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Record W2127266781 · doi:10.1109/tmtt.2003.822034

An Adjoint Variable Method for Time-Domain TLM With Wide-Band Johns Matrix Boundaries

2004· article· en· W2127266781 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.

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2004
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClassification of discontinuitiesMatrix (chemical analysis)Transmission-line matrix methodMathematicsTransposeTime domainFunction (biology)Transmission lineComputational electromagneticsMathematical analysisSensitivity (control systems)Adjoint equationDomain (mathematical analysis)AlgorithmApplied mathematicsComputer sciencePhysicsElectromagnetic fieldElectronic engineeringPartial differential equationEngineeringEigenvalues and eigenvectorsTelecommunications

Abstract

fetched live from OpenAlex

We present a novel algorithm for efficient estimation of objective function sensitivities for time-domain transmission-line modeling (TLM) with dispersive Johns matrix boundaries. The original electromagnetic structure is simulated using TLM. An adjoint TLM simulation that runs backward in time is derived and solved. The sensitivities of the objective function with respect to all designable parameters are estimated using only the original and adjoint simulations. We show that the Johns matrix of the adjoint problem at each time step is the transpose of the corresponding matrix for the original structure. Our approach is illustrated through the estimation of the sensitivities of objective functions with respect to the dimensions of waveguide discontinuities. A very good match is obtained between our sensitivity estimates and those obtained using central difference approximation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.302
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.266
Teacher spread0.260 · 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