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Obtaining reaction coordinates by likelihood maximization

Peters, Baron, Trout, Bernhardt L.·2006·The Journal of Chemical Physics

DOI 10.1063/1.2234477

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Abstract

We present a new approach for calculating reaction coordinates in complex systems. The new method is based on transition path sampling and likelihood maximization. It requires fewer trajectories than a single iteration of existing procedures, and it applies to both low and high friction dynamics. The new method screens a set of candidate collective variables for a good reaction coordinate that depends on a few relevant variables. The Bayesian information criterion determines whether additional variables significantly improve the reaction coordinate. Additionally, we present an advantageous transition path sampling algorithm and an algorithm to generate the most likely transition path in the space of collective variables. The method is demonstrated on two systems: a bistable model potential energy surface and nucleation in the Ising model. For the Ising model of nucleation, we quantify for the first time the role of nuclei surface area in the nucleation reaction coordinate. Surprisingly, increased surface area increases the stability of nuclei in two dimensions but decreases nuclei stability in three dimensions.

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1978, Ann. Stat., 6, 461
1996, Metastable Liquids

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Authors: Peters, B., & Trout, B. L.
Affiliations: Massachusetts Institute of Technology (US)
ORCID: Peters, Baron
Trout, Bernhardt L.
Venue: The Journal of Chemical Physics
Publisher: AIP Publishing
Published: 2006-08-04
Volume: 125
Issue: 5
Pages: 054108-054108
ISSN: 0021-9606 (ISSN-L)
1089-7690
DOI: 10.1063/1.2234477
OpenAlex: W2011242225
Cited by: 417
References: 45
Citations by year: 2026: 15 · 2025: 20 · 2024: 22 · 2023: 41 · 2022: 22 · 2021: 23 · 2020: 26 · 2019: 21 · 2018: 19 · 2017: 50 · 2016: 27 · 2015: 23 · 2014: 14 · 2013: 13 · 2012: 15
FWCI: 6.61
Type: journal article
Language: en
Open access: closed
Locations: The Journal of Chemical Physics (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
Keywords: reaction coordinate, transition path sampling, likelihood maximization, collective variables, Bayesian information criterion, nucleation, Ising model, surface area effect

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Obtaining reaction coordinates by likelihood maximization

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