PHY600 - Fall 2010
309 Physics Building, 443-5978,
The following is a list of topics I would like to cover.
In each case I shall try to include a self-contained introduction to
the physics problem/system,
an explanation of the algorithm used and a code that can be used
that algorithm. Small scale working demonstrations of such codes
will be used throughout to illustrate computational issues. Some
C/C++ will be assumed although a student with minimal programming
be able to learn more advanced programming concepts as the course
progresses. The course will involve substantial amounts of ``hands on''
experience using the PCs in the Physics cluster.
I will set (small) homework exercises every two weeks or so but will
require students to undertake a substantial computational project in
the second half of
This page maintained by Simon Catterall, last updated 18 August, 2010.
- Discrete quantum field theory as a problem in equilibrium
statistical mechanics. Example: 2D scalar field theory on the lattice
- Partition function as a probability distribution
- Markov processes, master equations as a way of realizing such
distributions. Stochastic estimation of observables -- the Monte Carlo
- Metropolis -- the simple, all purpose algorithm
- Simple introduction to C++ and its use in crafting
scientific simulation code.
- Heatbath and overrelaxation -- more efficient (local) algorithms
- Cluster techniques to tackle critical slowing down
- Simple error analysis and fitting techniques
- Introduction to phase transitions and critical phenomena.
Finite size scaling. Continuum limits
- Classical dynamics and Langevin methods for continuous systems.
Hybrid Monte Carlo -- application to non-local systems such as relativistic
fermions. Fourier acceleration.
- Techniques for solving large sparse linear problems
- Elementary ideas about the renormalization group (RG).
Introduction to Monte Carlo rnormalization group.
- Simple ideas about parallization
- Other physics topics: lattice gauge theories, spin systems,