Spatially dispersive dichroism in bianisotropic metamirrors
Bibliographic record
Abstract
Dichroism refers to the differential absorption of a material for different polarized waves and has important applications in polarimetry and optical wavefront manipulation. The coexistence of strong linear and circular dichroism at thin optical interfaces is usually challenging due to the weak chiral anisotropy in natural materials. Here, we investigate the spatially dispersive dichroism of bianisotropic metamirror, in which giant linear and circular dichroism can be achieved simultaneously. By covering the metallic mirror with an array of bianisotropic resonators, specific linearly and circularly polarized waves can be largely absorbed under normal and oblique incidences, respectively. This intriguing phenomenon is attributed to the anisotropic magneto-electric coupling, that is, the handedness and the strength of the equivalent transverse electric surface current are determined by the angle of incidence. Furthermore, dual-band and hybrid-chirality metamirrors for asymmetric spin reflection have been realized by adjusting the geometries and arrangement of the bianisotropic resonators. The overall thickness of the bianisotropic metamirror is only 1/50 of the wavelength and thus highly suitable for on-chip integration. Our findings may provide an alternative approach towards multifunctional optical mirrors, signal detectors, chiral imaging devices, and molecular analyzers.
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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) | 0.000 | 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".