A Multi-Time-Gated SPAD Array with Integrated Coarse TDCs
Bibliographic record
Abstract
Time-gating of single-photon avalanche diodes (SPADs) was commonly used as a method to reduce dark noise in biomedical imaging applications where photon events are correlated with a reference clock. Time-gating was also used to obtain timing information of photon events by shifting the gate windows applied to a SPAD array. However, in this approach, fine timing resolution comes at the cost of a lengthened measurement time due to the large number of counts required for each shift. As a solution, we present a multi-time-gated SPAD array that simultaneously applies shifted gate windows to an array of SPADs, which has the potential to reduce the measurement time compared to a single time gate window. Compared to similar works, this design has fully integrated the multi-gate generation using shared circuitry which also functions as a coarse time-to-digital converter. The proposed array, fabricated in the TSMC 65 nm standard CMOS process, achieved a median dark count rate (DCR) of 37 kHz, 4.37 ns gate widths, 550 ps timing resolution, and a peak photon detection probability (PDP) of 42.9% at 420 nm, all at a 0.8 V excess bias.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".