TY - JOUR
T1 - Stochastic Resetting for Enhanced Sampling
AU - Blumer, Ofir
AU - Reuveni, Shlomi
AU - Hirshberg, Barak
N1 - Publisher Copyright:
© 2022 The Authors. Published by American Chemical Society.
PY - 2022/12/8
Y1 - 2022/12/8
N2 - We present a method for enhanced sampling of molecular dynamics simulations using stochastic resetting. Various phenomena, ranging from crystal nucleation to protein folding, occur on time scales that are unreachable in standard simulations. They are often characterized by broad transition time distributions, in which extremely slow events have a non-negligible probability. Stochastic resetting, i.e., restarting simulations at random times, was recently shown to significantly expedite processes that follow such distributions. Here, we employ resetting for enhanced sampling of molecular simulations for the first time. We show that it accelerates long time scale processes by up to an order of magnitude in examples ranging from simple models to a molecular system. Most importantly, we recover the mean transition time without resetting, which is typically too long to be sampled directly, from accelerated simulations at a single restart rate. Stochastic resetting can be used as a standalone method or combined with other sampling algorithms to further accelerate simulations.
AB - We present a method for enhanced sampling of molecular dynamics simulations using stochastic resetting. Various phenomena, ranging from crystal nucleation to protein folding, occur on time scales that are unreachable in standard simulations. They are often characterized by broad transition time distributions, in which extremely slow events have a non-negligible probability. Stochastic resetting, i.e., restarting simulations at random times, was recently shown to significantly expedite processes that follow such distributions. Here, we employ resetting for enhanced sampling of molecular simulations for the first time. We show that it accelerates long time scale processes by up to an order of magnitude in examples ranging from simple models to a molecular system. Most importantly, we recover the mean transition time without resetting, which is typically too long to be sampled directly, from accelerated simulations at a single restart rate. Stochastic resetting can be used as a standalone method or combined with other sampling algorithms to further accelerate simulations.
UR - http://www.scopus.com/inward/record.url?scp=85143410530&partnerID=8YFLogxK
U2 - 10.1021/acs.jpclett.2c03055
DO - 10.1021/acs.jpclett.2c03055
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C2 - 36446130
AN - SCOPUS:85143410530
SN - 1948-7185
VL - 13
SP - 11230
EP - 11236
JO - Journal of Physical Chemistry Letters
JF - Journal of Physical Chemistry Letters
IS - 48
ER -