Performance Evaluation of a Fractal Plasmonic Bowtie Nano-Antenna: Optical and Far-Field Properties
Bibliographic record
Abstract
In the nano-antenna framework, in this work, we have proposed a fractal plasmonic bowtie nano-antenna (FPBNA) with three wings to maximize the coupling between higher and lower order modes. Hollow cavities of the bowtie nano-antenna support hybridization modes, both anti-bonding and bonding modes. In other words, the blue-shift in the hybridization modes results from an increase in the Sierpiński fractal iteration, which facilitates the minimization of hollow regions in fractals after each iteration. We have investigated both near-and-far field characteristics of the proposed FPBNA. We have investigated both near-and-far field characteristics of the proposed FPBNA. We have demonstrated that the near-field intensity of the FPBNA is tunable and adjustable by modifying geometrical and electromagnetic parameters and the incident wave. Furthermore, the FPBNA exhibits superior performance in terms of polarization independency, absorptance, and robustness against losses, compared to other available bowtie nano-antenna structures. In the far-field region, the FPBNA possesses very low-radiative characteristics, in the order of$10^{-7}$dB, as well as robustness to a variation of$\phi$angles.
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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".