MATH-487 / 6 credits

Teacher: Li-Hairer Xue-Mei

Language: English


Summary

This course develops a rigorous foundation in stochastic processes, limit theorems, and stochastic dynamics, with an emphasis on tools for analyzing systems across multiple scales.

Content

Gaussian Measures, Gaussian stochastic processes, mixing and erdocity, ergodic theorems, averaging, diffusion and rough generation, slow/fast Stochastic differential equations, and possibly rough differential equations.

Keywords

Gaussian processes, self-similar processes, stationary processes, invariant measures, ergodicity, strong mixing,  limit theorems, Brownian motions and fractional Brownian motions,  rough paths,  stochastic dynamics,  stochastic differntial equations, rough differential equations.

Learning Prerequisites

Required courses

Required background knowledge:  Analysis I-IV, Probability.

Knowledge of the following are useful: stochactic integrals,   differntiale equations, Banach spaces, metric spaces.

Important concepts to start the course

Brownian motion, Stochastic Processes

Teaching methods

Weekly lectures and exercise sessions with assistant

Assessment methods

Oral

Supervision

Office hours No
Assistant.e.s Yes
Forum No

Resources

Moodle Link

In the programs

  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Introduction to multi-scale stochastic dynamics
  • Courses: 3 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: optional
  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Introduction to multi-scale stochastic dynamics
  • Courses: 3 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: optional
  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Introduction to multi-scale stochastic dynamics
  • Courses: 3 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: optional
  • Semester: Fall
  • Exam form: Oral (winter session)
  • Subject examined: Introduction to multi-scale stochastic dynamics
  • Courses: 3 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: optional

Reference week

Tuesday, 10h - 12h: Lecture GRA332

Wednesday, 9h - 10h: Lecture MAA331

Friday, 13h - 15h: Exercise, TP MAA331

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