Power Balance Regularization of the Microwave Inverse Scattering Problem
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Bibliographic record
Abstract
The incorporation of a priori information is required to regularize the ill-posed microwave scattering problem associated with microwave tomography (MWT). A new physics-informed regularization technique using electromagnetic power balance is introduced. The method does not require the ad hoc specification of the regularization parameter. The technique is demonstrated on in silico synthetic data, as well as previously reported measurements for simple lossless dielectrics in free space, and in vivo measurements of human forearms in a lossy matching medium. In the lossless imaging scenario, the power balance regularization (PBR) technique produces similar results to the well-known truncated conjugate gradient (TCG) and total variation multiplicative regularizer (TVMR). However, for biomedical measurements, the results are markedly different with the reconstructed images demonstrating significantly higher contrast, more accurate property estimation for high contrast inclusions, and successful resolution of inclusions in the imaginary permittivity. The PBR technique can be easily added to conventional microwave imaging algorithms and suggests other physics-informed regularization schemes could be used in future work.
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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 | 0.000 |
| 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