Stochastic methods for physics and biology, spring 2012
Lecturer
Scope
10 cu.
Type
Advanced studies
Prerequisites
Lectures
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 110  Lectures 1020 

Lecture_01 Review of Probability: random variables and their expectations (rev 04.02)  Lecture_11 Karhunen–Loève representation of the Brownian motion 
Lecture_02 Review of Probability: classical theorems (part I) (rev 30.01)  Lecture_12 Ito and Stratonovich stochastic integrals 
Lecture_03 Review of Probability: classical theorems (part II) (rev 04.02)  Lecture_13 Stochastic differential equations 
Lecture_04 Probability and Classical Statistical Mechanics (rev 07.02)  Lecture_14 Backward Master equation and backward Kolmogorov equation 
Lecture_05 Random Walk (rev 13.03)  Lecture_15 Forward Master equation and forward Kolmogorov equation 
Lecture_06 Conditional expectation and Martingales (rev 13.03)  Lecture_16 Exit time statistics (rev 20.04) 
Lecture_07 Markov jump processes (rev 01.03)  Lecture_17 Diffusions in one dimension: analysis of boundary conditions 
Lecture_08 Continuity of paths, KolmogorovChentsov theorem  Lecture_18 HamiltonBellmanJacobi equation 
Lecture_09 Ito lemma for paths of finite quadratic variation 

Lecture_10 Brownian Motion 

Exams
Description
The aim of the course is to introduce the basic concepts of the theory
of stochastic differential equations (SDE) needed in applications (applied
mathematics, physics and biology). In particular we will illustrate
methods of qualitative, asymptotic and numerical analysis of SDE.
Among the scopes of the course is also to provide an elementary
introduction to stochastic control and filtering theory.
Bibliography
 Gardiner, C. W. Handbook of stochastic methods for physics, chemistry and the natural sciences Springer, 1994, 13, 442
 L.C. Evans, "An Introduction to Stochastic Differential Equations", Berkeley lecture notes.
 R. van Handel, "Stochastic Calculus and Stochastic Control", CalTech lecture notes (2007)
 D.J. Higham, "An algorithmic introduction to numerical simulation of stochastic differential equations" SIAM Review, Education Section, 43, 2001, 525546. (Link to Higham's publications page.)
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Exercise groups
Group  Day  Time  Place  Instructor 

1. 



