**Development of a generalized hybrid Monte Carlo algorithm to generate
the multicanonical ensemble with applications to molecular systems**

N Mukuta and S Miura, JOURNAL OF CHEMICAL PHYSICS, 149, 072322 (2018).

DOI: 10.1063/1.5028466

In the present paper, a generalized hybrid Monte Carlo method to
generate the multicanonical ensemble has been developed, which is a
generalization of the multicanonical hybrid Monte Carlo (HMC) method by
Hansmann and co-workers **Chem. Phys. Lett. 259, 321 (1996)**. The
generalized hybrid Monte Carlo (GHMC) method is an equations-of-motion
guided Monte Carlo combined with partial momentum refreshment. We
successfully applied our multicanonical GHMC to dense Lennard-Jones
fluids and a coarse grained protein model. It is found that good
computational efficiency can be gained in the case of the acceptance
ratio around 60% for the models examined. While a large number of
molecular dynamics (MD) steps in a single GHMC cycle is needed to yield
good computational efficiency at a large mixing ratio of momenta with
thermal noise vectors, corresponding to the original multicanonical HMC
method, a small number of MD steps are enough to achieve good efficiency
at a small mixing ratio. This property is useful to develop a composite
algorithm combining the present GHMC method with other Monte Carlo
moves. Published by AIP Publishing.

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