**[Fall 2020]**

**Prerequisites**

Elementary probability (as in e.g. the first chapter of Grimmett and Welsh). Basic abstract analysis and measure theoretic probability (as given e.g. in the mastermath course ``measure theoretic probability’’).

**Content of the course**

This course provides and introduction to the theory of interacting particle systems, a class of interacting Markov processes used to model many real-world phenomena such as the spread of an infection (contact process), the evolution of opinions in a population (voter model), transport phenomena, and (non)-equilibrium statistical physics.

The course treats the following basic techniques

- Markov processes in continuous time, semigroups, generators, invariant and ergodic measures, martingales. Elements of the construction of a general class of interacting particle systems.
- Coupling, monotonicity and positive correlations
- Duality
- These basis techniques will then be applied in the context of the exclusion process, a basic interacting particle system used e.g. to model transport of molecules, and traffic.
- Depending on time we will treat the hydrodynamic limit (derivation of the heat equation starting from the exclusion process).

**Aims**

1. Learn the basic techniques of interacting particle systems and Markov process theory.

2. Being able to apply these techniques in the exclusion process and related models.

3. Being able to read a research paper with up to date techniques in this area and give a presentation about it.

**Lecturer and Educational method**

Instructor: Luca Avena (MI,Leiden)

The plan is to offer two hours of lecture per week, and two hours of time to start reading the project paper (in the beginning we might start with two week of 4 hours lecture, so that the acquired basic techniques are sufficient to start reading).

Since the course will be online, the lectures will be based on a mixture between recorded lectures prepared by Frank Redig in 2018 for the same mastermath course and lectures in streaming by Luca Avena.

- Docent: Rangel Baldasso