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Record W3023215387 · doi:10.1364/ol.394719

Parity–time-symmetric frequency-tunable optoelectronic oscillator with a single dual-polarization optical loop

2020· article· en· W3023215387 on OpenAlexafffund
Peng Li, Zheng Dai, Zhiqiang Fan, Lianshan Yan, Jianping Yao

Bibliographic record

VenueOptics Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Mechanics and Non-Hermitian Physics
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsPhase noiseFiber Bragg gratingPassbandPolarization (electrochemistry)BirefringenceMicrowaveOptoelectronicsLithium niobateMaterials sciencePhysicsOptical filterOptical fiberBand-pass filter

Abstract

fetched live from OpenAlex

We propose and experimentally demonstrate a parity–time (PT)-symmetric frequency-tunable optoelectronic oscillator (OEO) in which the PT symmetry is implemented based on a single dual-polarization optical loop. By employing the inherent birefringence of a z-cut lithium niobate ( L i N b O 3 ) phase modulator (PM), two mutually coupled optoelectronic loops supporting orthogonally polarized light waves with one experiencing a gain and the other a loss are implemented. By controlling the gain, loss, and the coupling coefficients between the two loops, the PT symmetry breaking condition is met, which enables the OEO to operate in single mode without using an ultranarrow passband optical or microwave filter. The frequency tunability is realized using a microwave photonic filter (MPF) implemented using the PM and a phase-shifted fiber Bragg grating (PS-FBG). The proposed PT-symmetric OEO is experimentally evaluated. A stable and frequency-tunable microwave signal from 2 to 12 GHz is generated. The phase noise of the generated signal at 11.8 GHz is measured, which is − 124 d B c / H z at a frequency offset of 10 kHz.

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 score0.001
Threshold uncertainty score0.005

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations40
Published2020
Admission routes2
Has abstractyes

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