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Record W3013487765 · doi:10.1364/josab.390847

Modeling and experimental characterization of a dual-wavelength Bi-doped fiber laser with cascaded cavities

2020· article· en· W3013487765 on OpenAlexafffund
Galina Nemova, Jin Xian, Lawrence R. Chen, Sergei Firstov, Omur Sezerman

Bibliographic record

VenueJournal of the Optical Society of America B · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsOZ Optics (Canada)McGill University
FundersNatural Sciences and Engineering Research Council of CanadaRussian Foundation for Basic Research
KeywordsMaterials scienceCascadeLaserOpticsFiber laserWavelengthFiber Bragg gratingDispersion-shifted fiberLaser power scalingRate equationOptoelectronicsDistributed feedback laserFiberOptical fiberPhysicsFiber optic sensorChemistry

Abstract

fetched live from OpenAlex

We present a comprehensive theoretical and experimental investigation of a dual-wavelength, bismuth-doped fiber (BDF) laser operating near 1700 nm based on cascaded cavities. The BDF provides optical gain from 1650 nm to 1800 nm when pumped at 1550 nm. The linear laser cavity is defined by a 90% fiber mirror on one end and two fiber Bragg gratings (FBGs) with two lengths of BDF in cascade on the other. The laser can operate at either wavelength alone, or both wavelengths simultaneously by simple adjustment of the pump power. We develop a model based on rate equations and radiation transport equations for two level BDF lasers which we then extend to the case for cascaded cavities. Experimental results agree with simulations.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.217
Teacher spread0.204 · 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
GenreMethods

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

Citations10
Published2020
Admission routes2
Has abstractyes

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Same venueJournal of the Optical Society of America BSame topicAdvanced Fiber Optic SensorsFrench-language works237,207