTA LST project
Collaboration: CTA

Indico-ID: 459
Proceeding URL: https://pos.sissa.it/395/716

Tags:
Presenter: Gabriel Emery

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