Related papers: Profile approach for recognition of three-dimensio…
The antiferromagnetic - ferromagnetic phase transition in YBaCo2O5.50 and YBaCo2O5.44 cobaltites with different types of oxygen-ion ordering in the [YO0.5/0.44] layers has been studied by neutron powder diffraction. Using the magnetic…
Magnetic properties of stechiometric YTiO3 has been calculated within the single-ion-based paradigm taking into account the low-symmetry crystal field and the intra-atomic spin-orbit coupling of the Ti3+ ion. Despite of the very simplified…
We analyze the possible types of ordering in a boson--fermion model. The Hamiltonian is inherently related to the Bose--Hubbard model for vector two-species bosons in optical lattices. We show that such model can be reduced to the…
The quasi one-dimensional compound BaCu2Si2O7 demonstrates numerous spin-reorientation transitions both for a magnetic field applied along the easy axis of magnetization, and for a magnetic field applied perpendicular to it. The magnetic…
Three-dimensional magnetic nanostructures are an emerging platform capable of creating complex topological magnetic fields. The control of localized nanoscale magnetic fields is seen to be of importance for diverse areas from…
A wealth of literature exists on computing and visualizing cuts for the magnetic scalar potential of a current carrying conductor via Finite Element Methods (FEM) and harmonic maps to the circle. By a cut we refer to an orientable surface…
We derive the general form of the non-trivial geometric phase resulting from the unique combination of point group and time reversal symmetries. This phase arises e.g. when a magnetic adatom is adsorbed on a non-magnetic C$_n$ crystal…
Based on Monte-Carlo simulations, the stable magnetization configurations of an antiferromagnet on a quasiperiodic tiling are derived theoretically. The exchange coupling is assumed to decrease exponentially with the distance between…
A theoretical description is presented for low-temperature magnetic-field induced three-dimensional (3D) ordering transitions in strongly anisotropic quantum antiferromagnets, consisting of weakly coupled antiferromagnetic spin-1/2 chains…
Artificial neural networks and machine learning have now reached a new era after several decades of improvement where applications are to explode in many fields of science, industry, and technology. Here, we use artificial neural networks…
Magnetic structures, which play a central role in determining their physical properties, are known for only very limited compounds. Traditional theoretical approaches to predicting magnetic structures predominantly rely on first-principles…
In this paper, it is presented a novel strategy to optimize the determination of magnetic couplings by using ab-initio calculations of the energy. This approach allows determining efficiently, in terms of a proposed effective magnetic spin…
The magnetic configurations of barcode-type magnetic nanostructures consisting of alternate ferromagnetic and nonmagnetic layers arranged within a multilayer nanotube structure are investigated as a function of their geometry. Based on a…
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…
Artificial spin ices are arrays of coupled nanomagnets, which exhibit a variety of fascinating collective behaviour including emergent magnetic monopoles, charge screening, and novel phase transitions. However, they have mainly been…
Sophisticated spin instruments require high-precision spin control. In this study, we accurately study the intrinsic magnetic properties of the strongly disordered system NdFe0.5Cr0.5O3 through molecular field models combined with ASD…
Topology is a powerful tool for categorizing magnetization textures by defining a topological index in both two-dimensional (2D) systems, such as thin films or curved surfaces, and in 3D bulk systems. In the emerging field of 3D…
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…
We discuss the topology of the parameter space of invertible phases with an onsite symmetry $G$, i.e., quantum many-body ground states that have neither fractionalization nor spontaneous breaking of the symmetry. The classification of…
Spatial imaging of magnetic stray fields from magnetic materials is a useful tool for identifying the underlying magnetic configurations of the material. However, transforming the magnetic image into a magnetization image is an ill-poised…