Abstract
The parallel tempering simulation method was recently extended to allow for possible exchanges between non-adjacent replicas. We introduce a multiple-exchange variant which naturally incorporates the information from all replicas when calculating statistical averages, building on the related virtual-move method of Coluzza and Frenkel (ChemPhysChem 2005, 6, 1779). The method is extensively tested on three model systems, namely, a Lennard-Jones cluster exhibiting a finite size phase transition, the Lennard-Jones fluid, and the 2D ferromagnetic Ising model. In all cases, the present method performs significantly better and converges faster than conventional parallel tempering Monte Carlo simulations. The standard deviations are also systematically decreased with respect to virtual moves.
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