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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
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