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In this work, we developed an efficient approach to compute ensemble averages in systems with pairwise-additive energetic interactions between the entities. Methods involving full enumeration of the configuration space result in exponential…

Biomolecules · Quantitative Biology 2020-10-13 Arun V. Sathanur , Nathan A. Baker

Mean-field molecular dynamics based on path integrals is used to approximate canonical quantum observables for particle systems consisting of nuclei and electrons. A computational bottleneck is the sampling from the Gibbs density of the…

Numerical Analysis · Mathematics 2023-11-30 Xin Huang , Petr Plechac , Mattias Sandberg , Anders Szepessy

The strongly coupled electron liquid provides a unique opportunity to study the complex interplay of strong coupling with quantum degeneracy effects and thermal excitations. To this end, we carry out extensive \textit{ab initio} path…

Computational Physics · Physics 2020-02-05 Tobias Dornheim , Travis Sjostrom , Shigenori Tanaka , Jan Vorberger

The numerically exact path integral Monte Carlo approach for the real-time evolution of dissipative quantum systems (PIMC), particularly suited for systems with discrete configuration space (tight-binding systems), is extended to treat…

Statistical Mechanics · Physics 2009-11-11 Lothar Muehlbacher , Charlotte Escher , Joachim Ankerhold

In regimes of low signal strengths and therefore a small signal-to-noise ratio, standard data analysis methods often fail to accurately estimate system properties. We present a method based on Monte Carlo simulations to effectively restore…

A technique for reducing the number of integrals in a Monte Carlo calculation is introduced. For integrations relying on classical or mean-field trajectories with local weighting functions, it is possible to integrate analytically at least…

Statistical Mechanics · Physics 2024-05-17 Jarod Tall , Steven Tomsovic

We present in this paper a hybrid, Multi-Level Monte Carlo (MLMC) method for solving the neutral particle transport equation. MLMC methods, originally developed to solve parametric integration problems, work by using a cheap, low fidelity…

Numerical Analysis · Mathematics 2025-08-06 Vincent N. Novellino , Dmitriy Y. Anistratov

We propose the powerful integration of the Hybrid Monte Carlo (hybridMC) algorithm and Well-Tempered Metadynamics. This new algorithm, hybridMC-MetaD, enhances the flexibility and applicability of metadynamics by allowing for the…

Materials Science · Physics 2025-08-25 Charlotte Shiqi Zhao , Sun-Ting Tsai , Sharon C. Glotzer

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have…

Computational Physics · Physics 2007-05-23 David Ceperley , Mark Dewing , Carlo Pierleoni

We introduce a general Monte Carlo scheme for achieving atomistic simulations with monoelectronic Hamiltonians including the thermalization of both nuclear and electronic degrees of freedom. The kinetic Monte Carlo algorithm is used to…

Materials Science · Physics 2009-11-07 F. Calvo , F. Spiegelman

We present a multi-level delumping method suitable for thermal enhanced oil recovery processes, for which hydrocarbon components are vaporized under high temperatures, move downstream in the gas phase and condense back to the liquid phase.…

Computational Physics · Physics 2020-10-06 Matthias A. Cremon , Margot G. Gerritsen

The new {\em ab initio} quantum path integral Monte Carlo approach has been developed and applied for the entropy difference calculations for the strongly coupled degenerated uniform electron gas (UEG), a well--known model of simple metals.…

Plasma Physics · Physics 2021-07-28 Vladimir Filinov , Pavel Levashov , Alexander Larkin

Efficient sampling from ensembles of Hamiltonian cycles is critical for predicting the thermodynamic properties of compact polymers, with applications including modeling protein and RNA folding and designing soft materials. Although…

Quantum Physics · Physics 2026-03-16 Davide Rattacaso , Daniel Jaschke , Antonio Trovato , Ilaria Siloi , Simone Montangero

In Markov Chain Monte Carlo (MCMC) simulations, the thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples. These samples are selected in accordance with the…

Data Analysis, Statistics and Probability · Physics 2015-01-08 J. Li , P. Vignal , S. Sun , V. M. Calo

Sampling from multimodal distributions is a challenging task in scientific computing. When a distribution has an exact symmetry between the modes, direct jumps among them can accelerate the samplings significantly. However, the…

Numerical Analysis · Mathematics 2024-01-05 Lexing Ying

We propose extensions and improvements of the statistical analysis of distributed multipoles (SADM) algorithm put forth by Chipot et al. in [6] for the derivation of distributed atomic multipoles from the quantum-mechanical electrostatic…

Numerical Analysis · Mathematics 2010-07-28 Nicolas Champagnat , Christophe Chipot , Erwan Faou

The subsurface flow is usually subject to uncertain porous media structures. In most cases, however, we only have partial knowledge about the porous media properties. A common approach is to model the uncertain parameters of porous media as…

Numerical Analysis · Mathematics 2019-10-11 Yang Liu , Jingfa Li , Shuyu Sun , Bo Yu

We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev.…

Statistical Mechanics · Physics 2019-02-13 Pablo M. Piaggi , Michele Parrinello

We report the quantum phase diagram of a one-dimensional Coulomb wire obtained using the path integral Monte Carlo (PIMC) method. The exact knowledge of the nodal points of this system permits us to find the energy in an exact way, solving…

Quantum Gases · Physics 2016-01-20 G. Ferre , G. E. Astrakharchik , J. Boronat

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