ArticleThe Journal of chemical physics2024
Accurate estimates of dynamical statistics using memory.
Article in The Journal of chemical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A continuous-space analytical framework for committor functions from molecular dynamics.The Journal of chemical physics · 2026Article
- Article
- An Exact Multiple-Time-Step Variational Formulation for the Committor and the Transition Rate.The journal of physical chemistry. B · 2026Article
- Analysis of the Dynamics of a Complex, Multipathway Reaction: Insulin Dimer Dissociation.The journal of physical chemistry. B · 2024Article
- Spectral Map for Slow Collective Variables, Markovian Dynamics, and Transition State Ensembles.Journal of chemical theory and computation · 2024Article
- BAD-NEUS: Rapidly converging trajectory stratification.The Journal of chemical physics · 2024Article
- Dynamics of activation in the voltage-sensing domain of Ciona intestinalis phosphatase Ci-VSP.Nature communications · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Many chemical reactions and molecular processes occur on time scales that are significantly longer than those accessible by direct simulations. One successful approach to estimating dynamical statistics for such processes is to use many short time series of observations of the system to construct a Markov state model, which approximates the dynamics of the system as memoryless transitions between a set of discrete states. The dynamical Galerkin approximation (DGA) is a closely related framework for estimating dynamical statistics, such as committors and mean first passage times, by approximating solutions to their equations with a projection onto a basis. Because the projected dynamics are generally not memoryless, the Markov approximation can result in significant systematic errors. Inspired by quasi-Markov state models, which employ the generalized master equation to encode memory resulting from the projection, we reformulate DGA to account for memory and analyze its performance on two systems: a two-dimensional triple well and the AIB9 peptide. We demonstrate that our method is robust to the choice of basis and can decrease the time series length required to obtain accurate kinetics by an order of magnitude.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.