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Search for a light sterile neutrino with 7.5 years of IceCube DeepCore data
R. Abbasi, M. Ackermann, J. Adams, Sanjib Kumar Agarwalla, J. A. Aguilar, M. Ahlers, Jean-Marco Alameddine, N. M. Amin, K. Andeen, C. Argüelles, Yosuke Ashida, S. Athanasiadou, L. Ausborm, Spencer Axani, X. Bai, A. Balagopal V., M. Baricevic, S. W. Barwick, Simeon Bash, Vedant Basu, R. Bay, J. J. Beatty, J. Becker Tjus, Jakob Beise, C. Bellenghi, Charlotte Benning, S. BenZvi, D. Berley, E. Bernardini, D. Z. Besson, E. Blaufuss, Linda B. Bloom, Summer Blot, F. Bontempo, Julia Book, Caterina Boscolo Meneguolo, S. Böser, O. Botner, J. Böttcher, E. Bourbeau, J. Braun, Bennett Brinson, J. Brostean-Kaiser, Livia Brusa, Ryan T. Burley, Delaney Butterfield, Michael Campana, I. Caracas, K. Carloni, J. Graciá‐Carpio, S. Chattopadhyay, Thien Nhan Chau, Z. Chen, D. Chirkin, S. Choi, Brian Clark, Alan Coleman, G. H. Collin, A. Connolly, J. M. Conrad, Rebecca Corley, D. F. Cowen, P. Dave, C. De Clercq, J. J. DeLaunay, Diyaselis Delgado, Sen Deng, Abhishek Desai, P. Desiati, K. D. de Vries, G. de Wasseige, T. DeYoung, A. Diaz, J. C. Díaz–Vélez, P. Dierichs, M. Dittmer, A. Domi, Lincoln Draper, H. Dujmovic, D. Durnford, K. Dutta, M. A. DuVernois, T. Ehrhardt, Leonhard Eidenschink, A. Eimer, P. Eller, E. Ellinger, Sharif El Mentawi, Dominik Elsässer, R. Engel, H. Erpenbeck, J. C. Evans, P. A. Evenson, Kwok Lung Fan, Ke Fang, Kareem Ramadan Farrag, A. R. Fazely, A. Fedynitch, N. Feigl, Sebastian Fiedlschuster, C. Finley, L. Fischer, D. B. Fox, A. Franckowiak, S. Fukami, Philipp Fürst, J. Gallagher, Erik Ganster, Alfonso Garcia, M. García, Gaurav Garg, Eliot Genton, L. Gerhardt, A. Ghadimi, C. Girard-Carillo, Christian Gläser, T. Glüsenkamp, J. G. Gonzalez, Sreetama Goswami, Alejandra Granados, Darren Grant, S. J. Gray, Oliver Gries, S. Griffin, S. Griswold, Kathrine Mørch Groth, David Joseph Guevel, C. Günther, Pascal Gutjahr, C. Ha, Christian Haack, A. Hallgren, L. Halve, F. Halzen, H. Hamdaoui, Martin Ha Minh, Michael Handt, K. Hanson, J. Hardin, A. A. Harnisch, P. Hatch, A. Haungs, Jonas Häußler, K. Helbing, Jonas Hellrung, J. Hermannsgabner, L. Heuermann, N. Heyer, S. Hickford, Attila Hidvégi, J. Hignight, C. Hill, G. C. Hill, K. D. Hoffman, Sam Hori, K. Hoshina, Matheus Hostert, Wenjie Hou, Thomas Huber, K. Hultqvist, M. Hünnefeld, R. Hussain, Karolin Hymon, A. Ishihara, W. Iwakiri, M. Jacquart, Samyak Jain, Oliver Janik, M. Jansson, G. S. Japaridze, Minjin Jeong, Miaochen Jin, B. J. P. Jones, N. Kamp, Dong Woo Kang, Woosik Kang, X. Kang, A. Kappes, D. Kappesser, Leonora Kardum, T. Karg, M. Karl, A. Karle, Akanksha Katil, U. Katz, M. Kauer, J. L. Kelley, Manish Khanal, A. Khatee Zathul, Ali Kheirandish, J. Kiryluk, A. Kochocki, R. Koirala, H. Kolanoski, T. Kontrimas, L. Köpke, C. Kopper, D. J. Koskinen, Paras Koundal, Michael Kovacevich, M. Kowalski, Tetiana Kozynets, J. Krishnamoorthi, Karlijn Kruiswijk, E. Krupczak, Ashok Kumar, E. Kun, N. Kurahashi, N. N. Lad, Cristina Lagunas Gualda, M. Lamoureux, M. J. Larson, Silvia Latseva, Frederik Hermann Lauber, J. P. Lazar, J. W. Lee, Kayla Leonard DeHolton, A. Leszczyńska, J. Y. Liao, M. Lincetto, Yantao Liu, Maria Liubarska, Christina Love, L. Lu, Francesco Lucarelli, W. Luszczak, W. Y., J. Madsen, Else Magnus, K. B. M. Mahn, Yuya Makino, Elena Manao, Sarah Mancina, W. Marie Sainte, Ioana Codrina Mariş, S. Marka, Z. Márka, M. Marsee, I. Martinez-Soler, R. Maruyama, Finn Mayhew, F. McNally, J. V. Mead, K. Meagher, S. Mechbal, Andrés Medina, Maximilian Meier, Yarno Merckx, Lukas Merten, Jessie Micallef, J. Mitchell, T. Montaruli, R. W. Moore, Yasutsugu Morii, R. Morse, Marjon Moulai, T. Mukherjee, Richard Naab, Ryo Nagai, M. Nakos, U. Naumann, Jannis Necker, Akshima Negi, Ludwig Neste, M. Neumann, Hans Niederhausen, M. U. Nisa, K. Noda, A. Noell, A. Novikov, A. Obertacke Pollmann, Vivian O'Dell, Bob Oeyen, A. Olivas, R. Orsoe, J. Osborn, Erin O’Sullivan, Veronika Palušová, H. Pandya, N. Park, G. K. Parker, Ek Narayan Paudel, L. Paul, C. 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Bibliographic record
VenuePhysical review. D/Physical review. D. · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsQueen's UniversityInstitute of Particle PhysicsUniversity of Alberta
FundersOffice of Experimental Program to Stimulate Competitive ResearchJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of CanadaPhysics Division, National Center for Theoretical SciencesOffice of Polar ProgramsCollege of Engineering, Michigan State UniversityHelmholtz Alliance for Astroparticle PhysicsAlliance de recherche numérique du CanadaChiba UniversityInstitute for Global Prominent Research, Chiba UniversityRWTH Aachen UniversityKnut och Alice Wallenbergs StiftelseMarsden FundBundesministerium für Bildung und ForschungSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science FoundationBelgian Federal Science Policy OfficeDeutsche ForschungsgemeinschaftDeutsches Elektronen-SynchrotronNational Energy Research Scientific Computing CenterAustralian Research CouncilWestern Canada Research GridFonds De La Recherche Scientifique - FNRSPolarforskningssekretariatetUniversity of MarylandWisconsin Alumni Research FoundationNational Research Foundation of KoreaVillum FondenCompute CanadaCanada Foundation for InnovationMarquette UniversityVetenskapsrådetU.S. Department of EnergyUniversity of Wisconsin-MadisonNvidiaCarlsbergfondetOffice of Advanced CyberinfrastructureEuropean CommissionNational Research FoundationMichigan State UniversityFonds Wetenschappelijk Onderzoek
KeywordsNeutrinoPhysicsMuonMixing (physics)Sterile neutrinoParticle physicsNeutrino oscillation
Abstract
We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements |Uμ4|2<0.0534 and |Uτ4|2<0.0574 at 90% CL under the assumption that Δm412≥1 eV2 . These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the 3+1 sterile neutrino landscape. Published by the American Physical Society 2024
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 head0.049
GPT teacher head0.475
Teacher spread0.426 · 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 designObservational
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
Citations7
Published2024
Admission routes2
Has abstractyes