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    Computational methods for solving physics problems. Graphical visualisation. Numerical techniques for solving classes of equations in a variety of physical examples. Curve fitting, Fourier transforms. Non-linear dynamics and chaos.

    This paper aims to provide the core tools and methodology of computational physics. The emphasis is on gaining practical skills, and a key objective is that students gain the techniques and the confidence to tackle a broad range of problems in physics. Topics have been selected to provide a broad basis of skills, and each is illustrated by application to physical systems. The paper is taught in the open-source language Julia, for which prior knowledge is not essential. The language will feel very familiar to those with Matlab or Python experience and provides a flexible and powerful platform for modern technical computing and a convenient, open science environment.

    About this paper

    Paper title Computational Physics
    Subject Physics
    EFTS 0.15
    Points 18 points
    Teaching period Semester 1 (On campus)
    Domestic Tuition Fees ( NZD ) $1,173.30
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    (36 200-level PHSI points or (18 200-level PHSI points and 18 200-level MATH points)) and MATH 140
    Schedule C
    Teaching staff

    Course Co-ordinator: Dr Ashton Bradley
    Dr Annika Seppälä


    Textbooks are not required for this paper.

    Graduate Attributes Emphasised
    Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship, Communication, Critical thinking, Information literacy, Self-motivation.
    View more information about Otago's graduate attributes.
    Learning Outcomes

    After completing this paper students will be able to:

    1. Understand and apply the basic methodology of computational physics to a broad range of physics problems
    2. Write well-structured Julia programmes and independently acquire additional coding skills
    3. Process, analyse and plot data from a variety of physical phenomena and interpret their meaning
    4. Use specific computational techniques to solve ordinary differential equations and systems of linear equations, to analyse and manipulate spectral content of digitised data
    5. Present well-structured reports of the results of computational investigations in an open science framework


    Semester 1

    Teaching method
    This paper is taught On Campus
    Learning management system


    Stream Days Times Weeks
    A1 Monday 15:00-16:50 9-13, 15-22
    Wednesday 15:00-16:50 9-13, 15-22


    Stream Days Times Weeks
    A1 Thursday 14:00-15:50 9-13, 15-16, 18-22
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