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Record W2587271244 · doi:10.1007/jhep02(2017)033

Stellar cooling bounds on new light particles: plasma mixing effects

2017· article· en· W2587271244 on OpenAlexafffund

Bibliographic record

VenueJournal of High Energy Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsPerimeter Institute
FundersMinistero dello Sviluppo EconomicoInstitut Périmètre de physique théoriqueIndustry CanadaGovernment of Canada
KeywordsSupernovaMixing (physics)Scalar (mathematics)Coupling (piping)PhotonNucleonDark photonPlasmaElectron

Abstract

fetched live from OpenAlex

Strong constraints on the coupling of new light particles to the Standard Model (SM) arise from their production in the hot cores of stars, and the effects of this on stellar cooling. For new light particles which have an effective in-medium mixing with the photon, plasma effects can result in parametrically different production rates to those obtained from a naive calculation. Taking these previously-neglected contributions into account, we make updated estimates for the stellar cooling bounds on light scalars and vectors with a variety of SM couplings. In particular, we improve the bounds on light (m ≲ keV) scalars coupling to electrons or nucleons by up to 3 orders of magnitude in the coupling squared, significantly revise the supernova cooling bounds on dark photon couplings, and qualitatively change the mass dependence of stellar bounds on new vectors. Scalars with mass ≲ 2 keV that couple through the Higgs portal are constrained to mixing angle sin θ ≲ 3 × 10−10, which gives the dominant bound for scalar masses above ∼ 0.2eV.

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)0.001
metaresearch head score (Gemma)0.005
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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

Citations315
Published2017
Admission routes2
Has abstractyes

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