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We develop a path-integral dynamics method for water that resembles centroid molecular dynamics (CMD), except that the centroids are averages of curvilinear, rather than cartesian, bead coordinates. The curvilinear coordinates are used…

Chemical Physics · Physics 2019-09-04 George Trenins , Michael J. Willatt , Stuart C. Althorpe

We discuss the design of state-of-the-art numerical methods for molecular dynamics, focusing on the demands of soft matter simulation, where the purposes include sampling and dynamics calculations both in and out of equilibrium. We discuss…

Computational Physics · Physics 2020-02-14 Xiaocheng Shang , Martin Kröger , Benedict Leimkuhler

Particle-in-Cell (PIC) methods are widely used computational tools for fluid and kinetic plasma modeling. While both the fluid and kinetic PIC approaches have been successfully used to target either kinetic or fluid simulations, little was…

This paper is devoted to the study of quantum dissipation in cluster decay phenomena in the frame of the Lindblad approach to quantum open systems. The tunneling of a metastable state across a piecewise quadratic potential is envisaged for…

Quantum Physics · Physics 2016-09-08 S. Misicu

We frame the issue of pedestrian dynamics modeling in terms of path-integrals, a formalism originally introduced in quantum mechanics to account for the behavior of quantum particles, later extended to quantum field theories and to…

Physics and Society · Physics 2020-11-04 Alessandro Corbetta , Federico Toschi

The method to calculate the grand partition function of a particle system, in which constituents interact with each other via potential, that include repulsive and attractive components, is proposed. The cell model, which was introduced to…

Statistical Mechanics · Physics 2016-04-14 Mikhailo Kozlovskii , Oksana Dobush

This paper focuses on the temporal discretization of the Langevin dynamics, and on different resulting numerical integration schemes. Using a method based on the exponentiation of time dependent operators, we carefully derive a numerical…

Statistical Mechanics · Physics 2007-10-02 Fabrice Thalmann , Jean Farago

Two first-principles simulation techniques, path integral Monte Carlo (PIMC) and density functional molecular dynamics (DFT-MD), are applied to study hot, dense helium in the density-temperature range of 0.387 - 5.35 g/cc and 500 K -…

Materials Science · Physics 2015-05-13 B. Militzer

The calculation of thermal conductivity in insulating solids at temperatures below the Debye temperature is problematic, due to the breakdown of classical and semi-classical approaches. In this work, we present a fully quantum methodology…

Statistical Mechanics · Physics 2026-02-19 Vladislav Efremkin , Stefano Mossa , Jean-Louis Barrat , Markus Holzmann

A new Langevin-Verlet thermostat that preserves the fluctuation-dissipation relationship for discrete time steps, is applied to molecular modeling and tested against several popular suites (AMBER, GROMACS, LAMMPS) using a small molecule as…

Materials Science · Physics 2013-12-17 Niels Grønbech-Jensen , Natha Robert Hayre , Oded Farago

In this article we show in details the derivation of an integration scheme for the dissipative particle dynamic model (DPD) using the stochastic Trotter formula [De Fabritiis et al., Physica A, 361, 429 (2006)]. We explain some subtleties…

Soft Condensed Matter · Physics 2016-08-16 M. Serrano , G. De Fabritiis , P. Español , P. V. Coveney

Generalized Langevin Equation (GLE) thermostats have been used very effectively as a tool to manipulate and optimize the sampling of thermodynamic ensembles and the associated static properties. Here we show that a similar, exquisite level…

Chemical Physics · Physics 2017-09-06 Mariana Rossi , Venkat Kapil , Michele Ceriotti

Information about the nature of the low-temperature anomalies and in particular the properties of the tunneling systems in silica and lithium silica glasses are revealed via computer simulations. The potential energy landscape of these…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. Reinisch , A. Heuer

Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dynamics of biomolecules. This work presents a projection-based coarse-graining formalism for general…

Computational Physics · Physics 2026-05-28 Vahid Nateghi , Lara Neureither , Selma Moqvist , Carsten Hartmann , Simon Olsson , Feliks Nüske

The quantum harmonic oscillator is the fundamental building block to compute thermal properties of virtually any dielectric crystal at low temperatures in terms of phonons, extended further to cases with anharmonic couplings, or even…

Statistical Mechanics · Physics 2021-10-05 Vladislav Efremkin , Jean-Louis Barrat , Stefano Mossa , Markus Holzmann

We proposed a new technique to accelerate sampling methods for solving difficult optimization problems. Our method investigates the intrinsic connection between posterior distribution sampling and optimization with Langevin dynamics, and…

Machine Learning · Computer Science 2023-01-31 Junlong Lyu , Zhitang Chen , Wenlong Lyu , Jianye Hao

Warm dense matter (WDM) is an active field of research, with applications ranging from astrophysics to inertial confinement fusion. Ionization degree and continuum lowering are important quantities to understand how materials behave under…

Operator splitting methods tailored to coupled linear port-Hamiltonian systems are developed. We present algorithms that are able to exploit scalar coupling, as well as multirate potential of these coupled systems. The obtained algorithms…

Numerical Analysis · Mathematics 2025-01-14 Jan Lorenz , Tom Zwerschke , Michael Günther , Kevin Schäfers

The particle proper orthogonal decomposition (PPOD) is demonstrated on cases of particle flows in decaying homogeneous isotropic turbulence. Data is generated through one-way coupled simulations, where particle positions and velocities are…

Fluid Dynamics · Physics 2022-05-30 Martin Schiødt , Azur Hodzic , Fabien Evrard , Berend van Wachem , Clara M. Velte

Dissipative particle dynamics (DPD) is a novel particle method for mesoscale modeling of complex fluids. DPD particles are often thought to represent packets of real atoms, and the physical scale probed in DPD models are determined by the…

Chemical Physics · Physics 2016-10-18 R. Qiao , P. He