Measurements and modelling of secondary photon emission from SPADs and SiPMs
Bibliographic record
Abstract
This work presents experimental and modelling results for the secondary emission of photons in Single Photon Avalanche Diodes (SPADs) and Silicon Photomultipliers (SiPMs). Recombination of high-energy charge carriers during an avalanche can themselves produce photons, which may trigger secondary avalanches in other pixels of an SiPM or in other devices within a larger detector system. Accurate characterization of such ‘crosstalk’ noise mechanisms aids in precise photon counting using SiPMs and is essential for the design of detectors containing many such devices. The Microscope for the Injection and Emission of Light (MIEL) setup at TRIUMF has been used to measure the spectrum and number of photons emitted by laser-stimulated avalanches in various SiPMs, including conventional analogue devices and a ‘digital’ SiPM. A digital device allows SPAD pixels to be individually controlled, meaning that emission from a single SPAD can be measured with surrounding pixels deactivated in order to minimize systematic error. Measurement results will be presented alongside modelling of photon transport through an SiPM structure, relating the number of photons emitted from a device to the number produced by an avalanche within the silicon crystal. This permits a consideration of the recombination mechanisms which produce secondary photons, enabling generalization to the emission characteristics of a wide range of SPAD and SiPM structures and the optimized design of detectors with minimal crosstalk noise.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".