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Record W2135328793 · doi:10.1364/ol.35.000312

High-speed quantum random number generation by measuring phase noise of a single-mode laser

2010· article· en· W2135328793 on OpenAlexafffund
Bing Qi, Yue-Meng Chi, Hoi‐Kwong Lo, Li Qian

Bibliographic record

VenueOptics Letters · 2010
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsCanadian Quantum Research CenterUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacsCanadian Institute for Advanced Research
KeywordsOpticsRandom number generationPhase noiseInterferometryQuantum noisePhysicsLasing thresholdLaserNoise (video)Phase (matter)QuantumComputer scienceQuantum mechanicsAlgorithm

Abstract

fetched live from OpenAlex

We present a high-speed random number generation scheme based on measuring the quantum phase noise of a single-mode laser operating at a low intensity level near the lasing threshold. A delayed self-heterodyning system has been developed to measure the random phase fluctuation. By actively stabilizing the phase of the interferometer, a random number generation rate of 500 Mbit/s has been demonstrated and the generated random numbers have passed all the DIEHARD tests.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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

Citations289
Published2010
Admission routes2
Has abstractyes

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