Efficient Jacobian computation for high-frequency inverse problem solutions
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Bibliographic record
Abstract
Response Jacobians (gradients) can significantly improve the convergence of the reconstruction algorithms used in inverse problem solutions. However, the lack of efficient methods for computing response Jacobians has limited the applications of gradient-based algorithms to inverse problems when 3D numerical electromagnetic (EM) forward solvers are used. In this paper, we present the most recent developments in the self-adjoint sensitivity analysis (SASA) method for the computation of the response Jacobians with time-domain EM solvers. To our knowledge, our approach is the most computationally efficient method for EM sensitivity analysis with time-varying field solutions. It can deal with all types of optimizable (model) parameters, material parameters and shape parameters, of both dielectric and conducting objects in the structure of interest. Verification is carried out through the analysis of lossy dielectric structures. (5 pages)
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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