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Record W3091691240 · doi:10.1364/ao.402202

Raman suppression within the gain fiber of high-power fiber lasers

2020· article· en· W3091691240 on OpenAlexafffund
Weixuan Lin, Maxime Desjardins-Carrière, Benoit Sévigny, Julien Magné, Martin Rochette

Bibliographic record

VenueApplied Optics · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceOpticsFiber laserFiber Bragg gratingRaman spectroscopyLaserOptoelectronicsPhotonic-crystal fiberLaser power scalingPolarization-maintaining optical fiberDispersion-shifted fiberDouble-clad fiberFiberFiber optic sensorPhysics

Abstract

fetched live from OpenAlex

We report the effective suppression of Raman emission in a monolithic ytterbium-doped fiber laser by the insertion of a chirped and tilted fiber Bragg grating (CTFBG) directly within the gain fiber of the laser. In comparison with a non-compensated filtered laser cavity for which the Raman threshold occurs at an output power of 1.54 kW, the insertion of a CTFBG within the gain medium leads to an increase in the Raman threshold by 260 W. We also demonstrate that the insertion of a CTFBG in between a laser cavity and a passive beam delivery fiber leads to an increase in the Raman threshold by 100 W with respect to the non-compensated case.

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 score0.002

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 communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.186
Teacher spread0.178 · 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

Citations33
Published2020
Admission routes2
Has abstractyes

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