- About Us
- People
- Undergrad
- Graduate
- Research
- News & Events
- Outreach
- Equity
- _how-to
- Congratulations to our Class of 2021
- Archive
- AKCSE
- Atlas Tier 1 Data Centre
Biophysics and Soft Matter Seminar
Maximum Entropy Principle of Markov Processes and its connection to Stochastic Thermodynamics
Ying-Jen Yang, Laufer Center for Physical and Quantitative Biology, Stony Brook U
Location: P8445.2
Monday, 24 April 2023 01:30PM PDT
Copy
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.