Temperature quenching in LAB based liquid scintillator and muon-induced backgrounds in the SNO+ experiment
Bibliographic record
Abstract
The starting SNO+ experiment, successor to the Sudbury Neutrino Observatory, is a neutrino detector using LAB based liquid scintillator as active medium. Situated in the SNOLab deep underground laboratory in Sudbury, Canada, the rock overburden amounts to about 6 km.w.e., providing an effective shielding against cosmic rays. The residual muon rate is 63 μ/day going through the detector volume. About 780 t of an LAB mixture inside an acrylic sphere with a 6 m radius will be observed by ≈ 9300 photomultipliers, surrounded by a ≈ 7000 t water shielding. SNO+ will be searching for low energy solar-, geo-, reactor- and supernova neutrinos, but the main goal is the observation of the neutrinoless double beta decay in Te-130. Under operating conditions, the scintillator will be cooled to about 12° C. This work investigated the effect of temperature changes on the light output of LAB based liquid scintillator in a range from -5° C to 30° C with α-particles and electrons in a small scale setup. Assuming a linear behaviour, a combined negative temperature coefficient of (−0.29 ± 0.01) %/° C is found. Considering hints for a particle type dependency, electrons show (−0.17 ± 0.02) %/° C whereas the temperature dependency seems stronger for α-particles (−0.35 ± 0.03) %/° C. A pulse shape analysis shows increased strength of a slow decay component at lower temperatures, pointing to reduced non-radiative triplet state de-excitations at lower temperatures. Furthermore, this work found upper bounds for the in-situ muon-induced isotope production via scaling calculations and simulations with Geant4 based software. For the most concerning isotope C-11, an upper limit of about 1.3 × 10^3 decays/kt/yr is found and a reduction technique, developed by the Borexino collaboration, can be effectively applied for SNO+. Also a muon reconstruction algorithm is implemented, performing reasonably well, but not good enough to improve the background reduction scheme.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".