Summary
This year we will be looking into probabilistic study of some models of mathematical physics.
Content
We will consider some probabilistic models of mathematical physics and try to understand them as deeply as we can. The prime example will be the lattice Yang-Mills model, but we will have to also look at other models like the Ising model or Brownian motion to develop some tools.
Keywords
High-dimensional probability, concentration of measure, Gaussian processes, phase transitions, universality
Learning Prerequisites
Required courses
Mathematics Bachelor's level knowledge of analysis, linear algebra and probability.
Recommended courses
Knowledge of basic measure theory will simplify your life a lot. Interest in mathematical physics, combinatorics and geometry is of use.
Important concepts to start the course
Probability space, random variable and random vector, expectation, Gaussian random variables.
Teaching methods
Lectures, exercise classes. Maybe on some topics we also try a flipped format, where you can give a presentation.
Assessment methods
Most likely an oral exam, but in case of presentations, these would also count towards the final grade.
Resources
Bibliography
Will be discussed in class
Notes/Handbook
There might be partial notes, though the book is excellent.
In the programs
- Semester: Spring
- Exam form: Oral (summer session)
- Subject examined:
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Semester: Spring
- Exam form: Oral (summer session)
- Subject examined:
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Semester: Spring
- Exam form: Oral (summer session)
- Subject examined:
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
Reference week
| Mo | Tu | We | Th | Fr | |
| 8-9 | |||||
| 9-10 | |||||
| 10-11 | |||||
| 11-12 | |||||
| 12-13 | |||||
| 13-14 | |||||
| 14-15 | |||||
| 15-16 | |||||
| 16-17 | |||||
| 17-18 | |||||
| 18-19 | |||||
| 19-20 | |||||
| 20-21 | |||||
| 21-22 |
Légendes:
Lecture
Exercise, TP
Project, other