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Record W2883858862 · doi:10.1063/1.5017139

Influence of stripline coupling on the magnetostatic mode line width of an yttrium-iron-garnet sphere

2018· article· en· W2883858862 on OpenAlexafffund
Ying Yang, Michael Harder, Jinwei Rao, Bimu Yao, Wei Lü, Y. S. Gui, C.‐M. Hu

Bibliographic record

VenueAIP Advances · 2018
Typearticle
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsUniversity of Manitoba
FundersChina Scholarship CouncilScience and Technology Commission of Shanghai MunicipalityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsYttrium iron garnetStriplineCoupling (piping)Materials scienceDispersion (optics)Condensed matter physicsBroadbandLine (geometry)OptoelectronicsOpticsPhysicsComposite material

Abstract

fetched live from OpenAlex

We study the effect of stripline coupling on the damping of magnetostatic modes in an yttrium-iron-garnet sphere. Both the magnetostatic dispersion and line width display a pronounced dependence on the YIG-stripline separation, with the coupling dominating the line width for small separations. By suppressing the coupling effect we use a broadband technique to measure both the Gilbert damping, α = (6.5 ± 0.5) × 10−5, and the inhomogeneous broadening which is mode dependent and as small as 0.075 MHz. Our study therefore reveals the importance of, and a method for, exploring the influence of coupling on damping, which may be useful for future device characterization and design.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.246
Teacher spread0.235 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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