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Record W2998892499 · doi:10.1109/jstqe.2019.2958933

Opto-Mechanical Interactions in Multi-Core Optical Fibers and Their Applications

2019· article· en· W2998892499 on OpenAlexfundno aff
Hilel Hagai Diamandi, Yosef London, Arik Bergman, Gil Bashan, Javier Madrigal, David Barrera, Salvador Sales, Avi Zadok

Bibliographic record

VenueIEEE Journal of Selected Topics in Quantum Electronics · 2019
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsnot available
FundersH2020 European Research CouncilAzrieli FoundationUniversitat Politècnica de ValènciaHorizon 2020 Framework ProgrammeMinisterio de Ciencia e InnovaciónMinisterio de Economía y Competitividad
KeywordsCladding (metalworking)Optical fiberOpticsCross-phase modulationMaterials scienceAcoustic waveModulation (music)Optical powerPhase modulationOptoelectronicsPhysicsAcousticsPhase noise

Abstract

fetched live from OpenAlex

Optical fibers containing multiple cores are being developed towards capacity enhancement in space-division multiplexed optical communication networks. In many cases, the fibers are designed for negligible direct coupling of optical power among the cores. The cores remain, however, embedded in a single, mechanically-unified cladding. Elastic (or acoustic) modes supported by the fiber cladding geometry are in overlap with multiple cores. Acoustic waves may be stimulated by light in any core through electrostriction. Once excited, the acoustic waves may induce photo-elastic perturbations to optical waves in other cores as well. Such opto-mechanical coupling gives rise to inter-core cross-phase modulation effects, even when direct optical crosstalk is very weak. The cross-phase modulation spectrum reaches hundreds of megahertz frequencies. It may consist of discrete and narrow peaks, or may become quasi-continuous, depending on the geometric layout. The magnitude of the effect at the resonance frequencies is comparable with that of intra-core cross-phase modulation due to Kerr nonlinearity. Two potential applications are demonstrated: single-frequency opto-electronic oscillators that do not require radio-frequency electrical filters, and point-sensing of liquids outside the cladding of multi-core fibers, where light cannot reach.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.544

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 integrity0.0000.001
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 head0.017
GPT teacher head0.265
Teacher spread0.249 · 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 designSimulation or modeling
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

Citations17
Published2019
Admission routes1
Has abstractyes

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