English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We propose and implement a novel hybrid meta-heuristic optimization algorithmfor the identification of non-collinear global ground-states in magneticsystems. The inputs to this optimization scheme are directly from non-collineardensity functional theory (DFT), and the workflow is implemented in the atomatecode framework, making it suitable to run on high-performance computingarchitectures. The hybrid algorithm provides a seamless theoretical extensionof particle swarm optimization (PSO) algorithms to continuous $\mathcal S^2$spins, giving it the name SpinPSO. The hybrid nature of the algorithm stemsfrom setting the dynamics of individual spins to be governed by physicallymotivated atomistic spin dynamics. Using this algorithm, we are able to achieveconvergence to experimentally resolved magnetic ground-states for a set ofdiverse test case materials that exhibit exotic spin textures.

SpinPSO: An agent-based optimization workflow for identifying global noncollinear magnetic ground-states from first-principles