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Record W2724842419 · doi:10.1109/lpt.2017.2722381

High-Speed Random Bit Generation via Brillouin Random Fiber Laser With Non-Uniform Fibers

2017· article· en· W2724842419 on OpenAlexafffund
Song Gao, Liang Zhang, Yanping Xu, Liang Chen, Xiaoyi Bao

Bibliographic record

VenueIEEE Photonics Technology Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBrillouin zoneBrillouin scatteringLasing thresholdOpticsOptical fiberRayleigh scatteringMaterials scienceComputer sciencePhysicsLaser

Abstract

fetched live from OpenAlex

A bidirectional pumping Brillouin random fiber laser based on a non-uniform fiber is proposed and demonstrated for truly random number generation with enhanced bit rate. Numerical simulation indicates that, thanks to the unique distributed Brillouin gain profile along the non-uniform fiber, random lasing oscillation within a broadband Brillouin gain can be established by the mutual effect of Brillouin scattering and enhanced Rayleigh scattering, providing physical entropy source for truly random number generation. The poof-of-concept experiments demonstrate a truly random number with a bit rate of 71 Mbps, which significantly breaks through the limitation of the intrinsic Brillouin bandwidth (~10 MHz) in communication fibers.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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

Citations22
Published2017
Admission routes2
Has abstractyes

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