ArticleThe Journal of chemical physics2012
Markov processes follow from the principle of maximum caliber.
Article in The Journal of chemical physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Inferring effective neuronal circuits via network flux counting.PLoS computational biology · 2026Article
- A principled basis for nonequilibrium network flows.Nature communications · 2026Article
- Modeling and inferring metacommunity dynamics with Maximum Caliber.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Information Content and Maximum Entropy of Compartmental Systems in Equilibrium.Entropy (Basel, Switzerland) · 2025Article
- Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model.Nature communications · 2023Article
- Path sampling of recurrent neural networks by incorporating known physics.Nature communications · 2022Article
- The Maximum Caliber Variational Principle for Nonequilibria.Annual review of physical chemistry · 2020Review
- An efficient strategy to estimate thermodynamics and kinetics of G protein-coupled receptor activation using metadynamics and maximum caliber.The Journal of chemical physics · 2018Article
- An introduction to the maximum entropy approach and its application to inference problems in biology.Heliyon · 2018Review
- Building Predictive Models of Genetic Circuits Using the Principle of Maximum Caliber.Biophysical journal · 2017Article
- Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.PLoS computational biology · 2017Article
- Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis.Chemical reviews · 2017Article
- High-Dimensional Mutant and Modular Thermodynamic Cycles, Molecular Switching, and Free Energy Transduction.Annual review of biophysics · 2017Review
- Stochastic sensitivity analysis and kernel inference via distributional data.Biophysical journal · 2014Article
- Single molecule conformational memory extraction: p5ab RNA hairpin.The journal of physical chemistry. B · 2014Article
- A derivation of the master equation from path entropy maximization.The Journal of chemical physics · 2012Article
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Authors and funding
4 authors.
Funding
Abstract
Markov models are widely used to describe stochastic dynamics. Here, we show that Markov models follow directly from the dynamical principle of maximum caliber (Max Cal). Max Cal is a method of deriving dynamical models based on maximizing the path entropy subject to dynamical constraints. We give three different cases. First, we show that if constraints (or data) are given in the form of singlet statistics (average occupation probabilities), then maximizing the caliber predicts a time-independent process that is modeled by identical, independently distributed random variables. Second, we show that if constraints are given in the form of sequential pairwise statistics, then maximizing the caliber dictates that the kinetic process will be Markovian with a uniform initial distribution. Third, if the initial distribution is known and is not uniform we show that the only process that maximizes the path entropy is still the Markov process. We give an example of how Max Cal can be used to discriminate between different dynamical models given data.
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