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Record W2890015844 · doi:10.3390/instruments2040019

Quenching Circuit and SPAD Integrated in CMOS 65 nm with 7.8 ps FWHM Single Photon Timing Resolution

2018· article· en· W2890015844 on OpenAlexafffund
F. Nolet, Samuel Parent, N. Roy, Marc-Olivier Mercier, Serge A. Charlebois, Réjean Fontaine, J.‐F. Pratte

Bibliographic record

VenueInstruments · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsJitterFull width at half maximumCMOSAvalanche diodeSilicon photomultiplierSingle-photon avalanche diodePhysicsVoltagePhotonicsOptoelectronicsPropagation delayMaterials scienceOpticsElectronic engineeringAvalanche photodiodeDetectorBreakdown voltageEngineeringScintillator

Abstract

fetched live from OpenAlex

This paper presents a new quenching circuit (QC) and single photon avalanche diode (SPAD) implemented in TSMC CMOS 65 nm technology. The QC was optimized for single photon timing resolution (SPTR) with a view to an implementation in a 3D digital SiPM. The presented QC has a timing jitter of 4 ps full width at half maximum (FWHM) and the SPAD and QC has a 7.8 ps FWHM SPTR. The QC adjustable threshold allows timing resolution optimization as well as SPAD excess voltage and rise time characterization. The adjustable threshold, hold-off and recharge are essential to optimize the performances of each SPAD. This paper also provides a better understanding of the different contributions to the SPTR. A study of the contribution of the SPAD excess voltage variation combined to the QC time propagation delay variation is presented. The proposed SPAD and QC eliminates the SPAD excess voltage contribution to the SPTR for excess voltage higher than 1 V due to its fixed time propagation delay.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.243
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations62
Published2018
Admission routes2
Has abstractyes

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