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Record W2109072449 · doi:10.1364/josaa.29.002444

Electromagnetic scattering from finite and infinite array of two-dimensional overfilled cavities in a conductive surface using a hybrid finite element surface integral equation method

2012· article· en· W2109072449 on OpenAlexaff
Babak Alavikia, Omar M. Ramahi

Bibliographic record

VenueJournal of the Optical Society of America A · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFinite element methodBoundary (topology)Mathematical analysisIntegral equationBoundary value problemScatteringSurface (topology)Boundary element methodMathematicsPhysicsGeometryOptics

Abstract

fetched live from OpenAlex

This work presents a hybrid finite element boundary integral algorithm to solve the problem of scattering from finite and infinite arrays of two-dimensional overfilled cavities engraved in a perfectly electric conducting flat screen. The solution region is divided into interior regions containing the cavities and their protruding portions, and the region exterior to the overfilled cavities. The finite element formulation is applied only inside the interior regions to derive a linear system of equations associated with field unknowns. Using two-boundary formulation, the surface integral equation employing the half-space Green's function is applied on the boundary located at the interface of protruding portions of the cavities and the half-space as a boundary constraint to truncate the solution region. Placing the truncation boundary on the protruding portions of the cavities results in highly efficient solution in terms of computational resources, which makes the algorithm well suited for the optimization problems involving scattering from grating surfaces. The near fields are generated for finite and infinite arrays of overfilled cavities with different dimensions.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.275
Teacher spread0.257 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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