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Record W2041676158 · doi:10.1063/1.4905478

Ultra-high <i>Q</i> even eigenmode resonance in terahertz metamaterials

2015· article· en· W2041676158 on OpenAlexaff
Ibraheem Al‐Naib, Yuping Yang, Marc M. Dignam, Weili Zhang, Ranjan Singh

Bibliographic record

VenueApplied Physics Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsQueen's University
FundersDivision of Electrical, Communications and Cyber SystemsMinistry of Education, IndiaNational Science Foundation
KeywordsNormal modeResonatorEigenmode expansionResonance (particle physics)PhysicsMetamaterialQ factorExcitationSplit-ring resonatorOpticsAtomic physicsVibrationAcousticsQuantum mechanics

Abstract

fetched live from OpenAlex

We report the simultaneous excitation of the odd and the even eigenmode resonances in a periodic array of square split-ring resonators, with four resonators per unit cell. When the electric field is parallel to their gaps, only the two well-studied odd eigenmodes are excited. As the resonators are rotated relative to one another, we observe the emergence and excitation of an extremely sharp even eigenmode. In uncoupled split-ring resonators, this even eigenmode is typically radiative in nature with a broad resonance linewidth and low Q-factor. However, in our coupled system, for specific range of rotation angles, our simulations revealed a remarkably high quality factor (Q ∼ 100) for this eigenmode, which has sub-radiant characteristics. This type of quad-supercell metamaterial offers the advantage of enabling access to all the three distinct resonance features of the split-ring resonator, which consists of two odd eigenmodes in addition to the high-Q even eigenmode, which could be exploited for high performance multiband filters and absorbers. The high Q even eigenmode could find applications in designing label free bio-sensors and for studying the enhanced light matter interaction effects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations85
Published2015
Admission routes1
Has abstractyes

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