Rare event sampling with stochastic growth algorithms

We discuss uniform sampling algorithms that are based on stochastic growth methods, using sampling of extreme configurations of polymers in simple lattice models as a motivation. We shall show how a series of clever enhancements to a fifty-odd year old algorithm, the Rosenbluth method, led to a cutt...

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Main Author:	Prellberg Thomas
Format:	Article
Language:	English
Published:	EDP Sciences 2013-03-01
Series:	EPJ Web of Conferences
Online Access:	http://dx.doi.org/10.1051/epjconf/20134401001

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spelling	doaj-35516bcc19ad49429c42b4cb76202b222021-08-02T04:06:30ZengEDP SciencesEPJ Web of Conferences2100-014X2013-03-01440100110.1051/epjconf/20134401001Rare event sampling with stochastic growth algorithmsPrellberg ThomasWe discuss uniform sampling algorithms that are based on stochastic growth methods, using sampling of extreme configurations of polymers in simple lattice models as a motivation. We shall show how a series of clever enhancements to a fifty-odd year old algorithm, the Rosenbluth method, led to a cutting-edge algorithm capable of uniform sampling of equilibrium statistical mechanical systems of polymers in situations where competing algorithms failed to perform well. Examples range from collapsed homo-polymers near sticky surfaces to models of protein folding. http://dx.doi.org/10.1051/epjconf/20134401001
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Prellberg Thomas
spellingShingle	Prellberg Thomas Rare event sampling with stochastic growth algorithms EPJ Web of Conferences
author_facet	Prellberg Thomas
author_sort	Prellberg Thomas
title	Rare event sampling with stochastic growth algorithms
title_short	Rare event sampling with stochastic growth algorithms
title_full	Rare event sampling with stochastic growth algorithms
title_fullStr	Rare event sampling with stochastic growth algorithms
title_full_unstemmed	Rare event sampling with stochastic growth algorithms
title_sort	rare event sampling with stochastic growth algorithms
publisher	EDP Sciences
series	EPJ Web of Conferences
issn	2100-014X
publishDate	2013-03-01
description	We discuss uniform sampling algorithms that are based on stochastic growth methods, using sampling of extreme configurations of polymers in simple lattice models as a motivation. We shall show how a series of clever enhancements to a fifty-odd year old algorithm, the Rosenbluth method, led to a cutting-edge algorithm capable of uniform sampling of equilibrium statistical mechanical systems of polymers in situations where competing algorithms failed to perform well. Examples range from collapsed homo-polymers near sticky surfaces to models of protein folding.
url	http://dx.doi.org/10.1051/epjconf/20134401001
work_keys_str_mv	AT prellbergthomas rareeventsamplingwithstochasticgrowthalgorithms
_version_	1721242689369800704

Rare event sampling with stochastic growth algorithms

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