Numerical Methods for Stochastic Molecular Dynamics

  • Ben Leimkuhler
  • Charles Matthews
Part of the Interdisciplinary Applied Mathematics book series (IAM, volume 39)


In this chapter, we discuss principles for the design of algorithms for canonical sampling, based on the numerical discretization of stochastic dynamics models (such as Langevin dynamics) introduced in the previous chapter. Before we begin our discussion, let us consider the motivation for computing stationary averages using molecular dynamics.


Stochastic Differential Equation Potential Energy Function Invariant Distribution Langevin Dynamic Canonical Distribution 
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ben Leimkuhler
    • 1
  • Charles Matthews
    • 2
  1. 1.School of MathematicsUniversity of EdinburghEdinburghUK
  2. 2.Gordon Center for Integrative ScienceUniversity of ChicagoChicagoUSA

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