Related papers: Machine learning as an improved estimator for magn…
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…
One-dimensional spin-1/2 systems are well-known candidates to study the quantum correlations between particles. In the condensed matter physics, studies often are restricted to the 1st neighbor particles. In this work, we consider the 1D…
Recently, machine-learning methods have been shown to be successful in identifying and classifying different phases of the square-lattice Ising model. We study the performance and limits of classification and regression models. In…
We propose a non-collinear spin-constrained method that generates training data for deep-learning-based magnetic model, which provides a powerful tool for studying complex magnetic phenomena that requires large-scale simulations at the…
We study the magnetization curve of the Heisenberg model on the quasi-one-dimensional kagome-strip lattice that shares the same lattice structure in the inner part with the two-dimensional kagome lattice. Our numerical calculations based on…
The mapping transformation technique is applied to obtain exact results for the spin-1/2 and spin-S (S=1/2,1) Ising-Heisenberg antiferromagnetic chain in the presence of an external magnetic field. Within this scheme, a field-induced…
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…
Unconventional features of the magnetization curve at zero temperature such as plateaus or jumps are a hallmark of frustrated spin systems. Very little is known about their behavior at non-zero temperatures. Here we investigate the…
Entanglement can improve the measurement precision of quantum sensors beyond the shot noise limit. Neutral atoms, the basis of some of the most precise and accurate optical clocks and interferometers, do not naturally exhibit all-to-all…
We theoretically study the entanglement between two arbitrary spins in a magnetic material, where magnons naturally form a general squeezed coherent state, in the presence of an applied magnetic field and axial anisotropies. Employing…
Spin ice in a magnetic field in the [111] direction displays two magnetization plateaux, one at saturation and an intermediate one with finite entropy. We study the crossovers between the different regimes from a point of view of…
The Ising chain consisting of the antiferromagneticaly coupled ferromagnetic trimer is considered in the external magnetic field. In the framework of the transfer-matrix formalism the thermodynamics of the system is described. The…
Two one-dimensional spin-1 antiferromagnetic Ising models with a single-ion anisotropy under external magnetic field at low temperatures are exactly investigated by the transfer-matrix technique. The magnetization per spin ($m$) is obtained…
A full energy spectrum of the spin-1/2 Heisenberg cubic cluster is used to investigate a low-temperature magnetization process and adiabatic demagnetization of this zero-dimensional 2x2x2 quantum spin system. It is shown that the…
We present a method to compute the magnetic susceptibility of spin systems at all temperatures in one and two dimensions. It relies on an approximation of the entropy versus energy (microcanonical potential function) on the whole range of…
Machine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-dependent problems in micromagnetism such as fast response…
The characterization and manipulation of deposited magnetic clusters or molecules on surfaces is a prerequisite for their future utilization. In recent years techniques like spin-flip inelastic electron tunneling spectroscopy using a…
The magnetization process of the S=1 and 1/2 kagome Heisenberg antiferromagnet is studied by means of the numerical exact diagonalization method. It is found that the magnetization curve at zero temperature has a plateau at 1/3 of the full…
Machine learning has become a premier tool in physics and other fields of science. It has been shown that the quantum mechanical scattering problem can not only be solved with such techniques, but it was argued that the underlying neural…
The magnetization reversal in a single molecular magnet (SMM) weakly coupled to an electrode with spin-dependent splitting of chemical potentials (spin bias) is theoretically investigated by means of the rate equation. A microscopic…