Computing the Committor with the Committor: an Anatomy of the Transition State Ensemble
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866918364469788672 |
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| author | Kang, Peilin Trizio, Enrico Parrinello, Michele |
| author_facet | Kang, Peilin Trizio, Enrico Parrinello, Michele |
| contents | Determining the kinetic bottlenecks that make transitions between metastable states difficult is key to understanding important physical problems like crystallization, chemical reactions, or protein folding. In all these phenomena, the system spends a considerable amount of time in one metastable state before making a rare but important transition to a new state. The rarity of these events makes their direct simulation challenging, if not impossible. We propose a method to explore the distribution of configurations that the system passes as it translocates from one metastable basin to another. We shall refer to this set of configurations as the transition state ensemble. We base our method on the committor function and the variational principle to which it obeys. We find the minimum of the variational principle via a self-consistent procedure that does not require any input besides the knowledge of the initial and final state. Right from the start, our procedure focuses on sampling the transition state ensemble and allows harnessing a large number of such configurations. With the help of the variational principle, we perform a detailed analysis of the transition state ensemble, ranking quantitatively the degrees of freedom mostly involved in the transition and opening the way for a systematic approach for the interpretation of simulation results and the construction of collective variables. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_05279 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Computing the Committor with the Committor: an Anatomy of the Transition State Ensemble Kang, Peilin Trizio, Enrico Parrinello, Michele Computational Physics Statistical Mechanics Determining the kinetic bottlenecks that make transitions between metastable states difficult is key to understanding important physical problems like crystallization, chemical reactions, or protein folding. In all these phenomena, the system spends a considerable amount of time in one metastable state before making a rare but important transition to a new state. The rarity of these events makes their direct simulation challenging, if not impossible. We propose a method to explore the distribution of configurations that the system passes as it translocates from one metastable basin to another. We shall refer to this set of configurations as the transition state ensemble. We base our method on the committor function and the variational principle to which it obeys. We find the minimum of the variational principle via a self-consistent procedure that does not require any input besides the knowledge of the initial and final state. Right from the start, our procedure focuses on sampling the transition state ensemble and allows harnessing a large number of such configurations. With the help of the variational principle, we perform a detailed analysis of the transition state ensemble, ranking quantitatively the degrees of freedom mostly involved in the transition and opening the way for a systematic approach for the interpretation of simulation results and the construction of collective variables. |
| title | Computing the Committor with the Committor: an Anatomy of the Transition State Ensemble |
| topic | Computational Physics Statistical Mechanics |
| url | https://arxiv.org/abs/2401.05279 |