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Molecular dynamics algorithms are subject to some amount of error dependenton the size of the time step that is used. This error can be corrected byperiodically updating the system with a Metropolis criteria, where theintegration step is treated as a selection probability for candidate stategeneration. Such a method, closely related to generalized hybrid Monte Carlo(GHMC), satisfies the balance condition by imposing a reversal of momenta uponcandidate rejection. In the present study, we demonstrate that such momentumreversals can have a significant impact on molecular kinetics and extend thetime required for system decorrelation, resulting in an order of magnitudeincrease in the integrated autocorrelation times of molecular variables for theworst cases. We present a simple method, referred to as reduced-flipping GHMC,that uses the information of the previous, current, and candidate states toreduce the probability of momentum flipping following candidate rejection whilerigorously satisfying the balance condition. This method is a simplemodification to traditional, automatic-flipping, GHMC methods and significantlymitigates the impact of such algorithms on molecular kinetics and simulationmixing times.

Reducing the effect of Metropolization on mixing times in molecular dynamics simulations