Department of Physics, Unit Catalogue 2008/09 |
PH30056 Computational physics B |
| Credits: 6 |
| Level: Honours |
| Semester: 2 |
| Assessment: CW 100% |
| Requisites: |
| Before taking this unit you must take PH20018 and take PH30031 |
|
Aims: The aim of this unit is to provide students with experience in the application of some of the major techniques used in the simulation of physical systems, and to develop their ability at using computers in physical modelling. Topics will be chosen for study to encourage a greater understanding of both the model and the underlying physics. The emphasis will be on the application and interpretation of the techniques, not on programming.
Learning Outcomes: After taking this unit the student should be able to: * identify issues which influence the choice of programming environment, language and architecture; * write and develop C code for computer simulations, including interfacing to a 2d graphics package; * outline applications of the molecular dynamics technique and the surrounding computational issues; * outline the physics and computational issues illustrated by the Ising model; * explain the methodology and output of the simulations performed. Skills: Written Communication T/F A, Numeracy T/F A, Data Acquisition, Handling, and Analysis T/F A, Information Technology T/F A, Problem Solving T/F A. Content: Overview of computer languages for scientific work: Computer architecture and code optimisation. Revision of C programming in the UNIX environment. Lattice-based simulations: Overview of contemporary applications. Diffusion limited aggregation as a physical model for growth processes. Development of a practical algorithm. Implementation in C, including graphical visualisation. Investigation of properties of clusters formed by DLA. Effects of varying the growth rule. Molecular dynamics: Overview of contemporary applications. Application to multi-particle 2d Lennard-Jones system. Numerical solution of equations of motion. Potential cut-off. Implementation of NVE MD in C, including graphical visualisation. Calculation of observables; temperature, pressure, diffusion coefficient, structural information including pair correlation function g(r). Constant T, P simulations. Monte Carlo simulation in statistical physics: The Ising model. Revision of elementary statistical physics. Revision of Monte Carlo methods. Importance sampling. Markov states. Metropolis algorithm; Implementation in C, including graphical visualisation. Look-up tables. Computation of thermal averages; magnetisation, energy density, specific heat, susceptibility. Spin correlation function |