First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep Learning - Archive ouverte HAL Access content directly
Conference Papers Year : 2021

First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep Learning

Abstract

The Cherenkov Telescope Array is the future of ground-based gamma-ray astronomy. Its first prototype telescope built on-site, the Large Size Telescope 1, is currently under commissioning and taking its first scientific data. In this paper, we present for the first time the development of a full-event reconstruction based on deep convolutional neural networks and its application to real data. We show that it outperforms the standard analysis, both on simulated and on real data, thus validating the deep approach for the CTA data analysis. This work also illustrates the difficulty of moving from simulated data to actual data.
Fichier principal
Vignette du fichier
CBMI2021_ID23_jacquemont_camera_ready.pdf (654.59 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03241475 , version 2 (28-05-2021)
hal-03241475 , version 1 (16-06-2021)

Identifiers

Cite

Mikaël Jacquemont, Thomas Vuillaume, Alexandre Benoit, Gilles Maurin, Patrick Lambert, et al.. First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep Learning. International Conference on Content-Based Multimedia Indexing (CBMI), Jun 2021, Lille, France. 6 p., ⟨10.1109/CBMI50038.2021.9461918⟩. ⟨hal-03241475v2⟩
171 View
142 Download

Altmetric

Share

Gmail Facebook X LinkedIn More