ASIC-Enabled Programmable Metasurfaces—Part 1: Design and Characterization
Bibliographic record
Abstract
A multifunctional and reconfigurable programmable metasurface (PMSF) is presented in this work that is enabled by an application-specific integrated circuit (ASIC). The enabling ASIC integrates control, digital-to-analog converters, and loading elements (LEs) to programmatically alter the response of the PMSF unit cells while minimizing power consumption and cost. These programmable unit cells subsequently comprise a larger PMSF that provides control of the reflected magnitude and phase for a given incident wave for both transverse electric (TE) and transverse magnetic (TM) polarizations. With this ability, the reflected wave can be set to zero, and both polarizations can be perfectly absorbed simultaneously and independently up to oblique angles of incidence of 60° for TE polarization and 70° for TM polarization. The PMSF finds applications in smart wireless environments by providing the capability to redirect incident waves in a programmable manner, while also enabling the perfect absorption of incident interfering waves and programmatically synthesizing complex and polarization agile wavefronts. The accompanying article, Part 2, focuses on the wavefront synthesis and performance, while in this article, the design and characterization are presented.
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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 | 0.000 |
| 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".