Composite right/left‐handed extended equivalent circuit (CRLH‐EEC) FDTD: stability and dispersion analysis with examples
Bibliographic record
Abstract
Abstract A composite right/left‐handed (CRLH) extended equivalent circuit (EEC) FDTD method with a stability criterion based on a Liapunov discrete energy function is presented and applied to investigate several transient and refractive phenomena occurring at the interface between a CRLH metamaterial (MTM) and a purely right‐handed (PRH) structure. This formulation consists in an extension of the equivalent circuit (EC) Yee scheme including a left‐handed (LH) series capacitance and shunt inductance in addition to the canonical right‐handed (RH) series inductance and shunt capacitance, so as to model general CRLH transmission line (TL) MTMs. This CRLH‐EEC FDTD scheme is shown to represent a convenient numerical scheme, with remarkable formulation compactness and high computational efficiency, for the analysis of any type of MTM structure. Moreover, this scheme, coupled with a Y‐matrix representation of the EEC Yee cell, is shown to rigorously restore the dispersion/attenuation relation of CRLH MTMs. Transient solutions for the propagation of a modulated Gaussian pulse through a PRH–CRLH interface highlights interesting effects such as space‐domain compression, infinite phase velocity modulation and the well‐known backward wave effect. Frequency‐domain analysis of the fields radiated by dipoles through the Veselago–Pendry lens shows how focusing is affected both qualitatively and quantitatively by the orientation of the dipoles. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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 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".