Dispersion HIE-SF-FDTD Method for Simulating Graphene-Based Absorber
Bibliographic record
Abstract
This paper presents a novel dispersion hybrid implicit explicit single-field finite-difference time-domain (HIE-SF-FDTD) method which can be effectively used to simulate the graphene-based absorber. The stability condition of the proposed method is relaxed from the spatial mesh sizes along one direction which makes it a robust tool to simulate structures having fine details in one Cartesian direction such as thin graphene sheet. By applying the Crank-Nicolson (CN) scheme only to the electric field and a new time-splitting scheme to the graphene current density, the proposed algorithm is developed. In this method, not alike most of the FDTD algorithms in which both electric and magnetic fields are updated, only the electric field needs to be solved in each iteration. Thanks to the few and simple updating equations of the proposed algorithm, higher computational efficiency in terms of runtime is achieved. The accuracy and computational efficiency of the proposed method are demonstrated through comparison of the results obtained from the methods available in the literature.
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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 | 0.001 | 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) | 0.001 | 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 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".