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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

The variation with energy of the total cross section for elastic electron scattering from atoms of several elements is caused primarily by shape resonances corresponding to the formation of temporary negative ions. It is shown that such…

Atomic Physics · Physics 2007-05-23 Peter Nicoletopoulos

We develop an Over Barrier Model for computing charge exchange between ions and one-active-electron atoms at low impact energies. The main feature of the model is the treatment of the barrier crossing process by the electron within a…

Atomic Physics · Physics 2007-05-23 F. Sattin

We present cross sections for electron-impact-induced transitions n --> n' in hydrogen-like ions C 5+, Ne 9+, Al 12+, and Ar 17+. The cross sections are computed by Coulomb-Born with exchange and normalization (CBE) method for all…

We construct an effective low-energy Hamiltonian from the classical action via Monte Carlo with importance sampling. We use Monte Carlo (i) to compute matrix elements of the transition amplitude and (ii) to construct stochastically a basis.…

High Energy Physics - Lattice · Physics 2007-05-23 L. A. Caron , H. Kröger , G. Melkonyan , X. Q. Luo , K. J. M. Moriarty

This paper considers the problem of optimizing the average tracking error for an elliptic partial differential equation with an uncertain lognormal diffusion coefficient. In particular, the application of the multilevel quasi-Monte Carlo…

Numerical Analysis · Mathematics 2021-09-30 Philipp A. Guth , Andreas Van Barel

We derive, by introducing restrictions to the lesser self energy, a Monte Carlo scheme that solves the NEGF equations for electron transport. In doing so we formally prove that the Monte Carlo estimator has an expectation value equal to the…

Computational Physics · Physics 2018-05-28 Lars Musland , Espen Flage-Larsen , Joakim Bergli

In this work, we introduce a simple modification of the Monte Carlo algorithm, which we call step Monte Carlo (sMC). The sMC approach allows to simulate processes far from equilibrium and obtain information about the dynamic properties of…

Other Condensed Matter · Physics 2023-12-15 Dariusz Sztenkiel

We propose in this work a Monte Carlo method for three dimensional scalar radiative transfer equations with non-integrable, space-dependent scattering kernels. Such kernels typically account for long-range statistical features, and arise…

Numerical Analysis · Mathematics 2023-07-19 Christophe Gomez , Olivier Pinaud

Quantum Molecular Dynamics models (QMD) are Monte Carlo approaches targeted at the description of nucleon-ion and ion-ion collisions. We have developed a QMD code, which has been used for the simulation of the fast stage of ion-ion…

In stochastic processes with absorbing states, the quasi-stationary distribution provides valuable insights into the long-term behaviour prior to absorption. In this work, we revisit two well-established numerical methods for its…

Statistical Mechanics · Physics 2026-04-01 Sara Oliver-Bonafoux , Javier Aguilar , Tobias Galla , Raúl Toral

We propose an efficient method for Monte Carlo simulation of quantum lattice models. Unlike most other quantum Monte Carlo methods, a single run of the proposed method yields the free energy and the entropy with high precision for the whole…

Statistical Mechanics · Physics 2009-11-10 Chiaki Yamaguchi , Naoki Kawashima , Yutaka Okabe

Despite their formal simplicity, most lattice spin models cannot be easily solved, even under the simplifying assumptions of mean field theory. In this manuscript, we present a method for generating mean field solutions to classical…

Statistical Mechanics · Physics 2022-06-22 Yizhi Shen , Adam P. Willard

A Monte Carlo method for computing the action of a matrix exponential for a certain class of matrices on a vector is proposed. The method is based on generating random paths, which evolve through the indices of the matrix, governed by a…

Numerical Analysis · Mathematics 2019-06-19 Juan A. Acebron

Restricted Boltzmann Machines are simple and powerful generative models that can encode any complex dataset. Despite all their advantages, in practice the trainings are often unstable and it is difficult to assess their quality because the…

Machine Learning · Computer Science 2023-03-16 Nicolas Béreux , Aurélien Decelle , Cyril Furtlehner , Beatriz Seoane

We present a Monte Carlo method for simulating the inception of electric discharges in gases. The input consists of an unstructured grid containing the electrostatic field. The output of the model is the estimated probability of discharge…

Plasma Physics · Physics 2026-05-25 Jannis Teunissen , Yuting Gao

We review experimental and theoretical cross sections for electron scattering in nitric oxide (NO) and form a comprehensive set of plausible cross sections. To assess the accuracy and self-consistency of our set, we also review electron…

Chemical Physics · Physics 2021-10-26 Peter W. Stokes , Ronald D. White , Laurence Campbell , Michael J. Brunger

The shell-model Monte Carlo (SMMC) technique transforms the traditional nuclear shell-model problem into a path-integral over auxiliary fields. We describe below the method and its applications to four physics issues: calculations of sdpf-…

Nuclear Theory · Physics 2009-10-31 D. J. Dean , J. A. White

The seminal 2009 paper by Bernard, Krauth, and Wilson marked a paradigm shift in Monte Carlo sampling. By abandoning the restrictive condition of detailed balance in favor of the more fundamental principle of global balance, they introduced…

Computational Physics · Physics 2026-02-10 E. A. J. F. Peters

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the cumulative distribution function of a quantity of interest in problems with random input parameters or initial conditions. Our approach…

Numerical Analysis · Mathematics 2020-08-26 Søren Taverniers , Daniel M. Tartakovsky
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