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

Benedict Leimkuhler, Xiaocheng Shang

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
103 Downloads (Pure)


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 Nosé–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.
Original languageEnglish
Pages (from-to)174-193
JournalJournal of Computational Physics
Early online date29 Jul 2016
Publication statusPublished - 1 Nov 2016


  • dissipative particle dynamics
  • pairwise Nosé–Hoover–Langevin thermostat
  • pairwise adaptive Langevin thermostat
  • order of convergence
  • configurational temperature
  • momentum conservation
  • stochastic differential equations
  • molecular dynamics


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