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Record W3208450443 · doi:10.1364/ol.438484

Spin-orbit-enabled sorting of optical flows in plasmonic nanocircuits

2021· article· en· W3208450443 on OpenAlexaff
Youqiao Ma, Chengkai Jiang, Kaili Sun, Bo Liu, Jinhua Li, Zhanghua Han, Xin Hu, Yuan Ma

Bibliographic record

VenueOptics Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsDalhousie University
FundersStartup Foundation for Introducing Talent of Nanjing University of Information Science and TechnologyNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsNanoringNanophotonicsPlasmonOpticsWaveguideSpin (aerodynamics)Extinction ratioSurface plasmonPhysicsSortingPhotonChirality (physics)OptoelectronicsFano resonanceMaterials scienceQuantum mechanicsSymmetry breaking

Abstract

fetched live from OpenAlex

On-chip controlling of photon spin is essential in developing future integrated nanophotonics with complex functionalities. Here we propose and demonstrate a robust spin-sorting nanocircuit, which consists of a spin-orbit coupler (i.e., combined nanoring and nanodisk) and an L-shaped dielectric-loaded surface plasmon (DLSPs) waveguide. The nanocircuit with optimized geometric parameters is shown to be capable of unidirectionally exciting and routing a DLSP mode along an independent waveguide. We found experimentally that the proposed device possesses an average insertion loss (extinction ratio) of 0.13 dB (14.8 dB) under complete circularly polarized incidence with opposite spin, which is in good agreement with theoretical calculations. The proposed spin-selective scheme may pave the way for applications in the manipulation of chirality with a flexible degree of freedom.

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 score0.003

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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