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Electric But Not Eclectic: Thermal Relic Dark Matter for the XENON1T Excess

2020· article· en· W3037947687 on OpenAlexafffund
Joseph Bramante, Ningqiang Song

Bibliographic record

VenuePhysical Review Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsQueen's UniversityArthur B. McDonald-Canadian Astroparticle Physics Research InstitutePerimeter Institute
FundersInstitut Périmètre de physique théoriqueNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaMinistry of Colleges and UniversitiesInnovation, Science and Economic Development Canada
KeywordsPhysicsDark matterLight dark matterParticle physicsScalar field dark matterDark fluidDark energyNuclear physicsCosmologyAstrophysics

Abstract

fetched live from OpenAlex

The identity of dark matter is being sought with increasingly sensitive and voluminous underground detectors. Recently the XENON1T Collaboration reported excess electronic recoil events, with most of these having recoil energies around 1-30 keV. We show that a straightforward model of inelastic dark matter produced via early Universe thermal freeze-out annihilation can account for the XENON1T excess. Remarkably, this dark matter model consists of a few simple elements: sub-GeV mass Dirac fermion dark matter coupled to a lighter dark photon kinetically mixed with the standard model photon. A scalar field charged under the dark U(1) gauge symmetry can provide a mass for the dark photon and splits the Dirac fermion component state masses by a few keV, which survive in equal abundance and interact inelastically with electrons and nuclei.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.264
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations60
Published2020
Admission routes2
Has abstractyes

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