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Record W4408506876 · doi:10.1007/jhep03(2025)080

Broadband phonon production from axion absorption

2025· article· en· W4408506876 on OpenAlexafffund
Itay M. Bloch, Simon Knapen, Amalia Madden, Giacomo Marocco

Bibliographic record

VenueJournal of High Energy Physics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsPerimeter Institute
FundersKavli Institute for Theoretical Physics, University of California, Santa BarbaraMinistry of Colleges and UniversitiesAspen Center for PhysicsHigh Energy PhysicsGordon and Betty Moore FoundationU.S. Department of EnergyInstitut Périmètre de physique théoriqueInnovation, Science and Economic Development CanadaGovernment of CanadaNational Science Foundation
KeywordsPhysicsBroadbandPhononAxionAbsorption (acoustics)Particle physicsCondensed matter physicsQuantum electrodynamicsNuclear physicsOpticsDark matter

Abstract

fetched live from OpenAlex

A bstract We show that axion dark matter in the range meV ≲ m a ≲ 100 meV can incoherently excite phonons in crystal targets with unpolarised nuclear spins. This can occur through its coupling to nuclear spins and/or through its induced time-dependent electric dipole moment in nuclei. Due to the random orientation of the nuclear spins, translation symmetry is broken in the phonon effective theory, allowing axion absorption to create phonons with unrestricted momentum. The absorption rate is therefore proportional to the phonon density of states, which generically has support across a wide range of energies, allowing for a broadband detection scheme. We calculate the absorption rate for solid H 2 , D 2 , Al 2 O 3 , GaAs, H 2 O, D 2 O, Be and Li 2 O, and find that materials containing light, non-zero spin nuclei are the most promising. The predicted rates for the QCD axion are of the order of a few events / 10 kg-year exposure, setting an ambitious target for the required exposure and background suppression.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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 designTheoretical or conceptual
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

Citations5
Published2025
Admission routes2
Has abstractyes

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