Semivisible dark photon phenomenology at the GeV scale
Bibliographic record
Abstract
In rich dark sector models, dark photons heavier than tens of MeV can behave as semivisible particles; their decays contain both visible and invisible final states. We present models containing multiple dark fermions which allow for such decays and inscribe them in the context of inelastic dark matter and heavy neutral leptons scenarios. Our models represent a generalization of the traditional inelastic dark matter model by means of a charge conjugation symmetry. We revisit constraints on dark photons from ${e}^{+}{e}^{\ensuremath{-}}$ colliders and fixed-target experiments, including the effect of analysis vetoes on semivisible decays, ${A}^{\ensuremath{'}}\ensuremath{\rightarrow}{\ensuremath{\psi}}_{i}({\ensuremath{\psi}}_{j}\ensuremath{\rightarrow}{\ensuremath{\psi}}_{k}{\ensuremath{\ell}}^{+}{\ensuremath{\ell}}^{\ensuremath{-}})$. We find that in some cases the BABAR and NA64 experiments no longer exclude large kinetic mixing, $\ensuremath{\epsilon}\ensuremath{\sim}{10}^{\ensuremath{-}2}$, and, specifically, the related explanation of the discrepancy in the muon ($g\ensuremath{-}2$). This reopens an interesting window in parameter space for dark photons with exciting discovery prospects. We point out that a modified missing-energy search at NA64 can target short-lived ${A}^{\ensuremath{'}}$ decays and directly probe the newly-open parameter space.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".