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Record W2030483895 · doi:10.1117/12.567258

Analysis of the nonlinear optical loop mirror with feedback and low-birefringence twisted fiber in the loop

2004· article· en· W2030483895 on OpenAlexaff
Clark A. Merchant, A. L. Steele

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCarleton University
Fundersnot available
KeywordsBirefringenceOpticsPhysicsFeedback loopBistabilityResonatorOptical fiberNonlinear systemPolarization-maintaining optical fiberPolarization (electrochemistry)OptoelectronicsFiber optic sensorComputer science

Abstract

fetched live from OpenAlex

The dynamical behavior of the nonlinear optical loop mirror (NOLM) with feedback and low birefringence twisted fiber in the loop is examined. It is found that the output of the NOLM with feedback depends on many parameters, including the fiber beat length, the polarization state of the counter-propagating beams in the loop, as well as the length, twist rate, and nonlinearities of the loop fiber. The placement of a quarter-wave plate (QWP) asymmetrically in the loop allows for the tuning of the bistable and chaotic output from the optical resonator. As well, the output polarization state of the NOLM with feedback is shown to rely on the QWP angle as well as the input power, which is of importance when using the NOLM with feedback in optical systems that have polarization sensitivity. As all fibers exhibit some degree of twist and birefringence, the addition of a QWP in the NOLM with feedback allows for an easy and practical measure of control of the bistable and chaotic regions of the nonlinear optical resonator, which is important when implementing the device in an optical system.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Fiber Optic SensorsFrench-language works237,207