Sensitivity analysis of network parameters with electromagnetic frequency-domain simulators
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Bibliographic record
Abstract
A new practical approach to sensitivity analysis of the network parameters of high-frequency structures with commercial full-wave electromagnetic (EM) solvers is proposed. We show that the computation of the linear-network parameter derivatives in the design-parameter space does not require an adjoint-problem solution. The sensitivities are computed outside the EM solver, which simplifies the implementation. We discuss: 1) features of commercial EM solvers which allow the user to compute network parameters and their sensitivities through a single full-wave simulation; 2) the accuracy of the computed derivatives; and 3) the overhead of the sensitivity computation. Through examples based on FEMLAB and FEKO simulations, comparisons are made with the forward finite-difference derivative estimates in terms of accuracy and CPU time.
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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 | 0.000 | 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)
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.
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