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Record W2041633280 · doi:10.1117/12.384393

<title>Transverse modal characterization of VCSELs based on intensity measurement</title>

2000· article· en· W2041633280 on OpenAlexaff
Xin Xue, Andrew G. Kirk

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsMcGill University
Fundersnot available
KeywordsOpticsPhysicsSuperposition principleLaser beam qualityBeam (structure)Transverse planeIntensity (physics)Fourier transformLaserLaser beams

Abstract

fetched live from OpenAlex

In many VCSEL applications, it is essential to know the transverse beam characteristics. This paper reports an experiment of transverse modal characterization based on intensity measurement. The beam form a VCSEL is imaged by a microscope objective and intensity profiles are recorded by scanning an apertured detector. The second moment of the intensity profile is found to vary quadratically with the distance along the direction of beam propagation. An effective Rayleigh range is extracted by means of quadratic data fitting. Once this parameter is obtained, Fourier analysis of one intensity profile yields the relative weights of the Hermite-Gaussian (HG) modes, provided that the beam is indeed a superposition of independent HG modes. It is found that a VCSEL driven at low current generates a beam that is approximately HG or a superposition of independent HG modes. At high drive current, however, the transverse modal structure becomes more complicated. The experiment demonstrates that intensity-based Fourier analysis is a convenient method to assess the closeness of approximating the outputs form semiconductor lasers by superposition of independent HG modes without using sophisticated spatial modal filters. The experiment also measures the M<SUP>2</SUP> modes without using sophisticated spatial modal filters. The experiment also measures the M<SUP>2</SUP> parameter of beam quality versus the drive current.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicSemiconductor Lasers and Optical DevicesFrench-language works237,207