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Record W2078841973 · doi:10.1109/memea.2013.6549731

A fast quench-reset integrated circuit for high-speed single photon detection

2013· article· en· W2078841973 on OpenAlexafffund
Mahmoud Ameri, Ehsan Kamrani, Saeid Hashemi, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsPolytechnique Montréal
FundersCanadian Institutes of Health ResearchCanada Research ChairsHeart and Stroke Foundation of Canada
KeywordsReset (finance)Avalanche photodiodePhoton countingCMOSComputer scienceSchematicApplication-specific integrated circuitIntegrated circuitDetectorElectronic circuitElectronic engineeringPhysicsOptoelectronicsElectrical engineeringComputer hardwareEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper presents the design and implementation of a high-speed, and low-power single photon detection system. The system consists of a quench module and a digitizer in forward path and a reset feedback scheme to realize a reset block. This circuit when accompanied with an avalanche photodiode (APD) in its front-end could accurately detect and count the generated photons in few nanoseconds. Schematic-based simulations were conducted with TSMC 180nm CMOS process to characterize the circuit. The simulation results confirm quench time of 3ns for the circuit which adopts to the requirements of high speed photon detection quench circuits in functional near infrared optical brain imaging spectroscopy. The measurements are undergoing and preliminary results confirm the functionality of the design. Controllable hold-off time of 4ns-2μs and a reset time of 1-4ns enhance the characteristics of the proposed circuit among the previously cited solutions.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.114
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.189
Teacher spread0.177 · 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 teacher head, 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

Citations6
Published2013
Admission routes2
Has abstractyes

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