Time-Domain Analysis of Temporally and Spatially Dispersive Metasurfaces in GSTC-FDTD Frameworks
Bibliographic record
Abstract
In this paper, we propose two different methods for time-domain finite-difference analysis of uniform temporally and spatially dispersive metasurfaces using their zero thickness sheet representations using the Generalized Sheet Transition Conditions (GSTCs). Metasurfaces are described here using their effective surface susceptibilities which are assumed to exhibit Lorentzian temporal dispersion characteristics. For both methods, the spatial dispersion of the, the surface susceptibilities (i.e., their dependence on angle of incidence) are represented using the extended GSTCs presented in [1]-[3]. However, the first method takes advantage of a polynomial expansion of the angle-dependent surface susceptibilities in terms of the transverse wavevector to implement spatial derivatives of the electric and magnetic polarization as well as the average field on the surface, leading to a coupled set of field equations encompassing the entire surface. Limitations for this method are presented in terms of poor conditioning for a coupled system of equations and an inconvenient extension to the higher-order expansion of the susceptibility terms. The second method lifts these limitations by solving the spatial dispersion problem in the spatial frequency domain at every time step. Both methods are validated for custom Lorentzian models and two canonical physical cells while comparing their transmission and reflection coefficients with analytical results.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".