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Record W2087552607 · doi:10.1364/ipr.2002.ithi8

Comprehensive Modeling of Semiconductor Lasers Including the Effect of Gain Saturation

2002· article· en· W2087552607 on OpenAlexaff
Samy Ghoniemy, Leonard MacEachern, S. Mahmoud

Bibliographic record

VenueIntegrated Photonics Research · 2002
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsCarleton University
Fundersnot available
KeywordsLaserSemiconductor laser theoryGainRate equationLinearityModulation (music)Laser diode rate equationsMaterials scienceOpticsLaser diodeSaturation (graph theory)Fabry–Pérot interferometerSemiconductor optical gainDiodeOptoelectronicsElectronic engineeringPhysicsLaser power scalingMathematicsActive laser mediumInjection seederEngineeringAcoustics

Abstract

fetched live from OpenAlex

Fabry-Perot laser diode models incorporating spectral hole burning and index non-linearity in a modified gain formulation are discussed. Modified rate equations based on the proposed modified gain formula are presented. Symbolically Defined Devices (SDD) implemented in a commercial simulator are constructed using modified rate equations. Simulated laser modulation response characteristics are obtained with the SDD implementation. Predicted modulation response curves obtained using the modified gain formulation correctly predict laser modulation characteristics for higher laser bias levels, in contrast to results obtained using conventional non-modified gain formulations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.106
GPT teacher head0.334
Teacher spread0.228 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations6
Published2002
Admission routes1
Has abstractyes

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