Accurate and efficient splitting methods for dissipative particle dynamics

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We study numerical methods for dissipative particle dynamics (DPD), which is a system of stochastic differential equations and a popular stochastic momentum-conserving thermostat for simulating complex hydrodynamic behavior at mesoscales. We propose a new splitting method that is able to substantially improve the accuracy and efficiency of DPD simulations in a wide range of the friction coefficients, particularly in the extremely large friction limit that corresponds to a fluid-like Schmidt number, a key issue in DPD. Various numerical experiments on both equilibrium and transport properties are performed to demonstrate the superiority of the newly proposed method over popular alternative schemes in the literature.
Original languageEnglish
Article numberA1929–A1949
Pages (from-to)A1929-A1949
Number of pages21
JournalSIAM Journal on Scientific Computing
Issue number3
Publication statusPublished - 27 May 2021


  • Dissipative particle dynamics
  • Invariant measure
  • Order of convergence
  • Splitting methods
  • Stochastic differential equations
  • Transport properties

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


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