Characterization of external cross-talk from silicon photomultipliers in a liquid xenon detector
Bibliographic record
Abstract
Abstract The Light-only Liquid Xenon experiment (LoLX) employs a small-scale detector equipped with 96 Hamamatsu VUV4 silicon photomultipliers (SiPMs) submerged in 5 kg of liquid xenon (LXe) to perform characterization measurements of light production, transport and detection in xenon. In this work, we perform a novel measurement of the “external cross-talk” (ExCT) of SiPMs, where photons produced in the avalanche escape the device and produce correlated signals on other SiPMs. SiPMs are the photodetector technology of choice for next generation rare-event search experiments; understanding the sources and effects of correlated noise in SiPMs is critical for producing accurate estimates of detector performance and sensitivity projections. We measure the probability to observe ExCT through timing correlation of detected photons in low-light conditions within LoLX. Measurements of SiPM ExCT are detector dependent; thus the ExCT process is simulated and modelled using the Geant4 framework. Utilizing simulations, we determine the average transport and detection efficiency for ExCT photons within LoLX, a necessary input to extract the true ExCT probability and detector independent photon emission intensity. For an applied overvoltage of 4 V and 5 V, we measure a mean number of photons emitted into LXe per avalanche of $$0.5^{+0.3}_{-0.2}$$ 0 . 5 - 0.2 + 0.3 and $$0.6^{+0.3}_{-0.2},$$ 0 . 6 - 0.2 + 0.3 , respectively. Using an optical model to describe photon transmission through the SiPM surface, this corresponds to an estimated photon yield inside the bulk silicon of $$20^{+11}_{-9}$$ 20 - 9 + 11 and $$25^{+12}_{-9}$$ 25 - 9 + 12 photons per avalanche. The relative increase in intensity of SiPM ExCT emission between 4 and 5 V is consistent with expectation for the linear increase of gain with respect to overvoltage.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".