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Record W4324322785 · doi:10.1117/12.2646895

Full vectorial analysis of surface relief VCSEL

2023· article· en· W4324322785 on OpenAlexaff
A. I. Nashed, Michel Lestrade, Zhengnan LI, Z. M. Simon Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsCrosslight Software (Canada)
Fundersnot available
KeywordsVertical-cavity surface-emitting laserMaterials scienceLayer (electronics)LaserSurface (topology)OxideOptoelectronicsOpticsField (mathematics)PhysicsComposite materialGeometry

Abstract

fetched live from OpenAlex

The performance of the oxide-confined surface relief (SR) structure vertical-cavity surface-emitting laser (VCSEL) is simulated and analyzed by using the Finite Difference Frequency Domain (FDFD) microcavity model available in the PICS3D simulation package. Using the full vectorial microcavity model enables an accurate analysis of both the dominant and higher order modes, thus more insight into the cavity structural parameters can be investigated. In this proceeding, the impact of the oxide layer and the SR layer on both the emitting laser as well as the far field characteristics is investigated. The simulated Surface Relief (SR) VCSEL shows a threshold current increase to 1.2mA compared to 1.0mA without the SR layer, and far field divergent angles decrease to almost 10°.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.524

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 integrity0.0000.000
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 head0.012
GPT teacher head0.227
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2023
Admission routes1
Has abstractyes

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