Sensitivity Analysis With Full-Wave Electromagnetic Solvers Based on Structured Grids
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Bibliographic record
Abstract
Recently, we proposed a novel technique for design sensitivity analysis of high-frequency structures with respect to localized perturbations in conductive parameters. Here, we generalize the technique to include shape and material variations and utilize the response sensitivities in gradient-based optimization. Our technique belongs to the class of adjoint-variable methods. Thus, it computes the response and its gradient with only two electromagnetic (EM) simulations-of the original and the adjoint problems-regardless of the number of design parameters. For the first time, adjoint sensitivities with respect to conductive, dielectric-magnetic material and shape perturbations are computed via EM solvers on structured grids. Our approximate sensitivity analysis does not require analytical derivatives of the system matrix. This makes the technique versatile and easy to implement. The technique defaults to exact sensitivities with analytical system matrix derivatives when global design parameters are being perturbed. We discuss the accuracy of the approximate sensitivities, as well as the practicality of the exact sensitivities in specific design problems. We also discuss implementations in gradient-based optimization and illustrate them through simulation and design with the frequency domain transmission line method (FD-TLM).
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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 | 0.002 |
| 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.
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