Characterization of external cross-talk from silicon photomultipliers in a liquid xenon detector
Bibliographic record
Abstract
Silicon photomultipliers (SiPMs) are solid-state photo-detectors sensitive to single photons. They are composed of arrays of single-photon avalanche diodes (SPADs). Compared with the conventional photo-multiplier tubes (PMTs) widely used in particle and astroparticle physics, SiPMs are very compact, have an exceptional gain under low voltage and provide a fast response. For these reasons, SiPMs are attractive candidates to future noble-liquid scintillator rare-event search experiments such as dark matter and neutrino-less double beta decay experiments. The Light-only Liquid Xenon experiment (LoLX) is a small-scale R&D liquid xenon (LXe) setup located at McGill University. The detector is a small 3D-printed cylinder immersed in LXe. It operates 96 Hamamatsu VUV4 SiPMs. LoLX’s main goals are to study light emission and transport in LXe and to perform detailed characterization of SiPMs in order to inform future LXe experiments. When a photon triggers an avalanche in a SPAD, some light is emitted in the near infrared region (NIR). NIR light can transport across the detector to distant SiPMs and trigger correlated avalanches. This process is called external cross talk (eXT). It is crucial for future planned experiments to have a good understanding of eXT in a detector with similar geometric acceptance, such as LoLX, because it can impact their energy resolution. We will present the first measurement of SiPM external crosstalk in LXe with the LoLX detector.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".