Related papers: Supervised learning magnetic skyrmion phases
Topologically non-trivial spin textures, such as skyrmions and dislocations, display emergent electrodynamics and can be moved by spin currents over macroscopic distances. These unique properties and their nanoscale size make them excellent…
Skyrmions are topological magnetic textures that can arise in non-centrosymmetric ferromagnetic materials. In most systems experimentally investigated to date, skyrmions emerge as classical objects. However, the discovery of skyrmions with…
Complex spin-spin interactions in magnets can often lead to magnetic superlattices with complex local magnetic arrangements, and many of the magnetic superlattices have been found to possess non-trivial topological electronic properties.…
We introduce an unsupervised machine learning method based on Siamese Neural Networks (SNN) to detect phase boundaries. This method is applied to Monte-Carlo simulations of Ising-type systems and Rydberg atom arrays. In both cases the SNN…
We consider a lattice model of itinerant electrons coupled to an array of localized classical Heisenberg spins. The nature of the ground state ordered magnetic phases that result from the indirect spin-spin coupling mediated by the…
We apply unsupervised learning techniques to classify the different phases of the $J_1-J_2$ antiferromagnetic Ising model on the honeycomb lattice. We construct the phase diagram of the system using convolutional autoencoders. These neural…
The main ideas and some of the most important results of the spherically symmetric self-consistent approach and a number of related theoretical algorithms are presented. These methods make it possible to study low-dimensional…
We present the results of a muon-spin relaxation (muSR) investigation into magnetic ordering in several families of layered quasi-two-dimensional molecular antiferromagnets based on transition metal ions such as S=1/2 Cu2+ bridged with…
Machine-learning techniques are evolving into a subsidiary tool for studying phase transitions in many-body systems. However, most studies are tied to situations involving only one phase transition and one order parameter. Systems that…
Hamiltonian parameter estimation is crucial in condensed matter physics, but time and cost consuming in terms of resources used. With advances in observation techniques, high-resolution images with more detailed information are obtained,…
The ground states of square lattice two-dimensional antiferromagnets with anisotropy in an external magnetic field are determined using Monte Carlo simulations and compared to theoretical analysis. We find a new phase in between the…
Microstructure of materials is often characterized through image analysis to understand processing-structure-properties linkages. We propose a largely automated framework that integrates unsupervised and supervised learning methods to…
Magnetic skyrmions are topological quasiparticles potentially useful for memory and computing devices. Antiferromagnetic (AF) skyrmions present no transverse deflection, making them suitable candidates for data storage applications. After…
The entire magnetic phase diagram of the quasi two dimensional (2D) magnet on a distorted triangular lattice KFe(MoO4)2 is outlined by means of magnetization, specific heat, and neutron diffraction measurements. It is found that the spin…
In a broad range of applied magnetic fields and material parameters isolated magnetic skyrmions condense into skyrmion lattices. While the geometry of isolated skyrmions and their lattice counterparts strongly depend on field and…
Altermagnet is a newly discovered magnetic phase, characterized by non-relativistic spin-splitting that has been experimentally observed. Here, we introduce a framework dubbed {\it spin-orbital altermagnetism} to achieve spin-orbital…
The power of machine learning algorithms to automatically classify different phases of matter and detect quantum phase transitions without necessity to characterize phases by various quantities like local order parameters or topological…
We find approximate solutions for the two-dimensional non-linear {\Sigma}-model with Dzyalioshinkii-Moriya term, representing magnetic Skyrmions. They are built in an analytic form, by pasting different approximate solutions found in…
The classification of phases and the detection of phase transitions are central and challenging tasks in diverse fields. Within physics, it relies on the identification of order parameters and the analysis of singularities in the free…
The formation of a skyrmion crystal and its phase transition are studied taking into account the Dzyaloshinskii-Moriya (DM) interaction at the interface between a ferroelectric layer and a magnetic layer in a superlattice. The frustration…