arXiv · cond-mat/0209413
Metropolis Importance Sampling for Rugged Dynamical Variables
Abstract
A funnel transformation is introduced, which acts recursively from higher towards lower temperatures. It biases the a-priori probabilities of a canonical or generalized ensemble Metropolis simulation, so that they zoom in on the global energy minimum, if a funnel exists indeed. A first, crude approximation to the full transformation, called rugged Metropolis one (RM$_1$), is tested for Met-Enkephalin. At 300$ $K the computational gain is a factor of two and, due to its simplicity, RM$_1$ is well suited to replace the conventional Metropolis updating for these kind of systems.
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Bernd A. Berg. 2003-03-24. Metropolis Importance Sampling for Rugged Dynamical Variables. https://doi.org/10.1103/physrevlett.90.180601
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