Neutron Measurements and Reactor Antineutrino Search with the SNO+ Detector in the Water Phase
Bibliographic record
Abstract
The SNO+ experiment is a large-scale liquid scintillator neutrino experiment with a wide range of physics objectives. SNO+ has adopted a staged approach where the detector was first filled with ultra-pure water before substituting with liquid scintillator and the target isotope $^{130}$Te for neutrinoless double beta decay. During the SNO+ water phase, an $^{241}$Am$^{9}$Be source is deployed across the detector volume to calibrate the detector's energy response and its response to neutrons. The $^{241}$Am$^{9}$Be source emits a unique coincidence signal with the prompt event being a 4.4 MeV $\gamma$ and the delayed a neutron capture signal (2.2 MeV $\gamma$). A novel, minimalistic, statistical analysis of the $^{241}$Am$^{9}$Be calibration data was designed and used to measure the capture time constant $\tau$, capture cross-section $\sigma_{H,t}$, and the neutron detection efficiency $E_{\textrm{center}}$ at the center of the detector: \begin{equation} \begin{aligned} &\tau = 202.35 \pm 0.42\ (stat.)\ ^{+0.38}_{-0.31}\ (syst.)~\mu\textrm{s}, \\ &\sigma_{H,t} = 336.3 ^{+1.2}_{-1.5}~\textrm{mb}, \\ &E_{\textrm{center}} = (50.8 \pm 0.6)\%. \end{aligned} \end{equation} Additionally, with the help of Monte Carlo simulations, a volume-weighted neutron detection efficiency across the detector is evaluated to be $E_{\textrm{detector}} = (46.5 \pm 0.5\ (stat.\ only))\%$. The simulation is also central to an energy calibration using the 4.4 MeV $\gamma$ to measure the energy resolution and energy scale of the detector. Finally, with $\sim$115 days of early water data, an upper limit, $\hat{\Phi}_{\bar{\nu}_e, \textrm{ult}}$ = $(1.76 \pm 0.29) \times 10^6 \bar{\nu}/(\textrm{cm}^2\cdot\textrm{s})$, on the reactor antineutrino flux for SNO+ is obtained using a maximum likelihood approach. The limit is about a factor of 9 higher than the expected signal in SNO+, which can be calculated using available reactor output power data.
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) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".