A Comprehensive and Accurate Analytical SPAD Model for Circuit Simulation
Bibliographic record
Abstract
The single-photon avalanche diode (SPAD) is an attractive photosensor due to its high sensitivity and low dead time. In this paper, a comprehensive, accurate analytical SPAD circuit simulation model is proposed and implemented in Verilog-A hardware description language. It shows great application universality and is fully compatible with mainstream commercial circuit simulators. This model incorporates all important operating features of the SPAD. Most importantly, to the best of our knowledge, it is the first time that the band-to-band tunneling mechanism and the temporal dependence of after-pulsing probability are included in an SPAD circuit simulation model. The parameter extraction processes from interavalanche time measurement of a free-running SPAD device are discussed. The simulation results indicate that the proposed model works well. In addition, the primary dark counts from the model are validated against the measurement results. A maximum relative error of 8.7% is observed at 20 °C with an excess voltage of 0.5 V. The accuracy of this paper can be greatly improved by using more accurate physical parameters available from the SPAD fabrication vendor.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".