Teaching: Graduate curriculum in applied mathematics
This set of courses is designed for graduate students in applied mathematics
whose primary interest is in the modeling and analysis of scientific problems.
There is a total of five coursess. The first four courses have been
developed and are now either regular courses at Princeton or Peking
University or regular courses in the summer school at Peking University.
- Applied Partial Differential
Provides an overview of the PDEs that are often encountered in applied mathematics,
as well as an introduction of analytical, asymptotic and qualitative methods.
Emphasis is put on the qualitative properties of the solutions to these PDEs.
- Introduction to
A systematic introduction to simulation methods in computational sciences,
including quantum mechanics, molecular dynamics, Monte Carlo, Brownian dynamics
and continuum methods.
- Applied Stochastic Analysis
An introduction to stochastic analysis and stochastic methods. The material
is selected for the particular needs of applied mathematicians. It does not
assume background in probability theory or stochastic processes, yet it leads
to fairly advanced topics such as rare events.
- A Mathematical
Introduction to Aspects of Physics
Provides the necessary scientific background, including fundamental principles
of physics, atomic structures and chemical kinetics.
- An Introduction to Mathematical Physics
An introduction to the mathematical problems that arise in these areas, in
particular the modeling from atomistic to continuum scales.