Stochastic methods in physics and biology, spring 2014

Last modified by muratore@helsinki_fi on 2024/03/27 10:22

Stochastic methods in physics and biology, spring 2014

Lecturer

Paolo Muratore-Ginanneschi 

Matteo Marcozzi (assistant)

Scope

10 sp.

The aim of the course is to introduce the basic concepts of the theory of stochastic differential equations needed in applications (applied mathematics, physics and biology).

Prerequisites

Type

Advanced studies

Prerequisites

The course is intended for undergraduate students of mathematics, physics. Prior courses in advanced calculus and linear algebra are required (Diff.Int. 1-2 and Lineaarialgebra 1, or Mapu 1-2).

Lectures

Weeks 4-9 and 11-18, Monday 14-16 in room D123, and Friday 14-16 in room C123.

Easter holiday 17.-23.4.

Lecture Notes

The lecture notes cover and sometimes integrate the material expounded in the lections. They also give bibliographic references for the same topics.

Lectures 1-10

Lectures 10-20

Lecture 01: Probability spaces and random variables (v 11.02)

Lecture 11: Karhunen–Loève representation of the Brownian motion

Lecture 02:: Independence, conditional expectations and inequalities (v 11.02)

Lecture 12: Calculus for paths of finite quadratic variation (v 04.04)

Lecture 03: Classical limit theorems (v 11.02)

Lecture 13: Ito integrals (v. 08.04)

Lecture 04: Sequences of random variables and martingales (v 07.02)

Lecture 14: Stratonovich integral, stochastic differential equations (v 08.04)

Lecture 05: From Bernoulli variables to Random Walk (v 11.02)

 

Lecture 06: Continuous Time Random Walks and Montroll-Weiss equation

 

Lecture 07: Asymptotic analysis of the Montroll–Weiss process

 

Lecture_08: Girsanov formula for continuous Markov Processes

 

Lecture 09: Kolmogorov axioms and Kolmogorov–Chentsov theorem (v. 21.03)

 

Lecture 10: Brownian motion (v. 21.03)

 

Exams

Bibliography

  1. Schuss Z., "Theory and Applications of Stochastic Processes: An Analytical Approach" (Springer), 2010, 170, 468.

  2. Gardiner C. W., "Handbook of stochastic methods for physics, chemistry and the natural sciences" (Springer), 1994, 13, 442.

  3. Evans L. C., "An Introduction to Stochastic Differential Equations", Berkeley lecture notes.

  4. van Handel R., "Stochastic Calculus and Stochastic Control", CalTech lecture notes (2007).

  5. Klebaner F. C., "Introduction to stochastic calculus with applications" (Imperial College Press), 2005, 416.

  6. Higham D. J., "An algorithmic introduction to numerical simulation of stochastic differential equations", SIAM Review, Education Section, 43, 2001, 525-546. (Link to Higham's publications page.)

Registration

 
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Exercise session

Group

Day

Time

Place

Lecturer

1.

Friday

16-18

B321

Exercise Notes

 

Notes 01

 

Notes 02

 

Exercise Session07

 

Exercise Session 08