The University of Southampton
Courses

# PHYS6017 Computer Techniques in Physics

## Module Overview

This Computational Physics course is designed for students with definite interest in tackling physics problems that are only tractable through the use of computers. It covers all types of application of computers by physicists, except the control of equipment. It covers the areas of scientific computation, Monte Carlo simulations and random numbers, numerical integration, finite differencing, differential equations and signal processing.

### Aims and Objectives

#### Module Aims

The aim of the course is to describe how the approach to physics problems has changed due to the availability of computers and to provide experience in the solution of problems that are tractable only through the use of computers.

#### Learning Outcomes

##### Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• Describe general principles and simple algorithms for solving physics problems
##### Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Apply two or more computational techniques to solve two physics problems/projects numerically
##### Disciplinary Specific Learning Outcomes

Having successfully completed this module you will be able to:

• Write two reports, which describe the physics problem/project and your solution and evaluate your solution and its implications, in a style suitable for publication in a professional scientific journal

### Syllabus

Scientific computation - Languages for scientific computation - Getting answers right and fast - Recurrence relations - Computer exercise: Fourier series. Monte Carlo and random numbers - Monte Carlo simulations - Generating random numbers - Computer exercise: Buffon, random flights, random number generation. Numerical integration - Trapezium rule and improvements - Multidimensional integrals - Computer exercise: Gaussian integration, random flights. Finite differencing - Approximations to differentials - Matrix calculations - Eigenvalues - Computer exercise: diffusion, harmonic oscillator, Heisenberg model. Differential equations - Principles of numerical solution and stability - Quantum mechanics - Computer exercises: hanging chain, Morse potential, harmonic oscillator. Signal processing - High and low pass filters - Fourier analysis - Computer exercise: digital filter, Fourier transform.

### Learning and Teaching

TypeHours
Lecture12
Total study time12

#### Resources & Reading list

PL DeVries. A First Course in Computational Physics.

### Assessment

#### Summative

MethodPercentage contribution
Project report 50%
Project report 50%

#### Referral

MethodPercentage contribution
Coursework assignment(s) 100%

#### Repeat Information

Repeat type: Internal & External

Prerequisites: PHYS3004 and PHYS3007 and PHYS3008 (or PHYS3002)

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