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Semester 2

Modelling and Visualisation in Physics (PHYS10035)

Subject

Physics and Astronomy

College

SCE

Credits

10

Normal Year Taken

4

Delivery Session Year

2023/2024

Pre-requisites

Course Summary

This course covers the process of mapping a scientific problem onto a computer algorithm to enable it to be modelled, along with an introduction to visualisation techniques (e.g., via either gnuplot or Matplotlib or similar), to help visualise the solution. Example problems will be drawn from the Junior Honours physics programme, with additional examples from 'everyday' problems. The course will consist of lectures on the algorithms and weekly hands-on practical sessions, with three checkpoints.

Course Description

Theoretical background of core simulation techniques including:1. Monte-Carlo integration and Monte-Carlo simulations 2. Cellular automata3. Molecular dynamics simulations OR Partial differential equations (depending on year) Implementation of these core techniques in Python to solve specific (and potentially unseen) physics problemsIntegration of visualisation (evolving fields, moving particles, live graphs etc) and graphical user interfaces into simulation codesThe notion and origin of errors and instabilities in numerical algorithms, and simple techniques for handling themKey issues that arise in the development of scientific software, such as: compromises between efficiency and flexibility, the incorporation of third-party library code (and its distinction from plagiarism) and the utility of good-quality documentation and coding style

Assessment Information

Written Exam 50%, Coursework 50%, Practical Exam 0%

Additional Assessment Information

Checkpoint assessments based on computational laboratory tasks, 50%Unseen practical examination in CP Lab, 50%.

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