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Record W4408547206 · doi:10.1007/jhep03(2025)102

CPon Dark Matter

2025· article· en· W4408547206 on OpenAlexaff
Ferruccio Feruglio, Robert Ziegler

Bibliographic record

VenueJournal of High Energy Physics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsPhysicsDark matterParticle physics

Abstract

fetched live from OpenAlex

A bstract We study a class of supersymmetric models where the strong CP problem is solved through spontaneous CP violation, carried out by a complex scalar field that determines the Yukawa couplings of the theory. Assuming that one real component of this field — the CPon — is light, we examine the conditions under which it provides a viable Dark Matter candidate. The CPon couplings to fermions are largely determined by the field-dependent Yukawa interactions, and induce couplings to gauge bosons at 1-loop. All couplings are suppressed by an undetermined UV scale, which needs to exceed 10 12 GeV in order to satisfy constraints on excessive stellar cooling and rare kaon decays. The CPon mass is limited from below by 5th force experiments and from above by X-ray telescopes looking for CPon decays to photons, leaving a range roughly between 10 meV and 1 MeV. Everywhere in the allowed parameter space the CPon can saturate the observed Dark Matter abundance through an appropriate balance of misalignment and freeze-in production from heavy SM fermions.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

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 studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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