Analysis of cryogenic calorimeters with light and heat read-out for double beta decay searches
Bibliographic record
Abstract
The suppression of spurious events in the region of interest for neutrinoless double beta decay will play a major role in next generation experiments. The background of detectors based on the technology of cryogenic calorimeters is expected to be dominated by $$\alpha $$ particles, that could be disentangled from double beta decay signals by exploiting the difference in the emission of the scintillation light. CUPID-0, an array of enriched Zn $$^{82}$$ Se scintillating calorimeters, is the first large mass demonstrator of this technology. The detector started data-taking in 2017 at the Laboratori Nazionali del Gran Sasso with the aim of proving that dual read-out of light and heat allows for an efficient suppression of the $$\alpha $$ background. In this paper we describe the software tools we developed for the analysis of scintillating calorimeters and we demonstrate that this technology allows to reach an unprecedented background for cryogenic calorimeters.
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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 | 0.001 | 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".