Efficient leaky-wave antennas at terahertz frequencies generating highly directional beams
Bibliographic record
Abstract
Due to their frequency-dependent angular emission, leaky-wave antennas have been recently introduced in the terahertz band to tackle many of the challenges associated with THz wireless communications. Most previous works have exploited conventional leaky-wave waveguide architectures developed for the microwave region. In this paper, we study in detail the emission characteristics of leaky-wave antennas at THz frequencies. We show that, at these high frequencies, the wavelength-scale interaction with the aperture causes a nonuniform electric field distribution at the slot interface, which is a unique regime that is not typically encountered at lower frequencies. This effect is even more pronounced as the slot width increases to a point where the sides of the slot act as secondary leaking structures, and the well-known frequency–angle relationship is not obeyed as the energy at a given frequency is radiated in a broad range of angles. Therefore, to exploit the phase matching condition, which couples frequency to emission angle, one must use very thin rectangular slots d≪λ, at the expense of device efficiency. To address this problem, we explore an alternate slot aperture design, in which the slot width increases linearly along its length (i.e., a trapezoidal shape). We show that this preserves the phase-matching constraint while allowing higher output coupling efficiencies. Moreover, since a wider effective aperture is used, the radiated beam is narrow in both angular directions, allowing the generation of true pencil-like THz beams.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".