Proof of principle for a light dark matter search with low-energy positron beams at NA64
Bibliographic record
Abstract
A bstract Thermal light dark matter (LDM) with particle masses in the 1 MeV–1 GeV range could successfully explain the observed dark matter abundance as a relic from the primordial Universe. In this picture, a new feeble interaction acts as a “portal” between the Standard Model and LDM particles, allowing for the exploration of this paradigm at accelerator experiments. In the last years, the “missing energy” experiment NA64 e at CERN SPS (Super Proton Synchrotron) has set world-leading constraints in the vector-mediated LDM parameter space, by exploiting a 100 GeV electron beam impinging on an electromagnetic calorimeter, acting as an active target. In this paper, we report a detailed description of the analysis of a preliminary measurement with a 70 GeV/c positron beam at NA64 e , performed during summer 2023 with an accumulated statistics of 1 . 596 × 10 10 positrons on target (hereafter referred to as e + OT). This data set was analyzed with the primary aim of evaluating the performance of the NA64 e detector with a lower energy positron beam, towards the realization of the post-LS3 program. The analysis results, other than additionally probing unexplored regions in the LDM parameter space, provide valuable information towards the future NA64 e positron campaign.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".