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Record W4360615356 · doi:10.3390/s23073376

Towards a Multi-Pixel Photon-to-Digital Converter for Time-Bin Quantum Key Distribution

2023· article· en· W4360615356 on OpenAlexafffund
Simon Carrier, Michel Labrecque-Dias, Ramy Tannous, Pascal Gendron, F. Nolet, N. Roy, T. Rossignol, F. Vachon, Samuel Parent, Thomas Jennewein, Serge A. Charlebois, J.‐F. Pratte

Bibliographic record

VenueSensors · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsUniversity of WaterlooUniversité de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologiesCMC MicrosystemsUniversité de SherbrookeNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooCanada First Research Excellence Fund
KeywordsQuantum key distributionTime-to-digital converterBinPhotonComputer scienceElectronic engineeringChipAvalanche photodiodePhysicsDetectorOpticsComputer hardwareEngineeringClock signalTelecommunicationsJitter

Abstract

fetched live from OpenAlex

We present an integrated single-photon detection device custom designed for quantum key distribution (QKD) with time-bin encoded single photons. We implemented and demonstrated a prototype photon-to-digital converter (PDC) that integrates an 8 × 8 single-photon avalanche diode (SPAD) array with on-chip digital signal processing built in TSMC 65 nm CMOS. The prototype SPADs are used to validate the QKD functionalities with an array of time-to-digital converters (TDCs) to timestamp and process the photon detection events. The PDC uses window gating to reject noise counts and on-chip processing to sort the photon detections into respective time-bins. The PDC prototype achieved a 22.7 ps RMS timing resolution and demonstrated operation in a time-bin setup with 158 ps time-bins at an optical wavelength of 410 nm. This PDC can therefore be an important building block for a QKD receiver and enables compact and robust time-bin QKD systems with imaging detectors.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score1.000

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)0.0000.001

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 head0.018
GPT teacher head0.273
Teacher spread0.255 · 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.

Study designSimulation or modeling
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

Citations2
Published2023
Admission routes2
Has abstractyes

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