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Perfect anomalous reflection with an aggressively discretized Huygens' metasurface

2017· preprint· en· W2625895779 on OpenAlexaff
Alex M. H. Wong, George V. Eleftheriades

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiscretizationReflection (computer programming)PhysicsPower (physics)Electrical impedanceBinary numberOpticsPlane (geometry)Computer scienceMathematical analysisMathematicsGeometryQuantum mechanics

Abstract

fetched live from OpenAlex

This paper investigates the discretization of a periodic metasurface and demonstrates how such a surface can achieve perfect anomalous reflection. Whilst most contemporary theoretical works on metasurfaces deal with continuous current or impedance distributions, we examine how discretization affects a metasurface, and show that in some cases one can discretize a metasurface aggressively - to the extent of having only two cells per spatial period. Such aggressive discretization can lead to great simplifications in metasurface design, and perhaps more surprisingly, a possible performance improvement from continuous metasurfaces. Using this aggressive discretization technique, we report the design of a binary Huygens' metasurface which reflects an incident plane wave at 50° into a reflected direction of -22.5°. Full-wave electromagnetic simulation shows the achievement of anomalous reflection with a power efficiency of 99.1%, which dramatically surpasses the performance of a corresponding passive continuous metasurface, for which the power efficiency is fundamentally limited to 69.6%.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.052
GPT teacher head0.330
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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