English
Related papers

Related papers: Precise solution of few-body problems with the sto…

200 papers

The dynamics of fermionic many-body systems is investigated in the framework of Boltzmann-Langevin (BL) stochastic one-body approaches. Within the recently introduced BLOB model, we examine the interplay between mean-field effects and…

Nuclear Theory · Physics 2017-11-27 P. Napolitani , M. Colonna

We propose a simple method that allows, in one dimension, to solve exactly a wide class of classical stochastic many-body systems far from equilibrium. For the sake of illustration and without loss of generality, we focus on a model that…

Statistical Mechanics · Physics 2009-10-31 Pierre-Antoine Bares , Mauro Mobilia

Previous years researchers began to simulate open quantum system, taking into account the interaction between system and the environment. One approach to deal with this problem is to use the density matrix within the Liouville-von-Neumann…

Quantum Physics · Physics 2025-09-15 Mohammad Attrash , Roi Baer

In stochastic variational inference, the variational Bayes objective function is optimized using stochastic gradient approximation, where gradients computed on small random subsets of data are used to approximate the true gradient over the…

Methodology · Statistics 2015-10-19 Linda S. L. Tan , David J. Nott

We derive an exact single-body decomposition of the time-dependent Schroedinger equation for N pairwise-interacting fermions. Each fermion obeys a stochastic time-dependent norm-preserving wave equation. As a first test of the method we…

Quantum Physics · Physics 2009-11-10 L. Tessieri , J. Wilkie , M. Cetinbas

We tackle the problem of system identification, where we select inputs, observe the corresponding outputs from the true system, and optimize the parameters of our model to best fit the data. We propose a practical and computationally…

Systems and Control · Electrical Eng. & Systems 2025-10-02 Alexandros E. Tzikas , Mykel J. Kochenderfer

Dynamics in correlated quantum matter is a hard problem, as its exact solution generally involves a computational effort that grows exponentially with the number of constituents. While a remarkable progress has been witnessed in recent…

Strongly Correlated Electrons · Physics 2021-04-28 Roberto Verdel , Markus Schmitt , Yi-Ping Huang , Petr Karpov , Markus Heyl

The model of Fermi particles with random two-body interaction is investigated. This model allows to study the origin and accuracy of statistical laws in few-body systems, the role of interaction and chaos in thermalization, Fermi-Dirac…

Condensed Matter · Physics 2009-10-28 V. V. Flambaum , F. M. Izrailev , G. Casati

We study the full Navier--Stokes--Fourier system governing the motion of a general viscous, heat-conducting, and compressible fluid subject to stochastic perturbation. Stochastic effects are implemented through (i) random initial data, (ii)…

Analysis of PDEs · Mathematics 2017-10-31 Dominic Breit , Eduard Feireisl

We propose a general framework for finding the ground state of many-body fermionic systems by using feed-forward neural networks. The anticommutation relation for fermions is usually implemented to a variational wave function by the Slater…

Strongly Correlated Electrons · Physics 2021-12-21 Koji Inui , Yasuyuki Kato , Yukitoshi Motome

We present a variational Monte Carlo method that solves the nuclear many-body problem in the occupation number formalism exploiting an artificial neural network representation of the ground-state wave function. A memory-efficient version of…

Formalism based on complex-scaling method is developed for solving the few particle scattering problem by employing only trivial boundary conditions. Several applications are presented proving efficiency of the method in describing elastic…

Nuclear Theory · Physics 2015-03-19 Rimantas Lazauskas , Jaume Carbonell

The use of orthonormal wavelet basis functions for solving singular integral scattering equations is investigated. It is shown that these basis functions lead to sparse matrix equations which can be solved by iterative techniques. The…

Nuclear Theory · Physics 2009-11-10 B. M. Kessler , G. L. Payne , W. N. Polyzou

This paper presents a new stochastic finite element method for computing structural stochastic responses. The method provides a new expansion of stochastic response and decouples the stochastic response into a combination of a series of…

Numerical Analysis · Mathematics 2021-04-28 Zhibao Zheng

In this work we show results for light nuclear systems and small clusters of helium atoms using the hyperspherical harmonics basis. We use the basis without previous symmetrization or antisymmetrization of the state. After the…

Atomic and Molecular Clusters · Physics 2015-06-05 M. Gattobigio , A. Kievsky , M. Viviani

We study two-component bosonic systems with strong inter-species and vanishing intra-species interactions. A new class of exact eigenstates is found with energies that are {\it not} sums of the single-particle energies with wave functions…

Quantum Gases · Physics 2014-09-19 N. T. Zinner , A. G. Volosniev , D. V. Fedorov , A. S. Jensen , M. Valiente

A method to solve the Schr\"{o}dinger equation based on the use of constant particle-particle interaction potential surfaces is proposed. The many-body wave function is presented in configuration interaction form with coefficients -…

Quantum Physics · Physics 2018-06-19 V. M. Tapilin

We derive the exact form of the bosonized Hamiltonian for a many-body fermion system in one spatial dimension with arbitrary dispersion relations, using the droplet bosonization method. For a single-particle Hamiltonian polynomial in the…

High Energy Physics - Theory · Physics 2020-03-06 Dimitra Karabali , Alexios P. Polychronakos

Stochastic filtering is defined as the estimation of a partially observed dynamical system. A massive scientific and computational effort is dedicated to the development of numerical methods for approximating the solution of the filtering…

Probability · Mathematics 2013-06-04 Dan Crisan , Kai Li

Variational Bayes (VB) has been used to facilitate the calculation of the posterior distribution in the context of Bayesian inference of the parameters of nonlinear models from data. Previously an analytical formulation of VB has been…

Signal Processing · Electrical Eng. & Systems 2020-07-06 Michael A. Chappell , Martin S. Craig , Mark W. Woolrich