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Record W2725333436 · doi:10.1063/1.4990977

Characterization of the non-resonant radiation damping in coupled cavity photon magnon system

2017· article· en· W2725333436 on OpenAlexafffund
Jinwei Rao, Sukhvinder Kaur, Xiaolong Fan, Ding‐Jiang Xue, Bimu Yao, Y. S. Gui, C.‐M. Hu

Bibliographic record

VenueApplied Physics Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsUniversity of Manitoba
FundersScience and Technology Commission of Shanghai MunicipalityCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaChina Scholarship CouncilCanada Foundation for Innovation
KeywordsMagnonLaser linewidthPhysicsPhotonResonance (particle physics)Condensed matter physicsRelaxation (psychology)Magnetic dampingAtomic physicsOpticsQuantum mechanicsLaserFerromagnetismVibration

Abstract

fetched live from OpenAlex

We have experimentally investigated the non-resonant radiation damping in the coupled cavity photon-magnon system in addition to the resonant radiation damping which results in the linewidth exchange between the magnon-like and photon-like hybrid modes. The contribution of this non-resonant effect becomes apparent when the cavity photon-magnon resonance frequencies are mismatched. By carefully examining the change in the linewidth and the shift in the magnon resonance as a function of the coupling strength between the cavity photons and magnons, we can quantitatively describe this non-resonant radiation damping by including an additional relaxation channel for the hybridized photon-magnon system. This experimental realization and theoretical modelling of the non-resonant radiation damping in the cavity photon-magnon system may help in the design and adaptation of these systems for practical applications.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.376

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 head0.008
GPT teacher head0.216
Teacher spread0.207 · 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 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

Citations12
Published2017
Admission routes2
Has abstractyes

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