Math 106 Stochastic processes

Schedule

Unless otherwise noted all readings are from Applied Stochastic Analysis by E, Li and Vanden-Eijnden. Other textbooks are given on the home page. Click the Week links for details on what we cover and suggestions on navigating the readings. I will update these the Friday before we cover the material. Remember to refresh the webpage throughout the term!

The exercises listed on the Weekly pages should be completed by the Monday of the following week. They are not collected, but they are essential for exam preparation. It is strongly recommended that you attempt all exercises in the text related to the material we cover. I may add additional exercises while the material is being covered. If you cannot obtain a solution in a reasonable amount of time on your own, you may use ChatGPT for assistance or come to office hours.

Day Date Topics Readings
W1
Tue Jan 6 No Class (meet Xhours)
Thu Jan 8 Probability warm-up, Discrete-time Markov chains 3.1
Fri Jan 9 (Xhours) stationary distributions, Perron Frobenius and ergodic theorem 3.2,3.3
W2
Tue Jan 13 Poisson processes, Continuous-time Markov chains 3.4,3.5,3.6
Thu Jan 15 Embedded chain, Time reversal, detailed balance 3.8
W3
Tue Jan 20 a little measure theory, filtrations, Kolmogorov's extension theorem 1.2,5.1,5.2, D Theorem 5.8 on pg. 261
Thu Jan 22 Gaussian processes, Karhunen–Loève theorem 5.4
W4
Tue Jan 27 OU Processes as Markovian Gaussian processes 5.4
Thu Jan 29 Review for midterm
Fri Jan 30 (Xhours) Midterm
W5
Tue Feb 3 General Markov Processes, Infinitesimal generators 5.3
Thu Feb 5 Wiener process as a Gaussian process, Invariance principle, Donsker's theorem, Diffusion equation 6.1,6.3, 6.2, D7.6 (optional)
W6
Tue Feb 10 Stochastic integrals 7.1,7.2
Thu Feb 12 Itô's lemma, SDEs 7.3
W7
Tue Feb 17 Other stochastic integrals and numerical schemes 7.4,7.5
Thu Feb 19 The Fokker–Planck equation 8.1,8.2,8.3
W8
Tue Feb 24 Time reversal continued, Monte Carlo methods, importance sampling, variance reduction 4.2,4.3,4.4
Thu Feb 26 Feynman–Kac formula, and particle filtering 8.5,8.6
W9
Tue Mar 3 Rare events, large deviations
Thu Mar 5 Review