Saturated overburden scattering and the multiscatter frontier: Discovering dark matter at the Planck mass and beyond
Bibliographic record
Abstract
We show that underground experiments like LUX/LZ, PandaX-II, XENON, and PICO could discover dark matter up to the Planck mass and beyond, with new searches for dark matter that scatters multiple times in these detectors. This opens up significant discovery potential via reanalysis of existing and future data. We also identify a new effect that substantially enhances experimental sensitivity to large dark matter scattering cross sections: while passing through atmospheric or solid overburden, there is a maximum number of scatters that dark matter undergoes, determined by the total number of scattering sites it passes, such as nuclei and electrons. For dark matter heavier than $\ensuremath{\sim}{10}^{15}\text{ }\text{ }\mathrm{GeV}$, this extends the reach of some published limits and future analyses to exclude large dark matter scattering cross sections, using detectors two kilometers underground.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".