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Record W2961132564 · doi:10.5539/apr.v11n4p1

A Novel Theory for the Scattering of P-Polarized Hermite-Gaussian Electromagnetic Beams by a Double Metallic Nano-Slit

2019· article· en· W2961132564 on OpenAlexvenueno aff
I. Guzman-Montano, G. Montiel-González, J. Sumaya-Martínez, P. Rosendo‐Francisco, Juan Reyes-Gómez

Bibliographic record

VenueApplied Physics Research · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrbital Angular Momentum in Optics
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsDiffractionOpticsWavelengthGaussianScalar (mathematics)Polarization (electrochemistry)Hermite polynomialsScatteringLambdaGaussian beamBeam (structure)Quantum mechanicsGeometry

Abstract

fetched live from OpenAlex

We present a rigorous theory for oblique incident Hermite-Gaussian beams, diffracted by two optical nano-slits of width l and separation d, in a thick metallic screen for the case of polarization TM (P). The far field spectra as a function of several opto-geometrical parameters, wavelength λ , slit width l, separation d , incidence angle θi and Hermite order m is analyzed. In the vectorial diffraction region given when λ /l >0.2, where l is the incident wavelength and as a function of the separation between slits d; we have numerically analyzed: the far field spectra, the energy diffracted along the incident beam direction Ei , and the validity of an approximate diffraction (scalar) property, namely Ei= Ntao/lambda .

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.300
Teacher spread0.274 · 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 designTheoretical or conceptual
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

Citations0
Published2019
Admission routes1
Has abstractyes

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