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Record W2245204361 · doi:10.1364/josab.32.001676

Efficiency of dispersive wave generation in dual concentric core microstructured fiber

2015· preprint· en· W2245204361 on OpenAlexaff
D. Modotto, Marco Andreana, Katarzyna Krupa, G. Manili, Umberto Minoni, Alessandro Tonello, Vincent Couderc, Alain Barthélémy, Alexis Labruyère, Badr Mohammed Shalaby, Philippe Leproux, S. Wabnitz, Alejandro B. Aceves

Bibliographic record

VenueJournal of the Optical Society of America B · 2015
Typepreprint
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsUniversity of Ottawa
FundersMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsWavelengthDispersion (optics)OpticsZero-dispersion wavelengthMaterials scienceCore (optical fiber)FiberDispersion-shifted fiberMulti-mode optical fiberAmplitudeNanosecondConcentricOptical fiberLaserPhysicsFiber optic sensorMathematics

Abstract

fetched live from OpenAlex

We describe the generation of powerful dispersive waves that are observed when pumping a dual concentric core microstructured fiber by means of a sub-nanosecond laser emitting at a wavelength of 1064 nm. The presence of three zeros in the dispersion curve, their spectral separation from the pump wavelength, and the complex dynamics of solitons originated by the pump pulse breakup all contribute to boost the amplitude of the dispersive wave on the long-wavelength side of the pump. The measured conversion efficiency toward the dispersive wave at 1548 nm is as high as 50%. Our experimental analysis of the output spectra is completed by the acquisition of time delays of the different spectral components. Numerical simulations and an analytical perturbative analysis identify the central wavelength of the redshifted pump solitons and the dispersion profile of the fiber as the key parameters for determining the efficiency of the dispersive wave generation process.

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 score0.001
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 head0.023
GPT teacher head0.235
Teacher spread0.212 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueJournal of the Optical Society of America BSame topicPhotonic Crystal and Fiber OpticsFrench-language works237,207