Related papers: Machine learning dynamics of phase separation in c…
Learning from data has led to a paradigm shift in computational materials science. In particular, it has been shown that neural networks can learn the potential energy surface and interatomic forces through examples, thus bypassing the…
The Kondo lattice mode, as one of the most fundamental models in condensed matter physics, has been employed to describe a wide range of quantum materials such as heavy fermions, transition metal dichalcogenides and two-dimensional Moire…
We propose a method for learning dynamical systems from high-dimensional empirical data that combines variational autoencoders and (spatio-)temporal attention within a framework designed to enforce certain scientifically-motivated…
We consider a model with competing double-exchange (ferromagnetic) and super-exchange (anti-ferromagnetic) interactions in the regime where phase separation takes place. The presence of a long range Coulomb interaction frustrates a…
We study semiclassical dynamics of anisotropic Heisenberg models in two and three dimensions. Such models describe lattice spin systems and hard core bosons in optical lattices. We solve numerically Landau-Lifshitz type equations on a…
The effect of electron-lattice interaction is studied for a strongly correlated electron system described by the two-band Hubbard model. A two-fold effect of electron-lattice interaction is taken into account: in non-diagonal terms, it…
Characterizing quantum many-body phase structure is a major goal for quantum simulation. Here, we employ an unsupervised learning approach based on diffusion maps to learn phase transitions in bosonic lattice systems described by…
Multichannel Kondo lattice models are examples of strongly correlated electronic systems that exhibit non-Fermi-liquid behavior due to the presence of a continuous channel symmetry. Mean-field analyses have predicted that these systems…
The detection of phase transitions is a fundamental challenge in condensed matter physics, traditionally addressed through analytical methods and direct numerical simulations. In recent years, machine learning techniques have emerged as…
We study the Ising model under a time-varying, but spatially homogeneous, Gaussian random magnetic field. In the Monte Carlo simulations, we go beyond the standard analysis of the order parameter by measuring the magnetization probability…
Formation of magnetically ordered state in the Kondo lattices is treated within the degenerate $s-f$ exchange and Coqblin-Schrieffer models. The Kondo renormalizations of the effective coupling parameter, magnetic moment and spin excitation…
Kondo insulators are emerging as a simplified setting to study both magnetic and metal-to-insulator quantum phase transitions. Here, we study a half-filled Kondo lattice model defined on a magnetically frustrated Shastry-Sutherland…
We investigate the nonequilibrium dynamics of a laser-pumped two-dimensional spinless Holstein model within a semiclassical framework, focusing on the melting and recovery of long-range charge-density-wave order. Accurately describing this…
We study a spin-ice Kondo lattice model on a breathing pyrochlore lattice with classical localized spins. The highly efficient kernel polynomial expansion method, together with a classical Monte Carlo method, is employed in order to study…
Using numerical data coming from Monte Carlo simulations of four-dimensional Causal Dynamical Triangulations, we study how automated machine learning algorithms can be used to recognize transitions between different phases of quantum…
How many magnetic moments periodically arranged on a metallic surface are needed to generate a coherent Kondo lattice behavior? We investigate this fundamental issue within the particle-hole symmetric Kondo lattice model using quantum Monte…
Lattice models exhibit significant potential in investigating phase transitions, yet they encounter numerous computational challenges. To address these issues, this study introduces a Monte Carlo-based approach that transforms lattice…
We analyze theoretically the phase diagram of a triangular triple quantum dot with strong onsite repulsion coupled to ferromagnetic leads. This model includes the competition of magnetic ordering of local or itinerant magnetic moments,…
Motivated by the growing interest in the novel quantum phases in materials with strong electron correlations and spin-orbit coupling, we study the interplay between the spin-orbit coupling, Kondo interaction, and magnetic frustration of a…
We present the analysis of the slowing down exhibited by stochastic dynamics of a ring-exchange model on a square lattice, by means of numerical simulations. We find the preservation of coarse-grained memory of initial state of density-wave…