Pseudo-Random Sequence (PRS) (Space)Time-Modulated Metasurfaces
Bibliographic record
Abstract
This paper presents a novel class of (space)time-modulated metasurfaces, namely (space)time metasurfaces that are modulated by pseudo-random sequence (PRS) waveforms. In contrast to their harmonically or quasi-harmonically modulated counterparts, these metasurfaces massively alter the temporal spectrum of the waves that they process; as a result, they exhibit distinct properties and offer complementary applications. These metasurfaces are assumed here to operate in the `slow-modulation' regime, where the fixed-state time between state-transition is much larger than the transient time associated with the dispersion of the media involved, which allows safe separation of the time-variance and frequency-dispersive effects of the system. Thanks to the special properties of their modulation, which are generally assumed to have a staircase shape and to be periodic in addition to being pseudo-random, the PRS (space)time-modulated metasurfaces can perform a number of unique operations, such as spectrum spreading, interference suppression, and row/cell selection. These properties, combined with modern microwave CMOS technologies, lead to applications with unique performance or/and features, such as electromagnetic stealth, secured communication, direction of arrival estimation, and spatial multiplexing.
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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".