Related papers: Machine learning dynamics of phase separation in c…
The phenomenon of colossal magnetoresistance in manganites is generally agreed to be a result of competition between crystal phases with different electronic, magnetic, and structural order; a competition which can be strong enough to cause…
The quantum phase transition between paramagnetic and antiferromagnetic phases of the Kondo lattice model with Ising anisotropy in the intersite exchange is studied within the framework of extended dynamical mean-field theory.…
The diluted Kondo lattice model is investigated at strong antiferromagnetic local exchange couplings J, where almost local Kondo clouds drastically restrict the motion of conduction electrons, giving rise to the possibility of quantum…
The phase diagram of the ferromagnetic Kondo model for manganites is investigated using computational techniques. In clusters of dimensions 1 and 2, Monte Carlo simulations in the limit where the localized spins are classical show a rich…
We review recent advances in machine-learning (ML) force-field methods for large-scale Landau-Lifshitz-Gilbert (LLG) simulations of metallic spin systems. We generalize the Behler-Parrinello (BP) ML architecture -- originally developed for…
The phase transition of a random mixed-bond Ising ferromagnet on a cubic lattice model is studied both numerically and analytically. In this work, we use the Cluster algorithms of Wolff and Glauber to simulate the dynamics of the system. We…
Various auxiliary-particle approaches to treat electron correlations in many-electron models are analyzed. Applications to copper-oxide layered systems are discussed. The ground-state magnetic phase diagrams are considered within the…
We present a lattice model to study the equilibrium phase diagram of ordered alloys with one magnetic component that exhibits a low temperature phase separation between paramagnetic and ferromagnetic phases. The model is constructed from…
We report a preliminary numerical study by kinetic Monte Carlo simulation of the dynamics of phase separation following a quench from high to low temperature in a system with a single, conserved, scalar order parameter (a kinetic Ising…
The 2D ferromagnetic Kondo model with classical corespins is studied for a hole doping up to x = 0.125 via unbiased Monte Carlo (MC) simulations. A canonical algorithm for finite temperatures is developed. We show that with realistic…
The interplay between the Kondo effect and magnetic ordering driven by the Ruderman-Kittel-Kasuya-Yosida interaction is studied within the two-dimensional Hubbard-Kondo lattice model. In addition to the antiferromagnetic exchange…
We describe the transition from a ferromagnetic phase, to a disordered para- magnetic phase, which occurs in one-dimensional Kondo lattice models with partial conduction band filling. The transition is the quantum order-disorder transition…
We theoretically study photoinduced magnetic phase transitions and their dynamical processes in the Kondo-lattice model on a cubic lattice. It is demonstrated that light irradiation gives rise to magnetic phase transitions from the…
We propose a self-consistent approximate solution of the disordered Kondo-lattice model (KLM) to get the interconnected electronic and magnetic properties of 'local-moment' systems like diluted ferromagnetic semiconductors. Aiming at…
The unconventional critical behavior near magnetic quantum phase transitions in various heavy-fermion metals, apparently inconsistent with the standard spin-density-wave scenario, has triggered proposals on the breakdown of the Kondo effect…
We investigate the ferromagnetic Kondo-lattice model (FKLM) with a correlated conduction band. A moment conserving approach is proposed to determine the electronic self-energy. Mapping the interaction onto an effective Heisenberg model we…
We review the recent development of machine-learning (ML) force-field frameworks for Landau-Lifshitz-Gilbert (LLG) dynamics simulations of itinerant electron magnets, focusing on the general theory and implementations of symmetry-invariant…
A machine learning technique is proposed for quantifying uncertainty in power system dynamics with spatiotemporally correlated stochastic forcing. We learn one-dimensional linear partial differential equations for the probability density…
The phase diagram of the two-channel Kondo lattice model is examined with a Quantum Monte Carlo simulation in the limit of infinite dimensions. Commensurate (and incommensurate) antiferromagnetic and superconducting states are found. The…
Using unitary transformations, we express the Kondo lattice Hamiltonian in terms of fermionic operators that annihilate the ground state of the interacting system and that represent the best possible approximations to the actual charged…