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      Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics

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          Abstract

          We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise adaptive Langevin thermostat that precisely matches the dynamical characteristics of DPD simulations (e.g., autocorrelation functions) while automatically correcting thermodynamic averages using a negative feedback loop. In the low friction regime, it is possible to replace DPD by a simpler momentum-conserving variant of the Nos\'{e}--Hoover--Langevin method based on thermostatting only pairwise interactions; we show that this method has an extra order of accuracy for an important class of observables (a superconvergence result), while also allowing larger timesteps than alternatives. All the methods mentioned in the article are easily implemented. Numerical experiments are performed in both equilibrium and nonequilibrium settings; using Lees--Edwards boundary conditions to induce shear flow.

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          Lattice-Gas Automata for the Navier-Stokes Equation

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            Calculation of effective interaction potentials from radial distribution functions: A reverse Monte Carlo approach

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              Dense-fluid shear viscosity via nonequilibrium molecular dynamics

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                Author and article information

                Journal
                2016-07-28
                Article
                1607.08510
                ec018d5d-7c95-4b57-8049-099aea9cd63f

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                in Journal of Computational Physics (2016)
                physics.comp-ph

                Mathematical & Computational physics
                Mathematical & Computational physics

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