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Record W4387300718 · doi:10.1117/12.2676381

Design and fabrication of resonant grating laser mirrors for single mode emission in microchip lasers

2023· preprint· en· W4387300718 on OpenAlexaff
Ratish Rao Nagaraj Rao, Fangfang Li, Marina Fetisova, Théo Courval, Shawn Lapointe, Thomas Kämpfe, Isabelle Verrier, Yves Jourlin, Petri Karvinen, Markku Kuittinen, Jean‐François Bisson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsLaserFabricationMaterials scienceOptoelectronicsGratingOpticsSemiconductor laser theorySingle-mode optical fiberMode (computer interface)PhysicsComputer science

Abstract

fetched live from OpenAlex

Two laser mirrors with a Bragg mirrors and diffraction grating were designed to achieve single-mode emission. At normal incidence, the reflected transverse electric (TE) and transverse magnetic (TM) polarized beams exhibit a phase difference near π and, in the case of the output coupler, a difference in the reflected amplitude. Laser mirrors with suitably adjusted di-attenuation and di-retardance can be used to achieve single-mode emission of a microchip laser without additional intracavity elements by canceling axial hole burning and suppressing the undesired competing polarization eigenstate. An integrated microchip laser design is also presented to support the potential of delivering a monolithic and compact solution for single-mode emission.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.075
GPT teacher head0.285
Teacher spread0.210 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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