← Back to cohort
Low Energy Event Reconstruction in IceCube DeepCore
M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, M. Ahrens, Jean-Marco Alameddine, A. A. Alves, N. M. Amin, K. Andeen, T. Anderson, G. Anton, C. Argüelles, Yosuke Ashida, Spencer Axani, X. Bai, Aswathi Balagopal, S. W. Barwick, Benjamin Bastian, Vedant Basu, S. Baur, R. Curtis Bay, J. J. Beatty, K. Becker, J. Becker Tjus, Jakob Beise, Chiara Bellenghi, S. Benda, S. BenZvi, D. Berley, E. Bernardini, D. Besson, G. Binder, D. Bindig, E. Blaufuss, Summer Blot, Matthias Boddenberg, Federico Bontempo, Julia Book, Jürgen Borowka, S. Böser, O. Botner, J. Böttcher, Etienne Bourbeau, Federica Bradascio, J. Braun, Bennett Brinson, S. Bron, Jannes Brostean-Kaiser, Ryan T. Burley, Raffaela Busse, Michael Campana, Erin Carnie-Bronca, C. Chen, Z. Chen, D. Chirkin, K. Choi, Brian Clark, K. Clark, Lew Classen, Alan Coleman, G. H. Collin, J. M. Conrad, Paul Coppin, Pablo Correa, D. F. Cowen, R. Cross, Christian Dappen, Pranav Dave, C. De Clercq, James DeLaunay, H.-P. Dembinski, Kunal Deoskar, Abhishek Desai, P. Desiati, K. D. de Vries, G. de Wasseige, M. de With, T. DeYoung, A. Diaz, J. C. Díaz–Vélez, Markus Dittmer, Hrvoje Dujmović, M. Dunkman, M. A. DuVernois, Thomas Ehrhardt, P. Eller, R. Engel, Hannah Erpenbeck, John Evans, P. A. Evenson, Kwok Lung Fan, A. R. Fazely, Anatoli Fedynitch, Nora Feigl, Sebastian Fiedlschuster, Aaron Fienberg, C. Finley, D. B. Fox, A. Franckowiak, Edward Friedman, Alexander Fritz, Philipp Fürst, T. K. Gaisser, J. S. Gallagher, Erik Ganster, Alfonso Garcia, L. Gerhardt, Christian Gläser, Theo Glauch, T. Glüsenkamp, N. Goehlke, J. G. González, Sreetama Goswami, Darren Grant, T. Grégoire, Spencer Griswold, Christoph Günther, Pascal Gutjahr, Christian Haack, A. Hallgren, R. Halliday, L. Halve, F. Halzen, M. Ha Minh, K. Hanson, John Hardin, Alexander Harnisch, A. Haungs, D. Hebecker, K. Helbing, Felix Henningsen, Emma C. Hettinger, S. Hickford, J. Hignight, Colton Hill, G. C. Hill, K. D. Hoffman, R. Hoffmann, K. Hoshina, Wenjie Hou, F. Huang, M. E. Huber, Thomas Huber, K. Hultqvist, Mirco Hünnefeld, Raamis Hussain, Karolin Hymon, S. In, N. Iovine, A. Ishihara, M. Jansson, G. S. Japaridze, Minjin Jeong, Miaochen Jin, B. J. P. Jones, Donghwa Kang, Woosik Kang, X. Kang, David Kappesser, Leonora Kardum, T. Karg, Martina Karl, A. Karle, U. Katz, M. Kauer, Moritz Kellermann, Ali Kheirandish, Ken'ichi Kin, T. Kintscher, J. Kiryluk, Alina Kochocki, Ramesh Koirala, H. Kolanoski, Tomas Kontrimas, L. Köpke, Claudio Kopper, S. Kopper, D. J. Koskinen, Paras Koundal, Michael Kovacevich, M. Kowalski, Tetiana Kozynets, Emmett Krupczak, Emma Kun, N. Kurahashi, N. N. Lad, Cristina Lagunas Gualda, J. L. Lanfranchi, M. J. Larson, Frederik Hermann Lauber, J. P. Lazar, J. W. Lee, Agnieszka Leszczyńska, Yulong Li, Massimiliano Lincetto, Q. R. Liu, Maria Liubarska, Elisa Lohfink, L. Lu, Francesco Lucarelli, Andrew Ludwig, William Luszczak, J. Madsen, K. B. M. Mahn, Yuya Makino, Sarah Mancina, Ivan Martínez-Soler, R. Maruyama, S. McCarthy, Thomas McElroy, Frank McNally, J. V. Mead, K. Meagher, Andrés Medina, Maximilian Meier, S. Meighen-Berger, Jessie Micallef, D. Mockler, T. Montaruli, R. W. Moore, R. Morse, Marjon Moulai, Tridib Mukherjee, Ryo Nagai, Uwe Naumann, Jannis Necker, Hans Niederhausen, M. U. Nisa, Sarah Nowicki, A. Obertacke Pollmann, M. Oehler, Bob Oeyen, A. Olivas, Erin O’Sullivan, Hershal Pandya, D. V. Pankova, N. Park, Grant Parker, Ek Narayan Paudel, L. Paul, Lilly Peters, Josh Peterson, Saskia Philippen, Sarah Pieper, A. Pizzuto, M. Plum, Yuriy Popovych, Alessio Porcelli, Maria Prado Rodriguez, B. Pries, G. T. Przybylski, Christoph Raab, John Rack-Helleis, Amirreza Raissi, M. Rameez, K. Rawlins, I. C. Rea, Zoë Rechav, Abdul Rehman, Patrick Reichherzer, R. Reimann, Giovanni Renzi, E. Resconi, W. Rhode, M. Richman, Benedikt Riedel, E. J. Roberts, S. Robertson, Gerrit Roellinghoff, Martin Rongen, C. Rott, T. Ruhe, D. Ryckbosch, Devyn Rysewyk Cantu, I. Safa, Julian Saffer, P. Sampathkumar, S. E. Sanchez Herrera, Alexander Sandrock, M. Santander, S. Sarkar, K. Satalecka, Merlin Schaufel, H. Schieler, S. Schindler, T. Schmidt, A. Schneider, Judith Schneider, Frank Schröder, L. Schumacher, Georg Schwefer, S. Sclafani, D. Seckel, S. Seunarine, Ankur Sharma, S. Shefali, Nobuhiro Shimizu, M. Silva, Barbara Skrzypek, Ben Smithers, R. Snihur, Jan Soedingrekso, Dennis Soldin, Christian Spannfellner, G. M. Spiczak, Christian Spiering, M. Stamatikos, Todor Stanev, J. Stettner, T. Stezelberger, T. Stürwald, Thomas Stuttard, G. W. Sullivan, I. Taboada, S. Ter–Antonyan, Jessie Thwaites, S. Tilav, Franziska Tischbein, Kirsten Tollefson, Christoph Tönnis, S. Toscano, D. Tosi, M. Tselengidou, C. F. Tung, A. Turcati, Roxanne Turcotte, Colin Turley, Jean Pierre Twagirayezu, B. Ty, Martin Unland Elorrieta, Nora Valtonen-Mattila, J. Vandenbroucke, N. van Eijndhoven, D. Vannerom, J. Veitch-Michaelis, Stef Verpoest, C. Walck, W. Wang, Timothyblake Watson, Ch. Weaver, Philip Weigel, A. Weindl, Matthew J. Weiss, Jan Weldert, C. Wendt, Johannes Werthebach, Mark Weyrauch, C. H. Wiebusch, N. Willey, D. R. Williams, Martin Wolf, Gerrit Wrede, Johan Wilfried Wulff, Xiaolin Xu, Emre Burak Yildizci, S. Yoshida, Shaoqing Yu, Tianlu Yuan, Zelong Zhang, Pavel Zhelnin
Bibliographic record
VenuearXiv (Cornell University) · 2022
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsnot available
FundersOffice of Experimental Program to Stimulate Competitive ResearchJapan Society for the Promotion of ScienceDeutsches Elektronen-SynchrotronNatural Sciences and Engineering Research Council of CanadaOffice of Polar ProgramsCollege of Engineering, Michigan State UniversityHelmholtz Alliance for Astroparticle PhysicsInstitute for Global Prominent Research, Chiba UniversityRWTH Aachen UniversityChiba UniversityKnut och Alice Wallenbergs StiftelseVillum FondenNational Research Foundation of KoreaFonds Wetenschappelijk OnderzoekMarsden FundBundesministerium für Bildung und ForschungSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science FoundationBelgian Federal Science Policy OfficeDeutsche ForschungsgemeinschaftMichigan State UniversityNational Research FoundationWestern Canada Research GridFonds De La Recherche Scientifique - FNRSPolarforskningssekretariatetUniversity of OxfordCompute CanadaMarquette UniversityUniversity of Wisconsin-MadisonU.S. Department of EnergyVetenskapsrådet
KeywordsEvent reconstructionEvent (particle physics)Energy (signal processing)DetectorRange (aeronautics)Iterative reconstructionComputer scienceNeutrinoReconstruction algorithmAlgorithmPhysicsArtificial intelligenceOpticsParticle physicsAerospace engineeringEngineeringAstrophysics
Abstract
The reconstruction of event-level information, such as the direction or energy of a neutrino interacting in IceCube DeepCore, is a crucial ingredient to many physics analyses. Algorithms to extract this high level information from the detector's raw data have been successfully developed and used for high energy events. In this work, we address unique challenges associated with the reconstruction of lower energy events in the range of a few to hundreds of GeV and present two separate, state-of-the-art algorithms. One algorithm focuses on the fast directional reconstruction of events based on unscattered light. The second algorithm is a likelihood-based multipurpose reconstruction offering superior resolutions, at the expense of larger computational cost.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.020
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.022
GPT teacher head0.162
Teacher spread0.140 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations3
Published2022
Admission routes1
Has abstractyes