Related papers: IACT event analysis with the MAGIC telescopes usin…

The performance of the MAGIC telescopes using deep convolutional neural networks with CTLearn

The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescope system is located on the Canary Island of La Palma and inspects the very high-energy (VHE, few tens of GeV and above) gamma-ray sky. MAGIC consists of two imaging atmospheric…

Instrumentation and Methods for Astrophysics · Physics 2022-11-30 T. Miener , D. Nieto , R. López-Coto , J. L. Contreras , J. G. Green , D. Green , E. Mariotti on behalf of the MAGIC Collaboration

Reconstruction of IACT events using deep learning techniques with CTLearn

Arrays of imaging atmospheric Cherenkov telescopes (IACT) are superb instruments to probe the very-high-energy gamma-ray sky. This type of telescope focuses the Cherenkov light emitted from air showers, initiated by very-high-energy gamma…

Instrumentation and Methods for Astrophysics · Physics 2021-01-20 D. Nieto , T. Miener , A. Brill , J. L. Contreras , T. B. Humensky , R. Mukherjee

First IACT Waveform Analysis Based on Deep Convolutional Neural Networks Using CTLearn

Imaging atmospheric Cherenkov telescopes (IACTs) detect extended air showers (EASs) generated when very-high-energy (VHE) gamma rays or cosmic rays interact with the Earth's atmosphere. Cherenkov photons produced during an EAS are captured…

High Energy Astrophysical Phenomena · Physics 2025-09-19 T. Miener , L. Burmistrov , B. Lacave , A. Cerviño

Investigating a Deep Learning Method to Analyze Images from Multiple Gamma-ray Telescopes

Imaging atmospheric Cherenkov telescope (IACT) arrays record images from air showers initiated by gamma rays entering the atmosphere, allowing astrophysical sources to be observed at very high energies. To maximize IACT sensitivity,…

Instrumentation and Methods for Astrophysics · Physics 2020-01-13 Aryeh Brill , Qi Feng , T. Brian Humensky , Bryan Kim , Daniel Nieto , Tjark Miener

Processing Images from Multiple IACTs in the TAIGA Experiment with Convolutional Neural Networks

Extensive air showers created by high-energy particles interacting with the Earth atmosphere can be detected using imaging atmospheric Cherenkov telescopes (IACTs). The IACT images can be analyzed to distinguish between the events caused by…

Instrumentation and Methods for Astrophysics · Physics 2022-09-21 Stanislav Polyakov , Andrey Demichev , Alexander Kryukov , Evgeny Postnikov

A new method of reconstructing images of gamma-ray telescopes applied to the LST-1 of CTAO

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of…

High Energy Astrophysical Phenomena · Physics 2024-11-27 CTA-LST Project , : , K. Abe , S. Abe , A. Abhishek , F. Acero , A. Aguasca-Cabot , I. Agudo , C. Alispach , N. Alvarez Crespo , D. Ambrosino , L. A. Antonelli , C. Aramo , A. Arbet-Engels , C. Arcaro , K. Asano , P. Aubert , A. Baktash , M. Balbo , A. Bamba , A. Baquero Larriva , U. Barres de Almeida , J. A. Barrio , L. Barrios Jiménez , I. Batkovic , J. Baxter , J. Becerra González , E. Bernardini , J. Bernete Medrano , A. Berti , I. Bezshyiko , P. Bhattacharjee , C. Bigongiari , E. Bissaldi , O. Blanch , G. Bonnoli , P. Bordas , G. Borkowski , G. Brunelli , A. Bulgarelli , I. Burelli , L. Burmistrov , M. Buscemi , M. Cardillo , S. Caroff , A. Carosi , M. S. Carrasco , F. Cassol , N. Castrejón , D. Cauz , D. Cerasole , G. Ceribella , Y. Chai , K. Cheng , A. Chiavassa , M. Chikawa , G. Chon , L. Chytka , G. M. Cicciari , A. Cifuentes , J. L. Contreras , J. Cortina , H. Costantini , P. Da Vela , M. Dalchenko , F. Dazzi , A. De Angelis , M. de Bony de Lavergne , B. De Lotto , R. de Menezes , R. Del Burgo , L. Del Peral , C. Delgado , J. Delgado Mengual , D. della Volpe , M. Dellaiera , A. Di Piano , F. Di Pierro , R. Di Tria , L. Di Venere , C. Díaz , R. M. Dominik , D. Dominis Prester , A. Donini , D. Dorner , M. Doro , L. Eisenberger , D. Elsässer , G. Emery , J. Escudero , V. Fallah Ramazani , F. Ferrarotto , A. Fiasson , L. Foffano , L. Freixas Coromina , S. Fröse , Y. Fukazawa , R. Garcia López , C. Gasbarra , D. Gasparrini , D. Geyer , J. Giesbrecht Paiva , N. Giglietto , F. Giordano , P. Gliwny , N. Godinovic , R. Grau , D. Green , J. Green , S. Gunji , P. Günther , J. Hackfeld , D. Hadasch , A. Hahn , T. Hassan , K. Hayashi , L. Heckmann , M. Heller , J. Herrera Llorente , K. Hirotani , D. Hoffmann , D. Horns , J. Houles , M. Hrabovsky , D. Hrupec , D. Hui , M. Iarlori , R. Imazawa , T. Inada , Y. Inome , S. Inoue , K. Ioka , M. Iori , A. Iuliano , I. Jimenez Martinez , J. Jimenez Quiles , J. Jurysek , M. Kagaya , O. Kalashev , V. Karas , H. Katagiri , J. Kataoka , D. Kerszberg , Y. Kobayashi , K. Kohri , A. Kong , H. Kubo , J. Kushida , M. Lainez , G. Lamanna , A. Lamastra , L. Lemoigne , M. Linhoff , F. Longo , R. López-Coto , A. López-Oramas , S. Loporchio , A. Lorini , J. Lozano Bahilo , H. Luciani , P. L. Luque-Escamilla , P. Majumdar , M. Makariev , M. Mallamaci , D. Mandat , M. Manganaro , G. Manicò , K. Mannheim , S. Marchesi , M. Mariotti , P. Marquez , G. Marsella , J. Martí , O. Martinez , G. Martínez , M. Martínez , A. Mas-Aguilar , G. Maurin , D. Mazin , J. Méndez-Gallego , E. Mestre Guillen , S. Micanovic , D. Miceli , T. Miener , J. M. Miranda , R. Mirzoyan , T. Mizuno , M. Molero Gonzalez , E. Molina , T. Montaruli , A. Moralejo , D. Morcuende , A. Morselli , V. Moya , H. Muraishi , S. Nagataki , T. Nakamori , A. Neronov , L. Nickel , M. Nievas Rosillo , L. Nikolic , K. Nishijima , K. Noda , D. Nosek , V. Novotny , S. Nozaki , M. Ohishi , Y. Ohtani , T. Oka , A. Okumura , R. Orito , J. Otero-Santos , P. Ottanelli , E. Owen , M. Palatiello , D. Paneque , F. R. Pantaleo , R. Paoletti , J. M. Paredes , M. Pech , M. Pecimotika , M. Peresano , F. Pfeifle , E. Pietropaolo , M. Pihet , G. Pirola , C. Plard , F. Podobnik , E. Pons , E. Prandini , C. Priyadarshi , M. Prouza , S. Rainò , R. Rando , W. Rhode , M. Ribó , C. Righi , V. Rizi , G. Rodriguez Fernandez , M. D. Rodríguez Frías , A. Ruina , E. Ruiz-Velasco , T. Saito , S. Sakurai , D. A. Sanchez , H. Sano , T. Šarić , Y. Sato , F. G. Saturni , V. Savchenko , F. Schiavone , B. Schleicher , F. Schmuckermaier , J. L. Schubert , F. Schussler , T. Schweizer , M. Seglar Arroyo , T. Siegert , J. Sitarek , V. Sliusar , J. Strišković , M. Strzys , Y. Suda , H. Tajima , H. Takahashi , M. Takahashi , J. Takata , R. Takeishi , P. H. T. Tam , S. J. Tanaka , D. Tateishi , T. Tavernier , P. Temnikov , Y. Terada , K. Terauchi , T. Terzic , M. Teshima , M. Tluczykont , F. Tokanai , D. F. Torres , P. Travnicek , A. Tutone , M. Vacula , P. Vallania , J. van Scherpenberg , M. Vázquez Acosta , S. Ventura , G. Verna , I. Viale , A. Vigliano , C. F. Vigorito , E. Visentin , V. Vitale , V. Voitsekhovskyi , G. Voutsinas , I. Vovk , T. Vuillaume , R. Walter , L. Wan , M. Will , J. Wójtowicz , T. Yamamoto , R. Yamazaki , P. K. H. Yeung , T. Yoshida , T. Yoshikoshi , W. Zhang , N. Zywucka

Reconstruction of stereoscopic CTA events using deep learning with CTLearn

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…

Instrumentation and Methods for Astrophysics · Physics 2021-09-14 Tjark Miener , Daniel Nieto , Aryeh Brill , Samuel Spencer , Jose Luis Contreras

Exploring deep learning as an event classification method for the Cherenkov Telescope Array

Telescopes based on the imaging atmospheric Cherenkov technique (IACTs) detect images of the atmospheric showers generated by gamma rays and cosmic rays as they are absorbed by the atmosphere. The much more frequent cosmic-ray events form…

Instrumentation and Methods for Astrophysics · Physics 2019-08-14 D. Nieto , A. Brill , B. Kim , T. B. Humensky

Deep-learning-driven event reconstruction applied to simulated data from a single Large-Sized Telescope of CTA

When very-high-energy gamma rays interact high in the Earth's atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into…

Instrumentation and Methods for Astrophysics · Physics 2021-09-30 Pietro Grespan , Mikael Jacquemont , Rubèn López-Coto , Tjark Miener , Daniel Nieto-Castaño , Thomas Vuillaume

Deep Learning-Based Stereoscopic Event Reconstruction for CTAO using CTLearn

The Cherenkov Telescope Array Observatory (CTAO), a next-generation ground-based gamma-ray observatory, will be composed of two arrays of multiple imaging atmospheric Cherenkov telescopes (IACTs) located in both the Northern and Southern…

High Energy Astrophysical Phenomena · Physics 2025-09-19 T. Miener , I. Viale , B. Lacave , A. Cerviño

The major upgrade of the MAGIC telescopes, Part I: The hardware improvements and the commissioning of the system

The MAGIC telescopes are two Imaging Atmospheric Cherenkov Telescopes (IACTs) located on the Canary island of La Palma. The telescopes are designed to measure Cherenkov light from air showers initiated by gamma rays in the energy regime…

Instrumentation and Methods for Astrophysics · Physics 2015-05-01 MAGIC Collaboration , J. Aleksic , S. Ansoldi , L. A. Antonelli , P. Antoranz , A. Babic , P. Bangale , M. Barcelo , J. A. Barrio , J. Becerra Gonzalez , W. Bednarek , E. Bernardini , B. Biasuzzi , A. Biland , M. Bitossi , O. Blanch , S. Bonnefoy , G. Bonnoli , F. Borracci , T. Bretz , E. Carmona , A. Carosi , R. Cecchi , P. Colin , E. Colombo , J. L. Contreras , D. Corti , J. Cortina , S. Covino , P. Da Vela , F. Dazzi , A. De Angelis , G. De Caneva , B. De Lotto , E. de Ona Wilhelmi , C. Delgado Mendez , A. Dettlaff , D. Dominis Prester , D. Dorner , M. Doro , S. Einecke , D. Eisenacher , D. Elsaesser , D. Fidalgo , D. Fink , M. V. Fonseca , L. Font , K. Frantzen , C. Fruck , D. Galindo , R. J. Garcia Lopez , M. Garczarczyk , D. Garrido Terrats , M. Gaug , G. Giavitto , N. Godinovic , A. Gonzalez Munoz , S. R. Gozzini , W. Haberer , D. Hadasch , Y. Hanabata , M. Hayashida , J. Herrera , D. Hildebrand , J. Hose , D. Hrupec , W. Idec , J. M. Illa , V. Kadenius , H. Kellermann , M. L. Knoetig , K. Kodani , Y. Konno , J. Krause , H. Kubo , J. Kushida , A. La Barbera , D. Lelas , J. L. Lemus , N. Lewandowska , E. Lindfors , S. Lombardi , F. Longo , M. Lopez , R. Lopez-Coto , A. Lopez-Oramas , A. Lorca , E. Lorenz , I. Lozano , M. Makariev , K. Mallot , G. Maneva , N. Mankuzhiyil , K. Mannheim , L. Maraschi , B. Marcote , M. Mariotti , M. Martinez , D. Mazin , U. Menzel , J. M. Miranda , R. Mirzoyan , A. Moralejo , P. Munar-Adrover , D. Nakajima , M. Negrello , V. Neustroev , A. Niedzwiecki , K. Nilsson , K. Nishijima , K. Noda , R. Orito , A. Overkemping , S. Paiano , M. Palatiello , D. Paneque , R. Paoletti , J. M. Paredes , X. Paredes-Fortuny , M. Persic , J. Poutanen , P. G. Prada Moroni , E. Prandini , I. Puljak , R. Reinthal , W. Rhode , M. Ribo , J. Rico , J. Rodriguez Garcia , S. Rugamer , T. Saito , K. Saito , K. Satalecka , V. Scalzotto , V. Scapin , C. Schultz , J. Schlammer , S. Schmidl , T. Schweizer , A. Sillanpaa , J. Sitarek , I. Snidaric , D. Sobczynska , F. Spanier , A. Stamerra , T. Steinbring , J. Storz , M. Strzys , L. Takalo , H. Takami , F. Tavecchio , L. A. Tejedor , P. Temnikov , T. Terzic , D. Tescaro , M. Teshima , J. Thaele , O. Tibolla , D. F. Torres , T. Toyama , A. Treves , P. Vogler , H. Wetteskind , M. Will , R. Zanin

CTLearn: Deep Learning for Gamma-ray Astronomy

CTLearn is a new Python package under development that uses the deep learning technique to analyze data from imaging atmospheric Cherenkov telescope (IACT) arrays. IACTs use the Cherenkov light emitted from air showers, initiated by…

Instrumentation and Methods for Astrophysics · Physics 2019-12-23 D. Nieto , A. Brill , Q. Feng , T. B. Humensky , B. Kim , T. Miener , R. Mukherjee , J. Sevilla

A method to correct IACT data for atmospheric absorption due to the Saharan Air Layer

Using the atmosphere as a detector volume, Imaging Air Cherenkov Telescopes (IACTs) depend highly on the properties and the condition of the air mass above the telescope. On the Canary Island of La Palma, where the Major Atmospheric…

Astrophysics · Physics 2009-11-13 Daniela Dorner , Kari Nilsson , Thomas Bretz

Improvements to monoscopic analysis for imaging atmospheric Cherenkov telescopes: Application to H.E.S.S

Imaging atmospheric Cherenkov telescopes (IACTs) detect gamma rays by measuring the Cherenkov light emitted by secondary particles in the air shower when the gamma rays hit the atmosphere. At low energies, the limited amount of Cherenkov…

Instrumentation and Methods for Astrophysics · Physics 2025-02-13 Tim Unbehaun , Rodrigo Guedes Lang , Anita Deka Baruah , Prajath Bedur Ramesh , Jelena Celic , Lars Mohrmann , Simon Steinmassl , Laura Olivera-Nieto , Jim Hinton , Stefan Funk

Application of Deep Learning methods to analysis of Imaging Atmospheric Cherenkov Telescopes data

Ground based gamma-ray observations with Imaging Atmospheric Cherenkov Telescopes (IACTs) play a significant role in the discovery of very high energy (E > 100 GeV) gamma-ray emitters. The analysis of IACT data demands a highly efficient…

Instrumentation and Methods for Astrophysics · Physics 2018-11-07 Idan Shilon , Manuel Kraus , Matthias Büchele , Kathrin Egberts , Tobias Fischer , Tim Lukas Holch , Thomas Lohse , Ullrich Schwanke , Constantin Steppa , Stefan Funk

Energy Reconstruction in Analysis of Cherenkov Telescopes Images in TAIGA Experiment Using Deep Learning Methods

Imaging Atmospheric Cherenkov Telescopes (IACT) of TAIGA astrophysical complex allow to observe high energy gamma radiation helping to study many astrophysical objects and processes. TAIGA-IACT enables us to select gamma quanta from the…

Instrumentation and Methods for Astrophysics · Physics 2022-11-17 E. O. Gres , A. P. Kryukov

Analysis of the Cherenkov Telescope Array first Large-Sized Telescope real data using convolutional neural networks

The Cherenkov Telescope Array (CTA) is the future ground-based gamma-ray observatory and will be composed of two arrays of imaging atmospheric Cherenkov telescopes (IACTs) located in the Northern and Southern hemispheres respectively. The…

Instrumentation and Methods for Astrophysics · Physics 2021-08-10 Thomas Vuillaume , Mikaël Jacquemont , Mathieu de Bony de Lavergne , David A. Sanchez , Vincent Poireau , Gilles Maurin , Alexandre Benoit , Patrick Lambert , Giovanni Lamanna , CTA-LST Project

Deep learning with photosensor timing information as a background rejection method for the Cherenkov Telescope Array

New deep learning techniques present promising new analysis methods for Imaging Atmospheric Cherenkov Telescopes (IACTs) such as the upcoming Cherenkov Telescope Array (CTA). In particular, the use of Convolutional Neural Networks (CNNs)…

Instrumentation and Methods for Astrophysics · Physics 2021-03-31 Samuel Spencer , Thomas Armstrong , Jason Watson , Salvatore Mangano , Yves Renier , Garret Cotter

The analysis of VERITAS muon images using convolutional neural networks

Imaging atmospheric Cherenkov telescopes (IACTs) are sensitive to rare gamma-ray photons, buried in the background of charged cosmic-ray (CR) particles, the flux of which is several orders of magnitude greater. The ability to separate gamma…

Instrumentation and Methods for Astrophysics · Physics 2017-06-14 Qi Feng , Tony T. Y. Lin

Observation of Galactic Sources of Very High Energy Gamma-Rays with the MAGIC Telescope

The MAGIC telescope with its 17m diameter mirror is today the largest operating single-dish Imaging Air Cherenkov Telescope (IACT). It is located on the Canary Island La Palma, at an altitude of 2200m above sea level, as part of the Roque…

Astrophysics · Physics 2019-08-13 H. Bartko