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Record W3158044885 · doi:10.1364/optica.423833

Widely tunable silicon Raman laser

2021· article· en· W3158044885 on OpenAlex
Mohammad Ahmadi, Wei Shi, Sophie LaRochelle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptica · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaUniversité Laval
KeywordsMaterials scienceRaman laserOptoelectronicsLaserWaferRaman spectroscopyOpticsRaman scatteringLaser power scalingSiliconRaman amplificationWavelengthSIGNAL (programming language)Computer sciencePhysics

Abstract

fetched live from OpenAlex

Stimulated Raman scattering is an effective means of wavelength conversion and can largely extend the operating spectral range of an optical source. We demonstrate a high-performance tunable Raman laser on a sub-micrometer-thick silicon on insulator wafer using a standard foundry process. The key feature to this laser is the use of a tunable coupling mechanism to adjust both pump and signal coupling coefficients in the ring cavity, allowing demonstration of laser emission over a large wavelength tuning range of 83 nm. This Raman laser demonstrates efficient (slope of up to 26% and a maximum pump-to-signal power conversion efficiency of 10%) on-chip nonlinear wavelength conversion. Our results indicate great promise for substantially increasing the optical spectral resources available on a silicon chip.

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.

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: none
Teacher disagreement score0.539
Threshold uncertainty score0.944

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)0.0010.001

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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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