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Record W2063589362 · doi:10.1063/1.1321778

Low-frequency electrical noise of high-speed, high-performance 1.3 μm strained multiquantum well gain-coupled distributed feedback lasers

2000· article· en· W2063589362 on OpenAlexafffund
Xuyuan Chen, M. Jamal Deen, Chuan Peng

Bibliographic record

VenueJournal of Applied Physics · 2000
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNoise (video)LaserOptoelectronicsQuantum wellInfrasoundSemiconductor laser theoryMaterials scienceWavelengthCurrent (fluid)PhysicsSemiconductorOpticsAcoustics

Abstract

fetched live from OpenAlex

Measurements of low-frequency electrical noise (LFN) in an in-phase gain-coupled distributed feedback lasers with etched quantum-well active-layers emitting at 1.3 μm wavelength have been conducted. In particular, the injected current dependence of LFN is investigated over a wide range of injection current (from 10−2 μA to 60 mA). Pure 1/f noise spectra were observed in all measurements. The current dependence of the 1/f noise strongly correlates to the I–V characteristics. We find that noise from different mechanisms dominates when the lasers operate in different ranges of injection currents.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations6
Published2000
Admission routes2
Has abstractyes

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