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During the last 15 years, there has been much progress in defining the nuclear Hamiltonian and applying quantum Monte Carlo methods to the calculation of light nuclei. I describe both aspects of this work and some recent results.

Nuclear Theory · Physics 2014-11-18 Steven C. Pieper

We introduce modifications to Monte Carlo simulations of the Feynman path integral that improve sampling of localised interactions. The new algorithms generate trajectories in simple background potentials designed to concentrate them about…

Quantum Physics · Physics 2025-08-06 Ivan Ahumada , James P. Edwards

Here we present the derivation, description and results of a Monte Carlo-based algorithm for simulating inelastic scattering of photo-electrons when passing through some scattering medium, such as a gas atmosphere or a solid material. The…

Computational Physics · Physics 2021-01-06 Lukas Pielsticker , Robert Schlögl , Mark Greiner

In recent years, tremendous progress has been made on numerical algorithms for solving partial differential equations (PDEs) in a very high dimension, using ideas from either nonlinear (multilevel) Monte Carlo or deep learning. They are…

Numerical Analysis · Mathematics 2021-12-13 Weinan E , Jiequn Han , Arnulf Jentzen

The Diffusion Monte Carlo method with constant number of walkers, also called Stochastic Reconfiguration as well as Sequential Monte Carlo, is a widely used Monte Carlo methodology for computing the ground-state energy and wave function of…

Statistics Theory · Mathematics 2024-12-09 Michel Caffarel , Pierre del Moral , Luc de Montella

In Monte Carlo particle transport codes, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte Carlo. We present the theory and…

Computational Physics · Physics 2011-12-09 Marcus H. Mendenhall , Robert A. Weller

This paper addresses optimization problems constrained by partial differential equations with uncertain coefficients. In particular, the robust control problem and the average control problem are considered for a tracking type cost…

Optimization and Control · Mathematics 2017-11-08 Andreas Van Barel , Stefan Vandewalle

In the last ten years significant advances have been made in our understanding and ability to compute and predict properties of ferroelectrics and piezoelectrics using fundamental physics. Phase diagrams, electromechanical and elastic…

Materials Science · Physics 2007-05-23 Ronald E. Cohen

Monte Carlo methods are widely used importance sampling techniques for studying complex physical systems. Integrating these methods with deep learning has significantly improved efficiency and accuracy in high-dimensional problems and…

Disordered Systems and Neural Networks · Physics 2024-12-24 Yixiong Ren , Jianhui Zhou

Many biochemical systems appearing in applications have a multiscale structure so that they converge to piecewise deterministic Markov processes in a thermodynamic limit. The statistics of the piecewise deterministic process can be obtained…

Computational Physics · Physics 2016-12-30 Ethan Levien , Paul C. Bressloff

The emergence of hydrodynamic behavior in electronic flow within clean, particle-hole-symmetric systems at half-filling is a non-trivial problem. Navier-Stokes (NS) equations describe the momentum flow, while experimental measurements…

Mesoscale and Nanoscale Physics · Physics 2025-05-26 Adrien Reingruber , Kitinan Pongsangangan , Fakher Assaad , Maksim Ulybyshev

We propose and analyze a method for computing failure probabilities of systems modeled as numerical deterministic models (e.g., PDEs) with uncertain input data. A failure occurs when a functional of the solution to the model is below (or…

Numerical Analysis · Mathematics 2016-06-21 Daniel Elfverson , Fredrik Hellman , Axel Målqvist

We developed a three-dimensional radiative transfer code for an ultra-relativistic background flow-field by using the Monte Carlo (MC) method in the context of gamma-ray burst (GRB) emission. For obtaining reliable simulation results in the…

High Energy Astrophysical Phenomena · Physics 2017-09-13 Ayako Ishii , Naofumi Ohnishi , Hiroki Nagakura , Hirotaka Ito , Shoichi Yamada

The computational cost of a Monte Carlo algorithm can only be meaningfully discussed when taking into account the magnitude of the resulting statistical error. Aiming for a fixed error per particle, we study the scaling behavior of the…

Computational Physics · Physics 2010-02-11 Norbert Nemec

The goal of this manuscript is to estimate Type B uncertainties in absorbed-dose calculations arising from the different implementations in current state-of-the-art Monte Carlo codes of low-energy photon cross-sections (<200 keV). Monte…

We study semi-linear elliptic PDEs with polynomial non-linearity and provide a probabilistic representation of their solution using branching diffusion processes. When the non-linearity involves the unknown function but not its derivatives,…

Probability · Mathematics 2018-02-15 Ankush Agarwal , Julien Claisse

Electron transfer (ET) across molecular chains including an impurity is studied based on a recently improved real-time path integral Monte Carlo (PIMC) approach [J. Chem. Phys. {\bf 121}, 12696 (2004)]. The reduced electronic dynamics is…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Lothar Muehlbacher , Joachim Ankerhold

We present a version of the T-moves approach for treating nonlocal pseudopotentials in diffusion Monte Carlo which has much smaller time-step errors than the existing T-moves approaches, while at the same time preserving desirable features…

Chemical Physics · Physics 2021-07-29 Tyler A. Anderson , C. J. Umrigar

A new computational procedure is offered to provide simple, accurate and flexible methods for using modern computers to give numerical evaluations of the various Bessel functions. The Trapezoidal Rule, applied to suitable integral…

Numerical Analysis · Mathematics 2015-06-11 Charles Schwartz