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Metropolis Importance Sampling for Rugged Dynamical Variables by Berg, Bernd A. is a scholarly article available to read on EtoBox.

What is Metropolis Importance Sampling for Rugged Dynamical Variables about?

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.

Author

Berg, Bernd A.

Published

2002

Language

EN