Accelerating the convergence of replica exchange simulations using Gibbs sampling and adaptive temperature sets

TL;DR

This paper introduces an advanced replica-exchange simulation method that utilizes Gibbs sampling and adaptive temperature sets, enabling faster convergence and improved estimation of thermodynamic properties like the density of states.

Contribution

The paper presents a novel replica-exchange scheme that allows replicas to sample from past states via a global database and adapt temperature sets dynamically.

Findings

Enables rapid propagation of relevant states across replicas

Improves estimation of microcanonical temperature T(U) and density of states g(U)

Demonstrates enhanced convergence and reliability in simulations

Abstract

We recently introduced a novel replica-exchange scheme in which an individual replica can sample from states encountered by other replicas at any previous time by way of a global configuration database, enabling the fast propagation of relevant states through the whole ensemble of replicas. This mechanism depends on the knowledge of global thermodynamic functions which are measured during the simulation and not coupled to the heat bath temperatures driving the individual simulations. Therefore, this setup also allows for a continuous adaptation of the temperature set. In this paper, we will review the new scheme and demonstrate its capability. The method is particularly useful for the fast and reliable estimation of the microcanonical temperature T(U) or, equivalently, of the density of states g(U) over a wide range of energies.