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Search by the SENSEI Experiment for Millicharged Particles Produced in the NuMI Beam

2024· article· en· W4401526852 on OpenAlexfundno aff
L. Barak, Itay M. Bloch, Ana Martina Botti, Mariano Cababié, Gustavo Cancelo, Brenda A. Cervantes-Vergara, Luke Chaplinsky, M. B. Crisler, A. Drlica-Wagner, Rouven Essig, J. Estrada, Erez Etzion, Guillermo Fernández Moroni, S. Holland, Yaron Korn, Ian T. Lawson, Steffon Luoma, Sravan Munagavalasa, Aviv Orly, Santiago E. Perez, Darío Rodrigues, N. Saffold, S. Scorza, Aman Singal, Miguel Sofo Haro, Leandro Stefanazzi, Kelly Stifter, Javier Tiffenberg, Sho Uemura, Tomer Volansky, T. Yu, Roni Harnik, Zhen Liu, Ryan Plestid

Bibliographic record

VenuePhysical Review Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsnot available
FundersPlanning and Budgeting Committee of the Council for Higher Education of IsraelHorizon 2020 Framework ProgrammeMinistry of Colleges and UniversitiesAzrieli FoundationCanada Foundation for InnovationIsrael Science FoundationHeising-Simons FoundationEuropean Research CouncilWalter Burke Institute for Theoretical PhysicsAmbrose Monell FoundationU.S. Department of Energy
KeywordsPhysicsNuclear physicsBeam (structure)MINOSFermi Gamma-ray Space TelescopeProtonElectronParticle physicsBeam dumpNeutrinoNeutrino oscillationAstrophysicsOptics

Abstract

fetched live from OpenAlex

Millicharged particles appear in several extensions of the standard model, but have not yet been detected. These hypothetical particles could be produced by an intense proton beam striking a fixed target. We use data collected in 2020 by the SENSEI experiment in the MINOS cavern at the Fermi National Accelerator Laboratory to search for ultrarelativistic millicharged particles produced in collisions of protons in the NuMI beam with a fixed graphite target. The absence of any ionization events with 3 to 6 electrons in the SENSEI data allow us to place world-leading constraints on millicharged particles for masses between 30 to 380 MeV. This work also demonstrates the potential of utilizing low-threshold detectors to investigate new particles in beam-dump experiments, and motivates a future experiment designed specifically for this purpose.

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 imitation

Not 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.314
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine 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 designBench or experimental
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

Citations21
Published2024
Admission routes1
Has abstractyes

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