Diphoton signals of muon-philic scalars at DarkQuest
Bibliographic record
Abstract
We analyze the capability of the DarkQuest proton beam-dump experiment at Fermilab to discover new light resonances decaying into photons. As an example model, we focus on muon-philic scalar particles that decay to photons. This is one of the few minimal models that can address the ( g − 2 ) μ anomaly at low mass. These scalars can be copiously produced by meson decays and muon bremsstrahlung. We point out that thanks to DarkQuest’s compact geometry, muons can propagate through the dump and efficiently produce dark scalars near the end of the dump. This mechanism enables DarkQuest to be sensitive to both long-lived and prompt scalars. At the same time, diphoton signatures are generically not background free, and we discuss in detail the different sources of background and strategies to mitigate them. We find that the backgrounds can be sufficiently reduced for DarkQuest to test currently viable ( g − 2 ) μ parameter space. Published by the American Physical Society 2024
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".