Limits on the Light Dark Matter–Proton Cross Section from Cosmic Large-Scale Structure
Bibliographic record
Abstract
We set the strongest limits to date on the velocity-independent dark matter (DM)--proton cross section $\ensuremath{\sigma}$ for DM masses $m=10\text{ }\text{ }\mathrm{keV}$ to 100 GeV, using large-scale structure traced by the Lyman-alpha forest: e.g., a 95% lower limit $\ensuremath{\sigma}<6\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}30}\text{ }\text{ }{\mathrm{cm}}^{2}$, for $m=100\text{ }\text{ }\mathrm{keV}$. Our results complement direct detection, which has limited sensitivity to sub-GeV DM. We use an emulator of cosmological simulations, combined with data from the smallest cosmological scales used to date, to model and search for the imprint of primordial DM--proton collisions. Cosmological bounds are improved by up to a factor of 25.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".