Neutrino and gamma-ray signatures of inelastic dark matter annihilating outside neutron stars
Bibliographic record
Abstract
Abstract We present a new inelastic dark matter search: neutron stars in dark matter-rich environments capture inelastic dark matter which, for interstate mass splittings between about 45 - 285 MeV, will annihilate away before becoming fully trapped inside the object. This means a sizable fraction of the dark matter particles can annihilate while being outside the neutron star, producing neutron star-focused gamma-rays and neutrinos. We analyze this effect for the first time and target the neutron star population in the Galactic Center, where the large dark matter and neutron star content makes this signal most significant. Depending on the assumed neutron star and dark matter distributions, we set constraints on the dark matter-nucleon inelastic cross-section using existing H.E.S.S. observations. We also forecast the sensitivity of upcoming gamma-ray and neutrino telescopes to this signal, which can reach inelastic cross-sections as low as ∼ 2 × 10 -47 cm 2 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".