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  <doc>
    <id>4878</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>350</pageFirst>
    <pageLast>376</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>16</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
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    <title language="eng">Characterization of Rare Events in Molecular Dynamics</title>
    <parentTitle language="eng">Entropy (Special Issue)</parentTitle>
    <identifier type="doi">10.3390/e16010350</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="PreprintUrn">urn:nbn:de:0297-zib-42410</enrichment>
    <enrichment key="SourceTitle">Appeared in: Entropy (Special Issue), 16 (2013), pp. 350-376</enrichment>
    <author>Carsten Hartmann</author>
    <submitter>Erlinda Körnig</submitter>
    <author>Ralf Banisch</author>
    <author>Marco Sarich</author>
    <author>Thomas Badowski</author>
    <author>Christof Schütte</author>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="persons" number="schuette">Schütte, Christof</collection>
  </doc>
  <doc>
    <id>4241</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
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    <type>reportzib</type>
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    <completedDate>2013-09-11</completedDate>
    <publishedDate>2013-09-11</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Characterization of Rare Events in Molecular Dynamics</title>
    <abstract language="eng">A good deal of molecular dynamics simulations aims at predicting and quantifying rare events, such as the folding of a protein or a phase transition. Simulating rare events is often prohibitive, especially if the equations of motion are high-dimensional, as is the case in molecular dynamics. Various algorithms have been proposed for efficiently computing mean first passage times, transition rates or reaction pathways. This article surveys and discusses recent developments in the field of rare event simulation and outlines a new approach that combines ideas from optimal control and statistical mechanics. The optimal control approach described in detail resembles the use of Jarzynski's equality for free energy calculations, but with an optimized protocol that speeds up the sampling, while (theoretically) giving variance-free estimators of the rare events statistics. We illustrate the new approach with two numerical examples and discuss its relation to existing methods.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-42410</identifier>
    <enrichment key="SourceTitle">Appeared in Entropy (Special Issue), 16 (1)</enrichment>
    <author>Carsten Hartmann</author>
    <submitter>Erlinda Körnig</submitter>
    <author>Ralf Banisch</author>
    <author>Marco Sarich</author>
    <author>Thomas Badowski</author>
    <author>Christof Schütte</author>
    <series>
      <title>ZIB-Report</title>
      <number>13-51</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rare events</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>moleculare dynamics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>optimal pathways</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>stochastic control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>dynamic programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>change of measure</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>cumulant generating function</value>
    </subject>
    <collection role="msc" number="49M20">Methods of relaxation type</collection>
    <collection role="msc" number="60J45">Probabilistic potential theory [See also 31Cxx, 31D05]</collection>
    <collection role="msc" number="82C31">Stochastic methods (Fokker-Planck, Langevin, etc.) [See also 60H10]</collection>
    <collection role="msc" number="93E20">Optimal stochastic control</collection>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="persons" number="schuette">Schütte, Christof</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/4241/ZIB-Report13-51.pdf</file>
  </doc>
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