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We propose and apply simple machine learning approaches for recognition and classification of complex non-collinear magnetic structures in two-dimensional materials. The first approach is based on the implementation of the…

Strongly Correlated Electrons · Physics 2018-11-14 I. A. Iakovlev , O. M. Sotnikov , V. V. Mazurenko

We classify the magnetic ground states of a 2D lattice of localized magnetic moments which are coupled to a superconducting substrate with Rashba-spin-orbit coupling. We discover a rich magnetic phase diagram with surprisingly complex…

The magnetic structure is crucial in determining the physical properties inherent in magnetic compounds. We present an adequate descriptor for magnetic structure with proper magnetic symmetry and high discrimination performance, which does…

Materials Science · Physics 2023-07-19 Michi-To Suzuki , Takuya Nomoto , Eiaki V. Morooka , Yuki Yanagi , Hiroaki Kusunose

We explore the structure of the space of quasisymmetric configurations identifying them by their magnetic axes, described as 3D closed curves. We demonstrate that this topological perspective divides the space of all configurations into…

Plasma Physics · Physics 2022-09-14 Eduardo Rodriguez , Wrick Sengupta , Amitava Bhattacharjee

Originating from image recognition, methods of machine learning allow for effective feature extraction and dimensionality reduction in multidimensional datasets, thereby providing an extraordinary tool to deal with classical and quantum…

Statistical Mechanics · Physics 2019-01-16 Albert A. Shirinyan , Valerii K. Kozin , Johan Hellsvik , Manuel Pereiro , Olle Eriksson , Dmitry Yudin

Given the scarcity of experimentally confirmed magnetic structures, the reliable prediction of magnetic ground states is crucial; however, it remains a long-sought challenge because of the complex magnetic potential energy landscape. Here,…

Materials Science · Physics 2025-12-29 Yuhui Li , Sike Zeng , Xiaobing Chen , Renzheng Xiong , Yutong Yu , Yu-Jun Zhao , Qihang Liu

Recently, there has been an increased interest in the application of machine learning (ML) techniques to a variety of problems in condensed matter physics. In this regard, of particular significance is the characterization of simple and…

Strongly Correlated Electrons · Physics 2023-11-22 F. A. Gómez Albarracín , H. D. Rosales

The past years have seen rapid progress in the classification of topological materials. These diagnostical methods are increasingly getting explored in the pertinent context of magnetic structures. We report on a general class of electronic…

Mesoscale and Nanoscale Physics · Physics 2021-06-18 Adrien Bouhon , Gunnar F. Lange , Robert-Jan Slager

Magnetic skyrmion, i.e. a topologically stable swirling spin texture, appears as a particle-like object in the two-dimensional (2D) systems, and has recently attracted attention as a candidate of novel information carrier. In the real…

Strongly Correlated Electrons · Physics 2022-02-16 S. Seki , M. Suzuki , M. Ishibashi , R. Takagi , N. D. Khanh , Y. Shiota , W. Koshibae , Y. Tokura , T. Ono

One of the most important magnetic spin structure is the topologically stabilised skyrmion quasi-particle. Its interesting physical properties make them candidates for memory and efficient neuromorphic computation schemes. For the device…

Machine Learning · Computer Science 2023-03-31 Isaac Labrie-Boulay , Thomas Brian Winkler , Daniel Franzen , Alena Romanova , Hans Fangohr , Mathias Kläui

Two-dimensional colloidal suspensions exposed to periodic external fields exhibit a variety of molecular crystalline phases. There two or more colloids assemble at lattice sites of potential minima to build new structural entities, referred…

Soft Condensed Matter · Physics 2009-11-11 Andreja Sarlah , Erwin Frey , Thomas Franosch

Topological surgery in dimension $3$ is intrinsically connected with the classification of $3$-manifolds and with patterns of natural phenomena. In this expository paper, we present two different approaches for understanding and visualizing…

Geometric Topology · Mathematics 2018-11-21 Stathis Antoniou , Louis H. Kauffman , Sofa Lambropoulou

Finding the true magnetic structure at given external conditions is crucial for describing magnetic materials and predicting their properties. This is especially important for high-throughput screening of potentially good magnets that…

Materials Science · Physics 2021-04-07 Olga Yu. Vekilova

The structural and magnetic properties of the hexagonal four-layer form of SrMnO$_3$ have been investigated by combining magnetization measurements, electron diffraction and high-resolution synchrotron X-ray and neutron powder diffraction.…

Strongly Correlated Electrons · Physics 2007-05-23 A. Daoud-Aladine , C. Martin , L. C. Chapon , M. Hervieu , K. S. Knight , M. Brunelli , P. G. Radaelli

Due to a ferromagnetic in-chain coupling between Co$^{3+}$ ions at trigonal sites, chains Co$_2$O$_6$ are considered as large rigid spin moments. The antiferromagnetic Ising model on the triangular lattice is applied to describe an…

Strongly Correlated Electrons · Physics 2009-11-11 Yuri B. Kudasov

The identification and classification of different magnetic states are essential for understanding the complex behavior of magnetic systems. Traditional approaches that rely on handcrafted features or manual inspection often fall short,…

Materials Science · Physics 2026-05-22 Amal Aldarawsheh , Ahmed Alia , Stefan Blügel

Topological analysis of the magnetic field in simulated plasmas allows the study of various physical phenomena in a wide range of settings. One such application is magnetic reconnection, a phenomenon related to the dynamics of the magnetic…

The magnetic properties of single-domain nanoparticles with different geometric shapes, crystalline anisotropies and lattice structures are investigated. A recently proposed scaling approach is shown to be universal and in agreement with…

Strongly Correlated Electrons · Physics 2009-11-13 Wen Zhang , Rohit Singh , Noah Bray-Ali , Stephan Haas

Magnetic moments near zigzag edges in graphene allow complex nanostructures with customised spin properties to be realised. However, computational costs restrict theoretical investigations to small or perfectly periodic structures. Here we…

Mesoscale and Nanoscale Physics · Physics 2022-09-14 Meriç E. Kucukbas , Seán McCann , Stephen R. Power

Recent progress in nanofabrication and additive manufacturing have facilitated the building of nanometer-scale three-dimensional structures, that promise to lead to an emergence of new functionalities within a number of fields, compared to…

Mesoscale and Nanoscale Physics · Physics 2020-04-22 Claire Donnelly , Valerio Scagnoli
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