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Record W2094857917 · doi:10.1109/jstqe.2011.2119294

SOA Fiber Ring Lasers: Single- Versus Multiple-Mode Oscillation

2011· article· en· W2094857917 on OpenAlexaff
S. S. Girard, Michel Piché, Hongxin Chen, G. G. Schinn, Wang‐Yuhl Oh, B. B. Bouma

Bibliographic record

VenueIEEE Journal of Selected Topics in Quantum Electronics · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsExfo Electro-Optical Engineering (Canada)Université LavalInstitut National d'Optique
Fundersnot available
KeywordsLaser linewidthOpticsOptical amplifierFiber laserMaterials scienceOptical filterLongitudinal modeSemiconductor laser theoryLaserMulti-mode optical fiberBandwidth (computing)Ring laserSingle-mode optical fiberActive laser mediumOptoelectronicsOptical fiberPhysicsLaser power scalingComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Earlier investigations have demonstrated that a narrow bandwidth intracavity filter in a semiconductor optical amplifier (SOA) fiber ring laser results in an output spectrum comprising multiple longitudinal modes, whereas a large bandwidth filter generally leads to quasi-single-mode oscillation. In this paper, we report on a numerical model simulating the SOA fiber ring laser dynamics and compare its predictions with experimental results obtained with two different SOAs. We demonstrate that the observed experimental behavior results from the interplay between the complex transfer function of the intracavity optical filter, fast gain saturation and four-wave mixing (FWM) due to the linewidth enhancement factor. The dispersion introduced by the complex transfer function of the filter can lead to modulation instability, which plays a key role in the laser dynamics that can evolve into a single-longitudinal mode (SLM) operation. We also simulate the behavior of the laser emission when the wavelength of the optical filter is finely tuned.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.272
Teacher spread0.237 · 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 teacher head, 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

Citations17
Published2011
Admission routes1
Has abstractyes

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