Electromagnetic Scattering From 3-D Targets in a Random Medium Using Finite Difference Frequency Domain
Bibliographic record
Abstract
In this paper a three-dimensional (3-D) numerical technique based on the finite difference frequency domain (FDFD) is implemented to calculate the scattering from arbitrary shaped objects embedded in a continuous random medium. The total field/scattered field (TF/SF) algorithm is integrated with the FDFD to minimize the memory consumption and speed up the calculations. For validation purposes, the radar cross-section of a 2-D conducting cylinder in random medium is calculated using the FDFD technique and compared to previously published data based on the current generator method. An upgrade to a 3-D solver was then inspired once the idea of using the multi-grid technique was introduced to accelerate the convergence rate of the BICGSTAB iterative solver. Thus, allowing the FDFD technique to become a robust method to solve the scattering problem from large targets embedded in random medium. Therefore, using the introduced simulating scheme, one can easily elucidate any scattering information out of real life targets surrounded by random environmental effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".