Characterization of the background spectrum in DAMIC at SNOLAB
Why this work is in the frame
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Bibliographic record
Abstract
We construct the first comprehensive radioactive background model for a dark matter search with charge-coupled devices (CCDs). We leverage the well-characterized depth and energy resolution of the DAMIC at SNOLAB detector and a detailed geant4-based particle-transport simulation to model both bulk and surface backgrounds from natural radioactivity down to $50\text{ }\text{ }{\mathrm{eV}}_{\mathrm{ee}}$. We fit to the energy and depth distributions of the observed ionization events to differentiate and constrain possible background sources, for example, bulk $^{3}\mathrm{H}$ from silicon cosmogenic activation and surface $^{210}\mathrm{Pb}$ from radon plate-out. We observe the bulk background rate of the DAMIC at SNOLAB CCDs to be as low as $3.1\ifmmode\pm\else\textpm\fi{}0.6\text{ }\text{ }\mathrm{counts}\text{ }{\mathrm{kg}}^{\ensuremath{-}1}\text{ }{\mathrm{day}}^{\ensuremath{-}1}\text{ }{\mathrm{keV}}_{\mathrm{ee}}^{\ensuremath{-}1}$, making it the most sensitive silicon dark matter detector. Finally, we discuss the properties of a statistically significant excess of events over the background model with energies below $200\text{ }\text{ }{\mathrm{eV}}_{\mathrm{ee}}$.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 it