Neuro-TF Surrogate Model Optimization of Third-Order Waveguide Filter Based on Complex Frequency Domain EM Simulation
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Bibliographic record
Abstract
This paper introduces a CFD-based neuro-TF surrogate model and demonstrates its application in optimizing a third-order waveguide filter. The method employs a rapid frequency sweep technique for CFD electromagnetic simulation and integrates an innovative zero/pole extraction technique based on S-parameter magnitude to construct a high-precision NeuroTF surrogate model. Compared to traditional vector fitting methods, this model demonstrates significant advantages in the range of geometric parameters, effectively enhancing optimization efficiency. Experimental results show that the optimization method based on this surrogate model can quickly obtain structural parameters for third-order waveguide filter that meet design specifications, verifying the method's effectiveness and practicality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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