MPhys Physics with Theoretical Physics

Computation is a vital part of modern scientific research along with theory and experiment. Interpreting the ever-increasing volume and complexity of data from physical experiments and astronomical observations requires the application of sophisticated computational techniques such as Monte Carlo sampling methods and (machine-learning) neural networks. Furthermore, the numerical simulation of physical systems is an invaluable method for building and testing physical models as well as predicting results beyond current knowledge. In this unit, the students will be introduced to these techniques through a project-based learning format, enabling them to learn how the different methods work and apply them to study set problems through constructing their own computational solutions using Python code.

For the students to acquire advanced computational problem-solving skills in three key areas: 

1 – Numerical simulation using finite differe