Related papers: Dynamic structure factor of superfluid He-4 from Q…
\textit{Ab initio} quantum Monte Carlo (QMC) methods in principle allow for the calculation of exact properties of correlated many-electron systems, but are in general limited to the simulation of a finite number of electrons $N$ in…
To better understand the capture process by a nanopore, we introduce an efficient Kinetic Monte Carlo (KMC) algorithm that can simulate long times and large system sizes by mapping the dynamic of a point-like particle in a 3D spherically…
A study of Final State Effects (FSE) on the dynamic structure function of superfluid $^4$He in the Gersch--Rodriguez formalism is presented. The main ingredients needed in the calculation are the momentum distribution and the semidiagonal…
We present an elementary and self-contained account of the analogies existing between classical diffusion and the imaginary-time evolution of quantum systems. These analogies are used to develop a new quantum simulation method which allows…
Inferring a quantum system from incomplete information is a common problem in many aspects of quantum information science and applications, where the principle of maximum entropy (MaxEnt) plays an important role. The quantum state…
We introduce a theoretical approach to study the quantum-dissipative dynamics of electronic excitations in macromolecules, which enables to perform calculations in large systems and cover long time intervals. All the parameters of the…
In the last few years we have been developing a Monte Carlo simulation method to cope with systems of many electrons and ions in the Born-Oppenheimer (BO) approximation, the Coupled Electron-Ion Monte Carlo Method (CEIMC). Electronic…
We have studied the solubility of molecular hydrogen in bulk liquid $^4$He at zero temperature using the diffusion Monte Carlo method and realistic interatomic potentials between the different species of the mixture. Around the $^4$He…
We have simulated the three-dimensional Heisenberg model on simple cubic lattices, using the single-cluster Monte Carlo update algorithm. The expected pronounced reduction of critical slowing down at the phase transition is verified. This…
The behavior of quantum fluids (4He and H2) within nanopores is explored in various regimes, using several different methods. A focus is the evolution of each fluid's behavior as pore radius R is increased. Results are derived with the path…
We present a new approach to the study of equilibrium properties in many-body quantum physics. Our method takes inspiration from Density Matrix Quantum Monte Carlo and incorporates new crucial features. First of all, the dynamics is…
We present explicit methods for simulating diffusions whose generator is self-adjoint with respect to a known (but possibly not normalizable) density. These methods exploit this property and combine an optimized Runge-Kutta algorithm with a…
We perform calculations of the momentum distribution n(k) in solid \^4\He by means of path integral Monte Carlo methods. We see that, in perfect crystal, n(k) does not depend on temperature T and that is different from the classical…
The yardstick of new first-principles approaches to key points on reaction paths at metal surfaces is chemical accuracy compared to reliable experiment. By this we mean that such values as the activation barrier are required to within 1…
By using a Reverse Monte Carlo technique aimed at the inverse problem in the analysis of the H+D Ly-a absorption from QSO spectra we have estimated the physical parameters of the gas and the large-scale line of sight velocity structure…
We have performed quantum Monte Carlo simulations measuring the finite size and temperature superfluid response of helium-4 to the linear and rotational motion of the walls of a nanopore. Within the two-fluid model, the portion of the…
Feature detection is an important procedure for image matching, where unsupervised feature detection methods are the detection approaches that have been mostly studied recently, including the ones that are based on repeatability requirement…
Maximum entropy models provide the least constrained probability distributions that reproduce statistical properties of experimental datasets. In this work we characterize the learning dynamics that maximizes the log-likelihood in the case…
The study of alloys using computational methods has been a difficult task due to the usually unknown stoichiometry and local atomic ordering of the different structures experimentally. In order to combat this, first-principles methods have…
Dynamic properties of the three-dimensional single-band Hubbard model are studied using Quantum Monte Carlo combined with the maximum entropy technique. At half-filling, there is a clear gap in the density of states and well-defined…