The liquid-argon scintillation pulseshape in DEAP-3600
Bibliographic record
Abstract
Abstract DEAP-3600 is a liquid-argon scintillation detector looking for dark matter. Scintillation events in the liquid argon (LAr) are registered by 255 photomultiplier tubes (PMTs), and pulseshape discrimination (PSD) is used to suppress electromagnetic background events. The excellent PSD performance of LAr makes it a viable target for dark matter searches, and the LAr scintillation pulseshape discussed here is the basis of PSD. The observed pulseshape is a combination of LAr scintillation physics with detector effects. We present a model for the pulseshape of electromagnetic background events in the energy region of interest for dark matter searches. The model is composed of (a) LAr scintillation physics, including the so-called intermediate component, (b) the time response of the TPB wavelength shifter, including delayed TPB emission at $${\mathcal {O}}$$ O (ms) time-scales, and c) PMT response. TPB is the wavelength shifter of choice in most LAr detectors. We find that approximately 10% of the intensity of the wavelength-shifted light is in a long-lived state of TPB. This causes light from an event to spill into subsequent events to an extent not usually accounted for in the design and data analysis of LAr-based detectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".