Quenching Circuit Discriminator Architecture Impact on a Sub-10 ps FWHM Single-Photon Timing Resolution SPAD
Bibliographic record
Abstract
In the field of radiation instrumentation, there is a desire to reach a sub-10 ps FWHM timing resolution for applications such as time-of-flight positron emission tomography, time-of-flight positron computed tomography and time-resolved calorimetry. One of the key parts of the detection chain for these applications is a single-photon detector and, in recent years, the first single-photon avalanche diode (SPAD) with a sub-10 ps timing resolution was presented. To reach such a timing resolution, the SPAD was read out by an operational amplifier operated in open-loop as a comparator. This paper presents a comparison between comparators and inverters to determine which type of leading-edge discriminator can obtain the best single-photon timing resolution. Six different quenching circuits (QCs) implemented in TSMC 65 nm are tested with SPADs of the same architecture and in the same operation conditions. This allows us to compare experimental results between the different QCs. This paper also presents a method to measure the SPAD signal slope, the SPAD excess voltage variation and simulations to determine the added jitter of different leading-edge discriminators. For some discriminator architectures, a cascode transistor was required to increase the maximum excess voltage of the QC. This paper also presents the impact on the single-photon timing resolution of adding a cascode transistor for a comparator or an inverter-based discriminator. This paper reports a 6.3 ps FWHM SPTR for a SPAD read out by a low-threshold comparator and a 6.8 ps FWHM SPTR for an optimized 1 V inverter using a cascode transistor for a higher excess voltage.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".