This repo contains my final report for the Introduction to Numerical Modelling module project during my KCL physics degree which was graded as a 1st (87). The Jupyter Notebook contains my Python code and description of the three projects I completed.
This report will present three topics, with relevance to a range of scientific disciplines, to explore different numerical methods computationally. Common mathematical concepts will be utilised to create simplified models and discuss the questions these scenarios pose. Randomness and probabilistic techniques will be applied to the popular 'travelling salesman' problem, differential equations will be used to model the mechanics of the Tacoma bridge and finally a method of image compression using linear algebra will be implemented. Skills in the Python programming language will be developed by creating functions to investigate and find optimal modelling solutions. The applications and possible extensions of the strategies used will be considered, in addition to their importance in the skill set of a modern scientist.