Improving Sampling by Exchanging Hamiltonians with Efficiently Configured Nonequilibrium Simulations

Molecular simulations aim to sample all of the thermodynamically important states; when the sampling is inadequate, inaccuracy follows. A widely used technique to enhance sampling in simulations is Hamiltonian exchange. This technique introduces auxiliary Hamiltonians under which sampling is computationally efficient and attempts to exchange the molecular states among the auxiliary and the original Hamiltonians. The effectiveness of Hamiltonian exchange depends in part on the probability that the trial exchanges can be accepted, which involves good choices of auxiliary Hamiltonians and a good method of generating the trial exchanges. In this paper, we investigate nonequilibrium simulations as trial exchange generators and develop a theoretical model for the efficiency of Hamiltonian exchange and an algorithm to better configure such simulations. We show that properly configured nonequilibrium simulations can modestly increase the overall efficiency of Hamiltonian exchange