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Record W3005182630 · doi:10.1038/s41598-020-58706-z

Active Cloaking of a Non-Uniform Scatterer

2020· article· en· W3005182630 on OpenAlexafffund
Paris Ang, George V. Eleftheriades

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCloakCloakingOpticsScatteringConformal mapPhysicsBandwidth (computing)Oblique caseComputer scienceElectromagnetic radiationRadar cross-sectionAcousticsMetamaterialGeometryTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

An object illuminated by an electromagnetic wave can be actively cloaked using a surface conformal array of radiating sources to cancel out scattering. This method is promising as elementary antennas can be used as sources while its active nature can surpass passivity-based performance limitations. While this technique has been conceptually extended to accommodate complex geometries, experimental validation past simple uniform scatterers is lacking. To address this scarcity, the design and experimental demonstration of a low-profile, active cloak capable of concealing a complex, metallic, polygonal target is presented. This cloak is constructed with commercially available monopoles and enclosed within a parallel-plate waveguide-based apparatus to approximate a quasi-2D environment. Performance is then assessed when the target is illuminated at either frontal or oblique incidence by a 1.2 GHz cylindrical wave. Overall, the cloak reduces the target's scattering cross-section by an average of 7.2 dB at frontal incidence and 8.6 dB at oblique incidence. These results demonstrate the feasibility of this kind of active cloaking for more complex scatterers containing flat surfaces and edges. Further analysis shows that the cloak possesses a functional bandwidth of 14% and can be reconfigured for single frequency operation over 0.8-1.8 GHz.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.026
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.031
GPT teacher head0.276
Teacher spread0.245 · 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

Citations17
Published2020
Admission routes2
Has abstractyes

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