Characterization of SiPM Avalanche Triggering Probabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Silicon photo-multipliers (SiPMs) are detectors sensitive to single photons that are used to detect scintillation and Cherenkov light in a variety of physics and medical-imaging applications. SiPMs measure single photons by amplifying the photo-generated carriers (electrons or holes) via a Geiger-mode avalanche. The photon detection efficiency (PDE) is the combined probability that a photon is absorbed in the active volume of the device with a subsequently triggered avalanche. Absorption and avalanche triggering probabilities are correlated since the latter probability depends on where the photon is absorbed. In this article, we introduce a physics-motivated parameterization of the avalanche triggering probability that describes the PDE of a SiPM as a function of its reverse bias voltage, at different wavelengths. This parameterization is based on the fact that in p-on-n SiPMs, the induced avalanches are electron-driven in the ultraviolet (UV) range, while they become increasingly hole-driven toward the infrared range. The model has been successfully applied to characterize two Hamamatsu multi-pixel photon counters (MPPCs) and one Fondazione-Bruno-Kessler (FBK) SiPM, and it can be extended to other SiPMs. Furthermore, this model provides key insight into the electric field structure within SiPMs, which can explain the limitation of the existing devices and be used to optimize the performance of the future SiPMs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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 it