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Record W2588902211 · doi:10.1117/12.2252840

Nonlinear optical modulation in a plasmonic Bi:YIG Mach-Zehnder interferometer

2017· article· id· W2588902211 on OpenAlexaff
C. J. Firby, A. Y. Elezzabi

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2017
Typearticle
Languageid
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInterferometryMach–Zehnder interferometerPlasmonOpticsModulation (music)Nonlinear opticsNonlinear systemAstronomical interferometerOptoelectronicsMaterials sciencePhysicsLaserAcoustics

Abstract

fetched live from OpenAlex

In this work, we propose a magnetoplasmonic modulator for nonlinear radio-frequency (RF) modulation of an integrated optical signal. The modulator consists of a plasmonic Mach-Zehnder interferometer (MZI), constructed of the ferrimagnetic garnet, bismuth-substituted yttrium iron garnet (Bi:YIG). The transverse component of the Bi:YIG magnetization induces a nonreciprocal phase shift (NRPS) onto the guided optical mode, which can be actively modulated through external magnetic fields. In an MZI, the modulated phase shift in turn modulates the output optical intensity. Due to the highly nonlinear evolution of the Bi:YIG magnetization, we show that the spectrum of the output modulated intensity signal can contain harmonics of the driving RF field, frequency splitting around the driving frequency, down-conversion, or mixing of multiple RF signals. This device provides a unique mechanism of simultaneously generating a number of modulation frequencies within a single device.

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)0.000
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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicMagneto-Optical Properties and ApplicationsFrench-language works237,207