Adjoint EM Sensitivity Analysis for Fast Frequency Sweep Using Matrix Padé via Lanczos Technique Based on Finite-Element Method
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Bibliographic record
Abstract
Sensitivity analysis is important for electromagnetic (EM)-based design. The existing adjoint EM sensitivity analysis methods have to solve large systems of EM equations repetitively for different frequencies. This article addresses this situation and proposes to speed up the EM sensitivity analysis over a frequency range by solving EM equations at only a single frequency. A new adjoint EM sensitivity analysis algorithm for the fast frequency sweep using the matrix Padé via Lanczos (MPVL) technique based on the finite-element method (FEM) is proposed in this article. MPVL is incorporated to relate the information of one frequency to the information of multiple frequencies. A large system of EM equations is then solved at a single frequency to predict the sensitivity information for the entire frequency band. Adjoint formulations are further derived to avoid the effect of the number of design variables. The adjoint EM sensitivity analysis using the proposed technique can obtain the same accuracy as the existing techniques while taking less time by avoiding repetitively solving large systems of EM equations for different frequencies and different design variables. The proposed technique is demonstrated by three EM examples of microwave components.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it