Related papers: Enhancements to the IceCube Extremely High Energy …

Extreme High-Energy Neutrinos: IceCube vs. KM3NeT

We review the state of the art in the detection of extreme high-energy neutrinos, focusing on the IceCube and KM3NeT neutrino telescopes. IceCube, operating deep in Antarctic ice, and KM3NeT, a new array in the Mediterranean Sea, employ…

High Energy Astrophysical Phenomena · Physics 2025-09-17 Lu Lu , Tianlu Yuan

Graph Neural Networks for Low-Energy Event Classification & Reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and…

High Energy Physics - Experiment · Physics 2022-11-16 R. Abbasi , M. Ackermann , J. Adams , N. Aggarwal , J. A. Aguilar , M. Ahlers , M. Ahrens , J. M. Alameddine , A. A. Alves , N. M. Amin , K. Andeen , T. Anderson , G. Anton , C. Argüelles , Y. Ashida , S. Athanasiadou , S. Axani , X. Bai , A. Balagopal V. , M. Baricevic , S. W. Barwick , V. Basu , R. Bay , J. J. Beatty , K. -H. Becker , J. Becker Tjus , J. Beise , C. Bellenghi , S. Benda , S. BenZvi , D. Berley , E. Bernardini , D. Z. Besson , G. Binder , D. Bindig , E. Blaufuss , S. Blot , F. Bontempo , J. Y. Book , J. Borowka , C. Boscolo Meneguolo , S. Böser , O. Botner , J. Böttcher , E. Bourbeau , J. Braun , B. Brinson , J. Brostean-Kaiser , R. T. Burley , R. S. Busse , M. A. Campana , E. G. Carnie-Bronca , C. Chen , Z. Chen , D. Chirkin , K. Choi , B. A. Clark , L. Classen , A. Coleman , G. H. Collin , A. Connolly , J. M. Conrad , P. Coppin , P. Correa , S. Countryman , D. F. Cowen , R. Cross , C. Dappen , P. Dave , C. De Clercq , J. J. DeLaunay , D. Delgado López , H. Dembinski , K. Deoskar , A. Desai , P. Desiati , K. D. de Vries , G. de Wasseige , T. DeYoung , A. Diaz , J. C. Díaz-Vélez , M. Dittmer , H. Dujmovic , M. A. DuVernois , T. Ehrhardt , P. Eller , R. Engel , H. Erpenbeck , J. Evans , P. A. Evenson , K. L. Fan , A. R. Fazely , A. Fedynitch , N. Feigl , S. Fiedlschuster , A. T. Fienberg , C. Finley , L. Fischer , D. Fox , A. Franckowiak , E. Friedman , A. Fritz , P. Fürst , T. K. Gaisser , J. Gallagher , E. Ganster , A. Garcia , S. Garrappa , L. Gerhardt , A. Ghadimi , C. Glaser , T. Glauch , T. Glüsenkamp , N. Goehlke , J. G. Gonzalez , S. Goswami , D. Grant , S. J. Gray , T. Grégoire , S. Griswold , C. Günther , P. Gutjahr , C. Haack , A. Hallgren , R. Halliday , L. Halve , F. Halzen , H. Hamdaoui , M. Ha Minh , K. Hanson , J. Hardin , A. A. Harnisch , P. Hatch , A. Haungs , K. Helbing , J. Hellrung , F. Henningsen , L. Heuermann , S. Hickford , C. Hill , G. C. Hill , K. D. Hoffman , K. Hoshina , W. Hou , T. Huber , K. Hultqvist , M. Hünnefeld , R. Hussain , K. Hymon , S. In , N. Iovine , A. Ishihara , M. Jansson , G. S. Japaridze , M. Jeong , M. Jin , B. J. P. Jones , D. Kang , W. Kang , X. Kang , A. Kappes , D. Kappesser , L. Kardum , T. Karg , M. Karl , A. Karle , U. Katz , M. Kauer , J. L. Kelley , A. Kheirandish , K. Kin , J. Kiryluk , S. R. Klein , A. Kochocki , R. Koirala , H. Kolanoski , T. Kontrimas , L. Köpke , C. Kopper , D. J. Koskinen , P. Koundal , M. Kovacevich , M. Kowalski , T. Kozynets , E. Krupczak , E. Kun , N. Kurahashi , N. Lad , C. Lagunas Gualda , M. J. Larson , F. Lauber , J. P. Lazar , J. W. Lee , K. Leonard , A. Leszczyńska , M. Lincetto , Q. R. Liu , M. Liubarska , E. Lohfink , C. Love , C. J. Lozano Mariscal , L. Lu , F. Lucarelli , A. Ludwig , W. Luszczak , Y. Lyu , W. Y. Ma , J. Madsen , K. B. M. Mahn , Y. Makino , S. Mancina , W. Marie Sainte , I. C. Mariş , S. Marka , Z. Marka , M. Marsee , I. Martinez-Soler , R. Maruyama , T. McElroy , F. McNally , J. V. Mead , K. Meagher , S. Mechbal , A. Medina , M. Meier , S. Meighen-Berger , Y. Merckx , J. Micallef , D. Mockler , T. Montaruli , R. W. Moore , R. Morse , M. Moulai , T. Mukherjee , R. Naab , R. Nagai , U. Naumann , A. Nayerhoda , J. Necker , M. Neumann , H. Niederhausen , M. U. Nisa , S. C. Nowicki , A. Obertacke Pollmann , M. Oehler , B. Oeyen , A. Olivas , R. Orsoe , J. Osborn , E. O'Sullivan , H. Pandya , D. V. Pankova , N. Park , G. K. Parker , E. N. Paudel , L. Paul , C. Pérez de los Heros , L. Peters , T. C. Petersen , J. Peterson , S. Philippen , S. Pieper , A. Pizzuto , M. Plum , Y. Popovych , A. Porcelli , M. Prado Rodriguez , B. Pries , R. Procter-Murphy , G. T. Przybylski , C. Raab , J. Rack-Helleis , M. Rameez , K. Rawlins , Z. Rechav , A. Rehman , P. Reichherzer , G. Renzi , E. Resconi , S. Reusch , W. Rhode , M. Richman , B. Riedel , E. J. Roberts , S. Robertson , S. Rodan , G. Roellinghoff , M. Rongen , C. Rott , T. Ruhe , L. Ruohan , D. Ryckbosch , D. Rysewyk Cantu , I. Safa , J. Saffer , D. Salazar-Gallegos , P. Sampathkumar , S. E. Sanchez Herrera , A. Sandrock , M. Santander , S. Sarkar , S. Sarkar , M. Schaufel , H. Schieler , S. Schindler , B. Schlueter , T. Schmidt , J. Schneider , F. G. Schröder , L. Schumacher , G. Schwefer , S. Sclafani , D. Seckel , S. Seunarine , A. Sharma , S. Shefali , N. Shimizu , M. Silva , B. Skrzypek , B. Smithers , R. Snihur , J. Soedingrekso , A. Søgaard , D. Soldin , C. Spannfellner , G. M. Spiczak , C. Spiering , M. Stamatikos , T. Stanev , R. Stein , T. Stezelberger , T. Stürwald , T. Stuttard , G. W. Sullivan , I. Taboada , S. Ter-Antonyan , W. G. Thompson , J. Thwaites , S. Tilav , K. Tollefson , C. Tönnis , S. Toscano , D. Tosi , A. Trettin , C. F. Tung , R. Turcotte , J. P. Twagirayezu , B. Ty , M. A. Unland Elorrieta , K. Upshaw , N. Valtonen-Mattila , J. Vandenbroucke , N. van Eijndhoven , D. Vannerom , J. van Santen , J. Vara , J. Veitch-Michaelis , S. Verpoest , D. Veske , C. Walck , W. Wang , T. B. Watson , C. Weaver , P. Weigel , A. Weindl , J. Weldert , C. Wendt , J. Werthebach , M. Weyrauch , N. Whitehorn , C. H. Wiebusch , N. Willey , D. R. Williams , M. Wolf , G. Wrede , J. Wulff , X. W. Xu , J. P. Yanez , E. Yildizci , S. Yoshida , S. Yu , T. Yuan , Z. Zhang , P. Zhelnin

Deep Learning Based Event Reconstruction for the IceCube-Gen2 Radio Detector

The planned in-ice radio array of IceCube-Gen2 at the South Pole will provide unprecedented sensitivity to ultra-high-energy (UHE) neutrinos in the EeV range. The ability of the detector to measure the neutrino's energy and direction is of…

High Energy Astrophysical Phenomena · Physics 2023-08-02 Nils Heyer , Christian Glaser , Thorsten Glüsenkamp

Characterization of the PeV astrophysical neutrino energy spectrum with IceCube using down-going tracks

The IceCube Neutrino Observatory has observed a diffuse flux of astrophysical neutrinos with energies from TeV to a few PeV. Recent IceCube analyses have limited sensitivity to PeV neutrinos because upward-going neutrino fluxes are…

High Energy Astrophysical Phenomena · Physics 2021-08-02 Yang Lyu

Reconstruction of Neutrino Events in IceCube using Graph Neural Networks

The IceCube Neutrino Observatory is a cubic-kilometer scale neutrino detector embedded in the Antarctic ice of the South Pole. In the near future, the detector will be augmented by extensions, such as the IceCube Upgrade and the planned…

Instrumentation and Methods for Astrophysics · Physics 2021-07-27 Martin Ha Minh

Development of a Machine Learning Based Analysis Chain for the Measurement of Atmospheric Muon Spectra with IceCube

High-energy muons from air shower events detected in IceCube are selected using state of the art machine learning algorithms. Attributes to distinguish a HE-muon event from the background of low-energy muon bundles are selected using the…

Instrumentation and Methods for Astrophysics · Physics 2017-01-17 Tomasz Fuchs

Graph Neural Networks for IceCube Signal Classification

Tasks involving the analysis of geometric (graph- and manifold-structured) data have recently gained prominence in the machine learning community, giving birth to a rapidly developing field of geometric deep learning. In this work, we…

Machine Learning · Computer Science 2018-09-18 Nicholas Choma , Federico Monti , Lisa Gerhardt , Tomasz Palczewski , Zahra Ronaghi , Prabhat , Wahid Bhimji , Michael M. Bronstein , Spencer R. Klein , Joan Bruna

Reconstructing Neutrino Energy using CNNs for GeV Scale IceCube Events

Measurements of neutrinos at and below 10 GeV provide unique constraints of neutrino oscillation parameters as well as probes of potential Non-Standard Interactions (NSI). The IceCube Neutrino Observatory's DeepCore array is designed to…

High Energy Astrophysical Phenomena · Physics 2021-07-27 Jessie Micallef

Advanced Northern Tracks Selection using a Graph Convolutional Neural Network for the IceCube Neutrino Observatory

The IceCube Neutrino Observatory is a cubic-kilometer detector located in the Antarctic ice at the geographic South Pole. It reads out over 5,000 photomultiplier tubes (PMTs) to detect Cherenkov light produced by secondary particles,…

High Energy Astrophysical Phenomena · Physics 2025-07-11 Philipp Soldin , Shuyang Deng , Lasse Düser , Philipp Fürst

Search for Extremely High Energy Neutrinos with IceCube

Extremely high energy (EHE) neutrinos (with energies above $10^7$ GeV) are produced in interactions of the highest energy cosmic rays. A primary contribution to the EHE neutrino flux is expected from so-called cosmogenic neutrinos produced…

High Energy Astrophysical Phenomena · Physics 2023-08-16 Maximilian Meier , Brian Clark

Deep-learning-based reconstruction of the neutrino direction and energy for in-ice radio detectors

Ultra-high-energy (UHE) neutrinos ($>10^{16}$ eV) can be measured cost-effectively using in-ice radio detection, which has been explored successfully in pilot arrays. A large radio detector is currently being constructed in Greenland with…

Instrumentation and Methods for Astrophysics · Physics 2022-10-26 C. Glaser , S. McAleer , S. Stjärnholm , P. Baldi , S. W. Barwick

Fast Low Energy Reconstruction using Convolutional Neural Networks

IceCube is a Cherenkov detector instrumenting over a cubic kilometer of glacial ice deep under the surface of the South Pole. The DeepCore sub-detector lowers the detection energy threshold to a few GeV, enabling the precise measurements of…

High Energy Astrophysical Phenomena · Physics 2026-02-02 IceCube Collaboration

2D Convolutional Neural Network for Event Reconstruction in IceCube DeepCore

IceCube DeepCore is an extension of the IceCube Neutrino Observatory designed to measure GeV scale atmospheric neutrino interactions for the purpose of neutrino oscillation studies. Distinguishing muon neutrinos from other flavors and…

High Energy Astrophysical Phenomena · Physics 2026-02-02 J. H. Peterson , M. Prado Rodriguez , K. Hanson

Deep learning reconstruction of neutrino direction, energy, and flavor with complete uncertainty predictions

With the IceCube-Gen2 observatory under development and RNO-G under construction, the first detection of ultra-high-energy neutrinos is on the horizon making event reconstruction a priority. Here, we present a full reconstruction of the…

Instrumentation and Methods for Astrophysics · Physics 2024-10-15 Nils Heyer , Thorsten Glüsenkamp , Christian Glaser

Using Convolutional Neural Networks to Reconstruct Energy of GeV Scale IceCube Neutrinos

The IceCube Neutrino Observatory, located under 1.4 km of Antarctic ice, instruments a cubic kilometer of ice with 5,160 optical modules that detect Cherenkov radiation originating from neutrino interactions. The more densely instrumented…

High Energy Astrophysical Phenomena · Physics 2021-10-27 Jessie Micallef

Application of Deep Neural Networks to Event Type Classification in IceCube

The IceCube Neutrino Observatory is able to measure the all-flavor neutrino flux in the energy range between 100 GeV and several PeV. Due to the different features of the neutrino interactions and the geometry of the detector, all…

Instrumentation and Methods for Astrophysics · Physics 2019-08-26 Maximilian Kronmueller , Theo Glauch

Observation and Characterization of a Cosmic Muon Neutrino Flux from the Northern Hemisphere using six years of IceCube data

The IceCube Collaboration has previously discovered a high-energy astrophysical neutrino flux using neutrino events with interaction vertices contained within the instrumented volume of the IceCube detector. We present a complementary…

High Energy Astrophysical Phenomena · Physics 2017-01-10 IceCube Collaboration , M. G. Aartsen , K. Abraham , M. Ackermann , J. Adams , J. A. Aguilar , M. Ahlers , M. Ahrens , D. Altmann , K. Andeen , T. Anderson , I. Ansseau , G. Anton , M. Archinger , C. Argüelles , J. Auffenberg , S. Axani , X. Bai , S. W. Barwick , V. Baum , R. Bay , J. J. Beatty , J. Becker Tjus , K. -H. Becker , S. BenZvi , P. Berghaus , D. Berley , E. Bernardini , A. Bernhard , D. Z. Besson , G. Binder , D. Bindig , M. Bissok , E. Blaufuss , S. Blot , C. Bohm , M. Börner , F. Bos , D. Bose , S. Böser , O. Botner , J. Braun , L. Brayeur , H. -P. Bretz , A. Burgman , T. Carver , M. Casier , E. Cheung , D. Chirkin , A. Christov , K. Clark , L. Classen , S. Coenders , G. H. Collin , J. M. Conrad , D. F. Cowen , R. Cross , M. Day , J. P. A. M. de André , C. De Clercq , E. del Pino Rosendo , H. Dembinski , S. De Ridder , P. Desiati , K. D. de Vries , G. de Wasseige , M. de With , T. DeYoung , J. C. Díaz-Vélez , V. di Lorenzo , H. Dujmovic , J. P. Dumm , M. Dunkman , B. Eberhardt , T. Ehrhardt , B. Eichmann , P. Eller , S. Euler , P. A. Evenson , S. Fahey , A. R. Fazely , J. Feintzeig , J. Felde , K. Filimonov , C. Finley , S. Flis , C. -C. Fösig , A. Franckowiak , E. Friedman , T. Fuchs , T. K. Gaisser , J. Gallagher , L. Gerhardt , K. Ghorbani , W. Giang , L. Gladstone , M. Glagla , T. Glüsenkamp , A. Goldschmidt , G. Golup , J. G. Gonzalez , D. Grant , Z. Griffith , C. Haack , A. Haj Ismail , A. Hallgren , F. Halzen , E. Hansen , B. Hansmann , T. Hansmann , K. Hanson , D. Hebecker , D. Heereman , K. Helbing , R. Hellauer , S. Hickford , J. Hignight , G. C. Hill , K. D. Hoffman , R. Hoffmann , K. Holzapfel , K. Hoshina , F. Huang , M. Huber , K. Hultqvist , S. In , A. Ishihara , E. Jacobi , G. S. Japaridze , M. Jeong , K. Jero , B. J. P. Jones , M. Jurkovic , A. Kappes , T. Karg , A. Karle , U. Katz , M. Kauer , A. Keivani , J. L. Kelley , J. Kemp , A. Kheirandish , M. Kim , T. Kintscher , J. Kiryluk , T. Kittler , S. R. Klein , G. Kohnen , R. Koirala , H. Kolanoski , R. Konietz , L. Köpke , C. Kopper , S. Kopper , D. J. Koskinen , M. Kowalski , K. Krings , M. Kroll , G. Krückl , C. Krüger , J. Kunnen , S. Kunwar , N. Kurahashi , T. Kuwabara , M. Labare , J. L. Lanfranchi , M. J. Larson , F. Lauber , D. Lennarz , M. Lesiak-Bzdak , M. Leuermann , J. Leuner , L. Lu , J. Lünemann , J. Madsen , G. Maggi , K. B. M. Mahn , S. Mancina , M. Mandelartz , R. Maruyama , K. Mase , R. Maunu , F. McNally , K. Meagher , M. Medici , M. Meier , A. Meli , T. Menne , G. Merino , T. Meures , S. Miarecki , L. Mohrmann , T. Montaruli , M. Moulai , R. Nahnhauer , U. Naumann , G. Neer , H. Niederhausen , S. C. Nowicki , D. R. Nygren , A. Obertacke Pollmann , A. Olivas , A. O'Murchadha , T. Palczewski , H. Pandya , D. V. Pankova , P. Peiffer , Ö. Penek , J. A. Pepper , C. Pérez de los Heros , D. Pieloth , E. Pinat , P. B. Price , G. T. Przybylski , M. Quinnan , C. Raab , L. Rädel , M. Rameez , K. Rawlins , R. Reimann , B. Relethford , M. Relich , E. Resconi , W. Rhode , M. Richman , B. Riedel , S. Robertson , M. Rongen , C. Rott , T. Ruhe , D. Ryckbosch , D. Rysewyk , L. Sabbatini , S. E. Sanchez Herrera , A. Sandrock , J. Sandroos , S. Sarkar , K. Satalecka , M. Schimp , P. Schlunder , T. Schmidt , S. Schoenen , S. Schöneberg , L. Schumacher , D. Seckel , S. Seunarine , D. Soldin , M. Song , G. M. Spiczak , C. Spiering , M. Stahlberg , T. Stanev , A. Stasik , A. Steuer , T. Stezelberger , R. G. Stokstad , A. Stößl , R. Ström , N. L. Strotjohann , G. W. Sullivan , M. Sutherland , H. Taavola , I. Taboada , J. Tatar , F. Tenholt , S. Ter-Antonyan , A. Terliuk , G. Tešić , S. Tilav , P. A. Toale , M. N. Tobin , S. Toscano , D. Tosi , M. Tselengidou , A. Turcati , E. Unger , M. Usner , J. Vandenbroucke , N. van Eijndhoven , S. Vanheule , M. van Rossem , J. van Santen , J. Veenkamp , M. Vehring , M. Voge , M. Vraeghe , C. Walck , A. Wallace , M. Wallraff , N. Wandkowsky , Ch. Weaver , M. J. Weiss , C. Wendt , S. Westerhoff , B. J. Whelan , S. Wickmann , K. Wiebe , C. H. Wiebusch , L. Wille , D. R. Williams , L. Wills , M. Wolf , T. R. Wood , E. Woolsey , K. Woschnagg , D. L. Xu , X. W. Xu , Y. Xu , J. P. Yanez , G. Yodh , S. Yoshida , M. Zoll

Graph Neural Networks for reconstruction and classification in KM3NeT

KM3NeT, a neutrino telescope currently under construction in the Mediterranean Sea, consists of a network of large-volume Cherenkov detectors. Its two different sites, ORCA and ARCA, are optimised for few GeV and TeV-PeV neutrino energies,…

Instrumentation and Methods for Astrophysics · Physics 2021-11-17 S. Reck , D. Guderian , G. Vermariën , A. Domi

Optical follow-up of high-energy neutrinos detected by IceCube

Three-quarters of the 1 cubic kilometer neutrino telescope IceCube is currently taking data. Current models predict high-energy neutrino emission from transient objects like supernovae (SNe) and gammaray bursts (GRBs). To increase the…

High Energy Astrophysical Phenomena · Physics 2019-08-15 A. Franckowiak , C. Akerlof , D. F. Cowen , M. Kowalski , R. Lehmann , T. Schmidt , F. Yuan

Classification of Electron and Muon Neutrino Events for the ESS$\nu$SB Near Water Cherenkov Detector using Graph Neural Networks

In the effort to obtain a precise measurement of leptonic CP-violation with the ESS$\nu$SB experiment, accurate and fast reconstruction of detector events plays a pivotal role. In this work, we examine the possibility of replacing the…

High Energy Physics - Experiment · Physics 2025-04-04 J. Aguilar , M. Anastasopoulos , D. Barčot , E. Baussan , A. K. Bhattacharyya , A. Bignami , M. Blennow , M. Bogomilov , B. Bolling , E. Bouquerel , F. Bramati , A. Branca , G. Brunetti , A. Burgman , I. Bustinduy , C. J. Carlile , J. Cederkall , T. W. Choi , S. Choubey , P. Christiansen , M. Collins , E. Cristaldo Morales , P. Cupiał , D. D'Ago , H. Danared , J. P. A. M. de André , M. Dracos , I. Efthymiopoulos , T. Ekelöf , M. Eshraqi , G. Fanourakis , A. Farricker , E. Fasoula , T. Fukuda , J. García-Marcos , N. Gazis , Th. Geralis , M. Ghosh , A. Giarnetti , G. Gokbulut , C. Hagner , L. Halić , M. Hooft , K. E. Iversen , N. Jachowicz , M. Jenssen , R. Johansson , I. Karakoulias , E. Kasimi , A. Kayis Topaksu , B. Kildetoft , B. Kliček , K. Kordas , A. Leisos , M. Lindroos , A. Longhin , C. Maiano , S. Marangoni , C. Marrelli , D. Meloni , M. Mezzetto , N. Milas , J. L. Muñoz , K. Niewczas , M. Oglakci , T. Ohlsson , M. Olvegård , M. Pari , J. Park , D. Patrzalek , G. Petkov , Ch. Petridou , P. Poussot , A. Psallidas , F. Pupilli , D. Saiang , D. Sampsonidis , A. Scanu , C. Schwab , F. Sordo , A. Sosa , G. Stavropoulos , M. Stipčević , R. Tarkeshian , F. Terranova , T. Tolba , E. Trachanas , R. Tsenov , A. Tsirigotis , S. E. Tzamarias , M. Vanderpoorten , G. Vankova-Kirilova , N. Vassilopoulos , S. Vihonen , J. Wurtz , V. Zeter , O. Zormpa