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3D Method-of-Moment Design of Huygens' Metasurfaces

2024· article· en· W4395662114 on OpenAlexaff
Tianke Qiu, Vasileios G. Ataloglou, George V. Eleftheriades

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsElectrical impedanceDielectricLossless compressionMoment (physics)Method of moments (probability theory)ElectromagneticsElectromagnetic fieldPhysicsAcousticsMathematical analysisOpticsComputer scienceMathematicsClassical mechanicsOptoelectronicsAlgorithm

Abstract

fetched live from OpenAlex

Electromagnetic metasurfaces (MTSs) are often assumed to be passive and lossless, and can be modeled as purely reactive homogenized impedance sheets on dielectric substrates. In this paper, a 3-D design procedure for reflective metasurfaces based on the integral equation method and impedance boundary conditions is presented. The metasurface consists of impedance sheets placed on top of a grounded dielectric slab, and the impedance values are optimized to match certain far-field (FF) power patterns or to beamform using the gradient-descent method.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.234
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.290
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations2
Published2024
Admission routes1
Has abstractyes

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