Sökning: onr:"swepub:oai:lup.lub.lu.se:bf657ed0-7f8a-4556-9b12-986a41653bcd" >
Reconstruction of s...
Reconstruction of stereoscopic CTA events using deep learning with CTLearn
-
- Miener, T. (författare)
- Complutense University of Madrid
-
- Nieto, D. (författare)
- Complutense University of Madrid
-
- Brill, A. (författare)
- Columbia University
-
visa fler...
-
- Spencer, S. (författare)
- University of Oxford
-
- Carlile, C. (författare)
- Lund University,Lunds universitet,Astronomi - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Lund Observatory - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science
-
- Dravins, D. (författare)
- Lund University,Lunds universitet,Astronomi - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Lund Observatory - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science
-
- Zmija, A. (författare)
- Friedrich-Alexander University Erlangen-Nürnberg
-
visa färre...
-
(creator_code:org_t)
-
- Trieste, Italy : Sissa Medialab, 2022
- 2022
- Engelska.
-
Ingår i: 37th International Cosmic Ray Conference (ICRC2021) - GAI - Gamma Ray Indirect. - Trieste, Italy : Sissa Medialab. - 1824-8039. ; 395
- Relaterad länk:
-
http://dx.doi.org/10... (free)
-
visa fler...
-
https://pos.sissa.it...
-
https://lup.lub.lu.s...
-
https://doi.org/10.2...
-
visa färre...
Abstract
Ämnesord
Stäng
- The Cherenkov Telescope Array (CTA), conceived as an array of tens of imaging atmospheric Cherenkov telescopes (IACTs), is an international project for a next-generation ground-based gamma-ray observatory, aiming to improve on the sensitivity of current-generation instruments a factor of five to ten and provide energy coverage from 20 GeV to more than 300 TeV. Arrays of IACTs probe the very-high-energy gamma-ray sky. Their working principle consists of the simultaneous observation of air showers initiated by the interaction of very-high-energy gamma rays and cosmic rays with the atmosphere. Cherenkov photons induced by a given shower are focused onto the camera plane of the telescopes in the array, producing a multi-stereoscopic record of the event. This image contains the longitudinal development of the air shower, together with its spatial, temporal, and calorimetric information. The properties of the originating very-high-energy particle (type, energy, and incoming direction) can be inferred from those images by reconstructing the full event using machine learning techniques. In this contribution, we present a purely deep-learning driven, full-event reconstruction of simulated, stereoscopic IACT events using CTLearn. CTLearn is a package that includes modules for loading and manipulating IACT data and for running deep learning models, using pixel-wise camera data as input. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)
Ämnesord
- NATURVETENSKAP -- Fysik -- Astronomi, astrofysik och kosmologi (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences -- Astronomy, Astrophysics and Cosmology (hsv//eng)
Nyckelord
- Cosmic rays
- Cosmology
- Deep learning
- Gamma rays
- Germanium alloys
- Germanium compounds
- Stereo image processing
- Telescopes
- Tellurium compounds
- Air showers
- Cherenkov telescope arrays
- Current generation
- Energy
- Gamma ray observatories
- Ground based
- High energy gamma rays
- Imaging atmospheric Cherenkov telescopes
- International projects
- Very high energies
- Cameras
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
Hitta via bibliotek
Till lärosätets databas