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Record W4367663487 · doi:10.1109/tmtt.2023.3267537

Modeling of Finite Beams in Periodic FDTD Methods

2023· article· en· W4367663487 on OpenAlexafffund
Aaron J. Kogon, Costas D. Sarris

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFinite-difference time-domain methodParallelizable manifoldPeriodic boundary conditionsGaussianBroadbandFinite difference methodBessel functionGaussian beamBoundary value problemPerfectly matched layerBoundary (topology)Gaussian processGratingBeam (structure)PhysicsComputer scienceOpticsMathematical analysisMathematicsAlgorithm

Abstract

fetched live from OpenAlex

This article presents a finite-difference time-domain (FDTD) framework that accelerates the modeling of the interaction of infinite periodic structures with practical sources (such as Gaussian or Bessel beams) by exploiting periodic boundary conditions (PBCs). The technique involves the introduction of arbitrary beam-generating sources in periodic simulations via the array-scanning method (ASM). The proposed method is both efficient and practical, being naturally broadband and highly parallelizable. We present examples of Gaussian beams in free space and interacting with grating geometries, efficiently replicating the results of multi-period brute-force simulations.

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)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.032
GPT teacher head0.326
Teacher spread0.293 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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