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Record W2291194385 · doi:10.1109/nemo.2015.7415052

A scattering slab and time reversal make a computational superlens

2015· article· en· W2291194385 on OpenAlexaff
W.J.R. Hoefer, P.P.M. So

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsScatteringSuperlensOpticsMetamaterialSlabPhysicsImage resolutionPlanarTime domainNegative refractionLossless compressionComputer scienceAlgorithmComputer visionData compression

Abstract

fetched live from OpenAlex

The similarity of time reversal and negative refraction, as well as the counter-intuitive property of scattering media to enhance image resolution in concert with time reversal, are exploited in this paper to propose and demonstrate an accurate, high-resolution procedure for imaging impulsive electromagnetic point sources using time-domain Transmission Line Matrix (TLM) modeling. A computational planar superlens, made of lossless scattering material rather than of double-negative metamaterial, is shown to image impulsive sources with high temporal and spatial resolution. The field emitted by the sources is transmitted through the scattering slab, reversed in time, and transferred back through the slab. The original source locations are recovered through correlation of the forward and backward propagation across the multi-path environment provided by the scattering medium.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.374

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 head0.011
GPT teacher head0.199
Teacher spread0.188 · 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 designSimulation or modeling
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

Citations1
Published2015
Admission routes1
Has abstractyes

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