Organized By:
Alexei Borodin (MIT)
Ivan Corwin (Columbia)
Evita Nestoridi (Stony Brook)
Much of probability theory is concerned with understanding phenomena and structure that emerges in large, complex systems driven by disorder. This understanding is often first established for special example systems that are analyzable due to hidden connections to algebra. This summer workshop will focus on these hidden connections. Through a combination of mini-courses, lectures, and extensive time for discussion and collaboration, the workshop will bring together communities that are often concerned with different questions or probabilistic models, and focus them on the common ground within their methods.
Examples of the types of hidden structures and related probabilistic models include:
- Representation theory in Markov chain mixing and card shuffling.
- Quantum integrable systems and symmetric function theory in stochastic vertex models, random matrix theory, interacting particle systems and the Kardar-Parisi-Zhang universality class.
- Lax matrices in integrable systems driven by randomness or random initial data.