Supernova neutrinos and measurement of liquid scintillator backgrounds in SNO+
Bibliographic record
Abstract
Core collapse supernovae (CCSNe) are amongst the most powerful cosmic sources of neutrinos. The extreme environment during the supernova evolution provides opportunities to probe neutrino properties which are not accessible on Earth. In this thesis, the response to supernova neutrinos of the SNO+ experiment is explored as a representative case of neutrino detectors. SNO+, the successor of the Sudbury Neutrino Observatory (SNO), is a 780-tonne liquid scintillator detector located 2 km underground in Sudbury, Canada. The primary purpose of SNO+ is to detect the neutrinoless double beta (0νββ) in 130Te. During the time period covered by this thesis, SNO+ has undergone the transition from water phase to scintillator phase. By performing a bismuth-polonium (BiPo) coincidence study throughout the period, the 238U and 232Th chain, which are important backgrounds to 0νββ, concentrations in the scintillator have been measured to be (4.6 ± 1.2)×10−17 g/g and (4.8 ± 0.9)×10−17 g/g, respectively. With the measured radioactive background level and calibrated light yield level, a supernova burst trigger was developed. The study showed that SNO+ has the potential of detecting CCSNe at 100 kpc. The experience with the coincidence study was also found to be useful in the identification of inverse beta decay (IBD) signals, which is an important supernova neutrino signal common amongst different detectors. One application of this shared neutrino signal is the positioning of supernovae via multi-detector triangulation, which can serve as an alert to other channels of detection. This thesis presents a method using the comparison of light curves to determine the signal arrival time difference between pairs of detectors. The results outperformed existing methods by further reducing the uncertainty by about 30%. Finally, it was noticed during the triangulation study that the formation of black holes could potentially introduce additional resolution power. Previous studies on the black hole cut-off mostly focused on radial neutrino emissions. To investigate the effect of the black hole, a ray-trace study was performed to give a comprehensive account of the effects of including emissions from all angles upon black hole formation. Both the cases of non-rotating and rotating black holes were discussed. It was discovered that the non-radial emissions contribute a softening to the profile in both cases. Furthermore, extreme rotation introduces significant changes to the tail of the profile, which may be observable with next-generation neutrino 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".