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Record W4414912751 · doi:10.1103/9mlg-ckxl

Relaxation pathways and emergence of domains in square artificial spin ice

2025· article· en· W4414912751 on OpenAlexaff
Matteo Menniti, Naëmi Leo, P. Villalba-González, Matteo Pancaldi, P. Vavassori

Bibliographic record

VenuePhysical review. B./Physical review. B · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsUniversity of British Columbia
FundersHorizon 2020Ministerio de Ciencia e InnovaciónMinisterio de Ciencia, Innovación y UniversidadesUK Research and Innovation
KeywordsSpin iceKinetic Monte CarloMesoscale meteorologyNanomagnetSquare (algebra)Relaxation (psychology)Monte Carlo methodSpin (aerodynamics)

Abstract

fetched live from OpenAlex

Multidomain states of square artificial spin ice show a range of different morphologies ranging from simple stripelike domains to more organically shaped coral domains. To model the relevant dynamics leading to the emergence of such diverse domain structures, simplified descriptions of the switching behavior of individual nanomagnets are necessary. In this work, we employ kinetic Monte Carlo simulations of the demagnetization of square artificial spin ice toward its ground state and compare how the choice of transition barriers affect the emergence of mesoscale domains. We find that the commonly used mean-field barrier model (informed by equilibrium energetics only) results in propagation of ground-state string avalanches. In contrast, taking into account chiral barrier splitting enabled by state-dependent local torques supports the emergence of complex-shaped coral domains and their successful relaxation towards the ground state in later relaxation stages. Our results highlight that intrinsic contributions to switching barriers, in addition to the effect of extrinsic defects often attributed to nanofabrication irregularities, can subtly shift favored transition pathways and result in different emergent mesoscale features. Future kinetic Monte Carlo models that describe the evolution of artificial spin systems should thus account for these 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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.365
Teacher spread0.349 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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