Probing long-lived axions at the KOTO experiment
Bibliographic record
Abstract
While the main goal of the J-PARC KOTO experiment is to measure the rare decay ${K}_{L}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}\ensuremath{\nu}\overline{\ensuremath{\nu}}$, the unique setup of KOTO raises the possibility to search for physics beyond the Standard Model, in an attempt to probe parts of the parameter space which are not covered by other experiments. In this paper, we test the possibility of using KOTO to search for heavy QCD axions, or axionlike particles, a well-motivated extension of the Standard Model emerging in a variety of models. In particular, we estimate the sensitivity of the current KOTO setup as well as KOTO Step 2 for various benchmark scenarios of axion coupling to the Standard Model. We find that KOTO Step 2 can probe new regions in the parameter space, while KOTO with its current form can only reaffirm the existing bounds. The obtained axion datasets are available as an update of the public code of the alpinist framework, including implementation of KOTO setups in the simulation, allowing for interpretation of various analyses as searches for axions in custom models.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".