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Record W4386472788 · doi:10.1109/jphot.2023.3312388

Output Optical Power Enhancement of Push-Pull Modulated DFB Laser With Asymmetric Structure

2023· article· en· W4386472788 on OpenAlexaff
Jiewen Chi, Xun Li, Chuanning Niu, Jia Zhao

Bibliographic record

VenueIEEE photonics journal · 2023
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIntensity modulationLaserMaterials scienceDistributed feedback laserOptoelectronicsOpticsBandwidth (computing)Modulation (music)Optical powerSemiconductor laser theoryComputer sciencePhysicsTelecommunicationsPhase modulationAcoustics

Abstract

fetched live from OpenAlex

Conventional push-pull modulated (PPM) distributed feedback (DFB) lasers exploit structures with symmetry, which wastes a significant amount of the optical power output from the rear facet. To improve the power efficiency, PPM DFB lasers with asymmetrically coated facets can be considered. However, the resulted imbalanced push-pull modulation causes a dip in device small-signal intensity modulation response near the carrier-photon resonance (CPR) frequency, which distorts the waveform and even cuts off the bandwidth. This work proposes an asymmetric section length design in conjunction with the asymmetric facet coating to offset the aforementioned effect on device intensity modulation response. With a delayed push-pull modulation (DPPM) scheme further incorporated, our simulation result shows that the PPM DFB laser with optimized asymmetric structure can enhance the power efficiency and maintain a smooth modulation bandwidth up to around 50 GHz.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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