Virtual-move Parallel Tempering
Frenkel, Ivan Coluzza Daan
Original · EN
We report a novel Monte Carlo scheme that greatly enhances the power of parallel-tempering simulations. In this method, we boost the accumulation of statistical averages by including information about all potential parallel tempering trial moves, rather than just those trial moves that are accepted. As a test, we compute the free-energy landscape for conformational changes in simple model proteins. With the new technique, the sampled region of the configurational space in which the free-energy landscape could be reliably estimated, increases by a factor 20.
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