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Record W2998114873 · doi:10.1364/ol.383124

Mode characteristic manipulation of random feedback interferometers in Brillouin random fiber laser

2019· article· en· W2998114873 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

VenueOptics Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsOpticsFiber Bragg gratingLongitudinal modeBrillouin scatteringRayleigh scatteringPhysicsInterferometryAstronomical interferometerSingle-mode optical fiberFiber laserOptical fiberLaser

Abstract

fetched live from OpenAlex

The Brillouin random fiber laser (BRFL) suffers from high intensity noise that comes mainly from longitudinal mode beating at different mode frequencies. In this Letter, we propose and demonstrate that the mode characteristic of BRFL can be manipulated by distributed random feedback, which acts as the longitudinal mode filter. A theoretical model is developed for the first time, to the best of our knowledge, to analyze the mode characteristics of BRFL with different lengths of a weak fiber Bragg grating (FBG) array. In experiment, a single FBG, weak FBG array (reflection of $ - {40}\;{\rm dB}$-40dB) at various lengths, and a Rayleigh scattering fiber are used to provide the random feedback. Both theoretical analysis and experimental results show that single longitudinal mode operation can be realized with the distributed random feedback interferometer, leading to a stable temporal intensity output of the BRFL in the time domain.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.730

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)0.0010.000

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 head0.215
Teacher spread0.208 · 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