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Record W4391776088 · doi:10.1063/5.0176462

Nonreciprocity in cavity magnonics at millikelvin temperature

2024· article· en· W4391776088 on OpenAlexafffund
Mun Kim, Armin Tabesh, Tyler Zegray, Shabir Barzanjeh, C.‐M. Hu

Bibliographic record

VenueJournal of Applied Physics · 2024
Typearticle
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsUniversity of CalgaryUniversity of Manitoba
FundersRES’EAU-WaterNETAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsDissipative systemYttrium iron garnetIsolatorMicrowaveMagnonicsBroadbandReciprocity (cultural anthropology)OptoelectronicsMaterials scienceInsertion lossPhysicsOpticsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Incorporating cavity magnonics has opened up a new avenue in controlling non-reciprocity. This work examines a yttrium iron garnet sphere coupled to a planar microwave cavity at millikelvin temperature. Non-reciprocal device behavior results from the cooperation of coherent and dissipative coupling between the Kittel mode and a microwave cavity mode. The device’s bi-directional transmission was measured and compared to the theory derived previously in the room temperature experiment. Investigations are also conducted into key performance metrics such as isolation, bandwidth, and insertion loss. The findings point to the coexistence of coherent and dissipative interactions at cryogenic conditions, and one can leverage their cooperation to achieve directional isolation. This work foreshadows the application of a cavity magnonic isolator for on-chip readout and signal processing in superconducting circuitry.

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 score0.003

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 studies0.0000.001
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations9
Published2024
Admission routes2
Has abstractyes

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