Maximum Entropy Principle of Markov Processes and its connection to Stochastic Thermodynamics

Synopsis

Maximum Entropy Principle (Max Ent) is a generative principle in statistical physics that produces probabilistic models (Bolztmann distribution) and derives thermodynamic relations. It has been generalized to build models for not just state distributions but also stochastic dynamics. I will briefly introduce the historic derivation of Max Ent, and then connect the thermodynamics it derived to stochastic thermodynamics. Simple molecular motor examples will be used to demonstrate our theoretical results as well as how Max Ent can be used with experimental data.