Gwybodaeth Modiwlau
Course Delivery
| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 10 x 1 hour lecture |
| Practical | 12 x 2 hour workshops |
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Exercises set in semester week 8 comprising a portfolio drawn from coursework. | 40% |
| Semester Assessment | Mini project set in semester week 8 for Completion by the end of term. | 60% |
| Supplementary Assessment | Resubmit failed components | 100% |
Learning Outcomes
On successful completion of this module students should be able to:
Demonstrate a familiarity with various techniques and algorithms for scientific computing and analysis.
Devise and implement numerical programs to perform the relevant algorithms.
Aims
Numerical solutions to mathematical and physics problems is a cornerstone of both physics and applied mathematics research. This module is a continuation of the practical-based module PH36010. The numerical techniques are more advanced and will require more detailed understanding of the numerical methods.
Brief description
This module builds on the Numerical Methods module PH36010. Methods of solving (large) systems of simultaneous linear equations are introduced. This is then used to numerically solve partial differential equations. Monte Carlo methods are introduced as a general method. More specifically, Metropolis Monte Carlo methods for solving problems in statistical mechanics are covered. The students will implement these algorithms and apply them to simple physical problems. There will also be an introduction to parallel programming using the MPI library.
Content
Iterative methods for solving sparse systems of linear equations.
Numerical methods for partial differential equations.
Introduction to parallel programming using the Message Passing Interface.
Monte Carlo methods.
Metropolis Monte Carlo methods for simulation of statistical mechanical systems.
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | Throughout the module. |
| Communication | Writing a portfolio. |
| Information Technology | Python, Fortran, MPI. |
| Personal Development and Career planning | Programming skills. |
| Problem solving | Through the module. |
| Subject Specific Skills | Programming, numerical methods. |
Notes
This module is at CQFW Level 7