Pure and Linear Frequency Converter Temporal Metasurface
Bibliographic record
Abstract
Abstract Metasurfaces are ultrathin structures which are constituted by an array of subwavelength scatterers with designable scattering responses. They have opened up unprecedented exciting opportunities for extraordinary wave engineering processes. On the other hand, frequency converters have drawn wide attention due to their vital applications in telecommunication systems, health care devices, radio astronomy, military radars and biological sensing systems. Here, we show that a spurious-free and linear frequency converter metasurface can be realized by leveraging unique properties of engineered transmissive temporal supercells. Such a metasurface is formed by time-modulated supercells; themselves are composed of temporal and static patch resonators and phase shifters. This represents the first frequency converter metasurface possessing large frequency conversion ratio with controllable frequency bands and transmission magnitude. In contrast to conventional nonlinear mixers, the proposed temporal frequency converter offers a linear response. In addition, by taking advantage of the proposed surface-interconnector-phaser-surface (SIPS) architecture, a spurious-free and linear frequency conversion is achievable, where all undesired mixing products are strongly suppressed. The proposed metasurface may be digitally controlled and programmed through a field programmable gate array. This makes the spurious-free and linear frequency converter metasurface a prominent solution for wireless and satellite telecommunication systems, as well as invisibility cloaks and radars. This study opens a way to realize more complicated and enhanced-efficiency spectrum-changing metasurface.
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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) | 0.002 | 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".