First Direct-Detection Constraints on eV-Scale Hidden-Photon Dark Matter with DAMIC at SNOLAB
Bibliographic record
Abstract
We present direct detection constraints on the absorption of hidden-photon dark matter with particle masses in the range $1.2--30\text{ }\mathrm{eV}\text{ }{c}^{\ensuremath{-}2}$ with the DAMIC experiment at SNOLAB. Under the assumption that the local dark matter is entirely constituted of hidden photons, the sensitivity to the kinetic mixing parameter $\ensuremath{\kappa}$ is competitive with constraints from solar emission, reaching a minimum value of $2.2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}14}$ at $17\text{ }\text{ }\mathrm{eV}\text{ }{c}^{\ensuremath{-}2}$. These results are the most stringent direct detection constraints on hidden-photon dark matter in the galactic halo with masses $3--12\text{ }\text{ }\mathrm{eV}\text{ }{c}^{\ensuremath{-}2}$ and the first demonstration of direct experimental sensitivity to ionization signals $<12\text{ }\text{ }\mathrm{eV}$ from dark matter interactions.
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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 | 0.001 |
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 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".