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Record W2067833495 · doi:10.1117/12.577172

A novel laser device for all optical wavelength conversion

2005· article· en· W2067833495 on OpenAlexaff
Zhenguo Lü, Chander P. Grover

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceOpticsWavelengthOptical amplifierOptoelectronicsLaser linewidthEnergy conversion efficiencyLaserPhotonicsTerahertz radiationZero-dispersion wavelengthOptical fiberDispersion-shifted fiberPhysicsFiber optic sensor

Abstract

fetched live from OpenAlex

A widely tunable, narrow-linewidth, simultaneous triple-wavelength oscillation erbium-doped fiber ring laser (EDFRL) has been developed. The EDFRL can produce double-wavelength oscillations with the same linear-polarization output, as well as another widely tunable wavelength oscillation with orthogonal linear-polarization from 1522.2 nm to 1595.9 nm. The long-term stability of the triple-wavelength output was observed with a high signal-to-noise ratio of larger than 40 dB. By using this EDFRL in combination with a 1550-nm semiconductor optical amplifier (SOA), an ultrabroad tunable wavelength converter is demonstrated with uniform efficiency and equalized optical signal-to-noise ratio (OSNR) over a 9.1 THz tuning range through four-wave mixing (FWM) in a SOA. This result is a significant improvement of both the conversion efficiency and the SNR as compared with the conventional FWM-based wavelength converters. We have also investigated the effect of both input power and wavelength of pump P2 on conversion efficiency and OSNR of the wavelength-converted signals

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 score0.005

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.226
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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicOptical Network TechnologiesFrench-language works237,207