First Direct Detection Constraints on Planck-Scale Mass Dark Matter with Multiple-Scatter Signatures Using the DEAP-3600 Detector
Bibliographic record
Abstract
Dark matter with Planck-scale mass ($\ensuremath{\simeq}{10}^{19}\text{ }\text{ }\mathrm{GeV}/{c}^{2}$) arises in well-motivated theories and could be produced by several cosmological mechanisms. A search for multiscatter signals from supermassive dark matter was performed with a blind analysis of data collected over a 813 d live time with DEAP-3600, a 3.3 t single-phase liquid argon-based detector at SNOLAB. No candidate signals were observed, leading to the first direct detection constraints on Planck-scale mass dark matter. Leading limits constrain dark matter masses between $8.3\ifmmode\times\else\texttimes\fi{}{10}^{6}$ and $1.2\ifmmode\times\else\texttimes\fi{}{10}^{19}\text{ }\text{ }\mathrm{GeV}/{c}^{2}$, and $^{40}\mathrm{Ar}$-scattering cross sections between $1.0\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}23}$ and $2.4\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}18}\text{ }\text{ }{\mathrm{cm}}^{2}$. These results are interpreted as constraints on composite dark matter models with two different nucleon-to-nuclear cross section scalings.
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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".