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Record W2285776047 · doi:10.1109/tap.2015.2510373

An Adjoint Variable Method for Wideband Second-Order Sensitivity Analysis Through FDTD

2015· article· en· W2285776047 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2015
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHessian matrixFinite-difference time-domain methodWidebandSensitivity (control systems)Variable (mathematics)Applied mathematicsFunction (biology)MathematicsAlgorithmProduct (mathematics)Computer scienceMathematical analysisPhysicsElectronic engineeringGeometryOptics

Abstract

fetched live from OpenAlex

We propose an efficient adjoint variable method (AVM) for estimating wideband second-order response sensitivities using the finite-difference time-domain (FDTD) approach. Our AVM approach reduces the number of required simulations for computing the Hessian matrix of the desired objective function from O(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) to only n + 1 where n is the number of designable parameters. All first-order sensitivities are also estimated as a by-product. Our sensitivity technique is illustrated through 1-D, 2-D, and 3-D electromagnetic examples involving both dispersive and nondispersive materials. The accuracy of our AVM approach is verified through comparison with analytical sensitivity results or sensitivities estimated using the accurate but computationally intensive central finite-difference (CFD) approximations.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.716
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.303
Teacher spread0.275 · 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