MétaCan
Menu
Back to cohort
Record W3199768892

Optical Cloak Design Exploiting Efficient Anisotropic Adjoint Sensitivity Analysis

2017· article· en· W3199768892 on OpenAlexaff
Laleh Seyyed-Kalantari, Mohamed H. Bakr

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCloakingSensitivity (control systems)Computer scienceCloakRobustness (evolution)WidebandInvisibilityAnisotropyFunction (biology)Variable (mathematics)Mathematical optimizationAlgorithmOpticsPhysicsMathematicsElectronic engineeringMetamaterialMathematical analysisArtificial intelligenceEngineering
DOInot available

Abstract

fetched live from OpenAlex

We propose in this work a novel optimizationbased wideband invisibility cloaking approach at optical frequencies. We exploit the memory efficient anisotropic adjoint variable method (AVM) to significantly accelerate the sensitivity analysis with respect to the large number of parameters. Minimizing the cloaking objective function involves the gradients estimation with respect to a massive number of parameters at every iteration for time-intensive electromagnetic simulations. The AVM evaluates the required gradients over one thousand time faster than conventional methods. The significant reduction in the computational cost enables wideband optimization-based cloak design at optical region.

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 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 score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.064
GPT teacher head0.300
Teacher spread0.236 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicMetamaterials and Metasurfaces ApplicationsFrench-language works237,207