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Record W2007571237 · doi:10.1109/tmtt.2012.2224670

A Spatially Filtered Finite-Difference Time-Domain Scheme With Controllable Stability Beyond the CFL Limit: Theory and Applications

2012· article· en· W2007571237 on OpenAlexaff
Chun Chang, Costas D. Sarris

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2012
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinite-difference time-domain methodLimit (mathematics)Stability (learning theory)HarmonicsComputational electromagneticsFilter (signal processing)Finite difference methodMathematicsElectromagnetic fieldElectronic engineeringComputer scienceMathematical analysisPhysicsOpticsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

A 3-D finite-difference time-domain (FDTD) scheme with controllable stability beyond the stability limit of FDTD is presented. The key to controlling the FDTD stability limit is a spatial filter applied to the electromagnetic field vectors in order to ensure that unstable spatial harmonics are eliminated. A significant advantage of this approach is the simplicity of its incorporation into existing FDTD codes. Moreover, this method is employed as a means to implement a late-time stable 3-D sub-gridding scheme. Applications include waveguide filters and the analysis of screens for near-field sub-wavelength focusing at microwave frequencies.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.230
Teacher spread0.220 · 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
GenreMethods

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

Citations45
Published2012
Admission routes1
Has abstractyes

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