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Record W1991123090 · doi:10.1364/oe.17.010419

Output characterization of a self-pulsating and aperiodic optical fiber source based on cascaded regeneration

2009· article· en· W1991123090 on OpenAlexafffund
Kai Sun, Martin Rochette, Lawrence R. Chen

Bibliographic record

VenueOptics Express · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsPicosecondBand-pass filterDispersion (optics)Materials sciencePulse (music)AmplifierWavelengthPhysicsOptoelectronicsLaser

Abstract

fetched live from OpenAlex

We investigate the properties of a self-pulsating fiber cavity based on cascaded regeneration. The mechanisms that govern the number of oscillating pulses in the cavity, the pulse peak power, the pulse width, the wavelength tunability as well as the generation of sub-picosecond pulses are identified, analyzed and quantified. We find that the described self-pulsating cavity enables the oscillation of quasi transform-limited pulses with a pulsewidth of 4.8 ps at 1540.0 nm when using 0.4 nm non-Gaussian bandpass filters. Sub-picosecond pulses with an autocorrelation width of 471 fs are generated from the same self-pulsating source with modified bandpass filters and the addition of a chromatic dispersion compensator. The number of eigenpulses that oscillate simultaneously in the cavity can be adjusted from 0 up to 29,500 with proper cavity adjustment. This source has dual-wavelength output and can be tuned throughout the gain band of the amplifiers.

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 score0.004

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 studies0.0000.000
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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

Citations38
Published2009
Admission routes2
Has abstractyes

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