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Directional Local Density of States of Classical and Quantum Propagating Surface Plasmons

2017· article· en· W2582106147 on OpenAlexfundno aff
Martin Berthel, Quanbo Jiang, Aline Pham, J. Bellessa, Cyriaque Genet, S. Huant, Aurélien Drezet

Bibliographic record

VenuePhysical Review Applied · 2017
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsnot available
FundersOntario Ministry of Research, Innovation and ScienceAgence Nationale de la RechercheEquipex
KeywordsPhysicsPlasmonSurface plasmonQuantumCoupling (piping)Local density of statesQuantum opticsQuantum imagingOptoelectronicsOpticsQuantum mechanicsQuantum technologyOpen quantum systemMaterials science

Abstract

fetched live from OpenAlex

Surface plasmons (SPs) are key excitations for manipulating light in two dimensions, as in integrated optical circuits on chips. Here the authors show how to filter, in selected directions, the signal due to SP motion in a collimating device. Considering both the classical and quantum optical regimes, they interpret their findings in terms of a propagative electromagnetic local density of states. This approach could also be used in other quantum-technology contexts, $e.g.$ to optimize the coupling efficiency of quantum emitters.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.286
Teacher spread0.266 · 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 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

Citations8
Published2017
Admission routes1
Has abstractyes

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