Canonical sampling through velocity rescaling

TLDR

The authors introduce a new molecular dynamics algorithm to sample the canonical distribution. The algorithm rescales particle velocities by a random factor, defines a conserved quantity to assess sampling accuracy, and is demonstrated on Lennard‑Jones and TIP4P water models. The method is formally justified, preserves a conserved quantity despite stochasticity, and shows excellent, thermostat‑parameter‑independent performance, including accurate dynamic properties.

Abstract

The authors present a new molecular dynamics algorithm for sampling the canonical distribution. In this approach the velocities of all the particles are rescaled by a properly chosen random factor. The algorithm is formally justified and it is shown that, in spite of its stochastic nature, a quantity can still be defined that remains constant during the evolution. In numerical applications this quantity can be used to measure the accuracy of the sampling. The authors illustrate the properties of this new method on Lennard-Jones and TIP4P water models in the solid and liquid phases. Its performance is excellent and largely independent of the thermostat parameter also with regard to the dynamic properties.