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<p>The problem of studying rare events is central to many areas of computer simulations. We recently proposed an approach to solving this problem that involves computing the committor function, showing how it can be iteratively computed in a variational way while efficiently sampling the transition state ensemble. Here we greatly improve this procedure by combining it with a metadynamics-like enhanced sampling approach in which a logarithmic function of the committor is used as a collective variable. This procedure leads to an accurate sampling of the free energy surface in which transition states and metastable basins are studied with the same thoroughness. We show that our approach can be used in cases with the possibility of competing reactive paths and metastable intermediates. In addition, we demonstrate how physical insights can be obtained from the optimized committor model and the sampled data, thus providing a full characterization of the rare event under study.</p>

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Everything everywhere all at once: a probability-based enhanced sampling approach to rare events

  • 期刊论文

  • 发表日期：

    2025年5月5日

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  • Enrico Trizio,
  • Peilin Kang,
  • Michele Parrinello

摘要

The problem of studying rare events is central to many areas of computer simulations. We recently proposed an approach to solving this problem that involves computing the committor function, showing how it can be iteratively computed in a variational way while efficiently sampling the transition state ensemble. Here we greatly improve this procedure by combining it with a metadynamics-like enhanced sampling approach in which a logarithmic function of the committor is used as a collective variable. This procedure leads to an accurate sampling of the free energy surface in which transition states and metastable basins are studied with the same thoroughness. We show that our approach can be used in cases with the possibility of competing reactive paths and metastable intermediates. In addition, we demonstrate how physical insights can be obtained from the optimized committor model and the sampled data, thus providing a full characterization of the rare event under study.