TY - JOUR
T1 - Efficient dynamic importance sampling of rare events in one dimension
AU - Zuckerman, Daniel M.
AU - Woolf, Thomas B.
PY - 2001
Y1 - 2001
N2 - Exploiting stochastic path-integral theory, we obtain by simulation substantial gains in efficiency for the computation of reaction rates in one-dimensional, bistable, overdamped stochastic systems. Using a well-defined measure of efficiency, we compare implementations of “dynamic importance sampling” (DIMS) methods to unbiased simulation. The best DIMS algorithms are shown to increase efficiency by factors of approximately 20 for a (Formula presented) barrier height and 300 for (Formula presented) compared to unbiased simulation. The gains result from close emulation of natural (unbiased), instantonlike crossing events with artificially decreased waiting times between events that are corrected for in rate calculations. The artificial crossing events are generated using the closed-form solution to the most probable crossing event described by the Onsager-Machlup action. While the best biasing methods require the second derivative of the potential (resulting from the “Jacobian” term in the action, which is discussed at length), algorithms employing solely the first derivative do nearly as well. We discuss the importance of one-dimensional models to larger systems, and suggest extensions to higher-dimensional systems.
AB - Exploiting stochastic path-integral theory, we obtain by simulation substantial gains in efficiency for the computation of reaction rates in one-dimensional, bistable, overdamped stochastic systems. Using a well-defined measure of efficiency, we compare implementations of “dynamic importance sampling” (DIMS) methods to unbiased simulation. The best DIMS algorithms are shown to increase efficiency by factors of approximately 20 for a (Formula presented) barrier height and 300 for (Formula presented) compared to unbiased simulation. The gains result from close emulation of natural (unbiased), instantonlike crossing events with artificially decreased waiting times between events that are corrected for in rate calculations. The artificial crossing events are generated using the closed-form solution to the most probable crossing event described by the Onsager-Machlup action. While the best biasing methods require the second derivative of the potential (resulting from the “Jacobian” term in the action, which is discussed at length), algorithms employing solely the first derivative do nearly as well. We discuss the importance of one-dimensional models to larger systems, and suggest extensions to higher-dimensional systems.
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U2 - 10.1103/PhysRevE.63.016702
DO - 10.1103/PhysRevE.63.016702
M3 - Article
C2 - 11304388
AN - SCOPUS:20444367704
SN - 1063-651X
VL - 63
JO - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
JF - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
IS - 1
ER -