68416 Computational Physics
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Credit points: 6 cp
Result type: Grade and marks
Requisite(s): (68201 Physics 2 OR 68037 Physical Modelling) AND (33230c Mathematics 2 OR 68038 Advanced Mathematics and Physics OR 33290 Statistics and Mathematics for Science)
The lower case 'c' after the subject code indicates that the subject is a corequisite. See definitions for details.
These requisites may not apply to students in certain courses. See access conditions.
Description
This subject introduces the key elements of computational physics such as methods for solving physical problems numerically and the use of computers for simulating the dynamics of large or complex systems. Depending on selected project topics, numerical techniques including matrix manipulation, iterative optimisation and differential equation solvers may be introduced. These are developed and applied to selected problems in areas such as quantum mechanics, statistical mechanics, electrodynamics and molecular dynamics. Project work allows students to explore advanced simulations and further develop analysis and visualisation of results.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Write programs in a numerical programming environment to solve simple equations, analyse results and plot graphs |
|---|---|
| 2. | Write and document code in a manner that makes it re-usable and transferable. |
| 3. | Build models of relatively complex physical systems, by researching the required physics, and constructing, testing and applying appropriate simulation modules. |
| 4. | Communicate results and information in a professional and competent way appropriate to the discipline. |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of following course intended learning outcomes:
- Demonstrate coherent understanding of physics and related knowledge applied to diverse contexts. (1.1)
- Evaluate the reliability of scientific evidence and apply effective experimental design, analysis and critical thinking to predict the behaviour of real-world systems using physical models (2.1)
- Engage autonomously or in teams to derive and analyse data from instrumentation and physical models to make ethical contributions to society. (3.1)
- Evaluate and design solutions to complex physical problems through creative problem-solving, using analytical, computational, and experimental approaches. (4.1)
- Apply effective and appropriate communication methods for discussing physics concepts, data and analysis with diverse audiences. (5.1)
Contribution to the development of graduate attributes
1. Disciplinary knowledge
Students will develop knowledge of key numerical algorithms through exercises at the beginning of the subject, reading resources and applying these algorithms to basic physical processes. They further extend their knowledge of algorithms and physics as they develop computer models for their specific project. Careful comparison to test cases and feedback will inform this learning process.
2. Research, inquiry and critical thinking
Students will systematically explore computational problems, particularly in addressing their project, and by doing so develop an understanding of the benefits and limitations of a computational approach. Ongoing review and feedback will assist students in development.
3. Professional, ethical and social responsibility
Students will develop basic programming skills (e.g. in Matlab) through structured exercises and extend these skills throughout their project, with development guided by regular feedback and review. They will be shown how to document their work, and come to understand its value through feedback and peer-review. They have the opportunity to collaborate, and learn the importance of appropriate attribution, through active participation in projects and review. They will be informed of management processes and develop these through planning and ongoing review of their progress.
4. Reflection, Innovation, Creativity
Students will develop in at least two important areas: driving their own learning during their project, and critical evaluation of their own and others work. Students take the initiative in selecting their project and are responsible for the direction of the investigation. Through ongoing review of their own and other's work they can evaluate a variety of approaches and have the opportunity to try approaches they hadn't previously considered.
5. Communication
Students will develop communication skills throughout this subject, especially of graphical information but also of documentation and appropriately structured reporting. Ongoing participation in review with evaluation and action in response to feedback is particularly important in this regard.
Teaching and learning strategies
2x2hr mixed lecture & computer lab sessions will be available. We will only make minimal use of lectures as necessary, and will focus on engaging in active learning and consultation. You are expected to be proactive in managing your learning and will need to spend some time outside of class, so that you can make the best use of consultation opportunities in class. Regular person attendance is expected, so that you can discuss coding strategies with your peers and tutors.
The overarching strategy is producing a portfolio of work that demonstrates a solution to a problem of your choice, which has been developed and tested throughout the session with regular review by yourself, peers and tutors. You have the opportunity to work collaboratively, and are encouraged to consult with other teams and tutors to review the quality of your work, but everything you submit must demonstrate your own learning and any minor contributions from others (including external sources) must be clearly acknowledged. Evaluating and acting on this feedback will help you improve the quality of your work. You will be supported to develop programming, project management, and communication skills through a number of activities with ongoing review.
Initially you will assess and develop your personal competence in basic programming and numerical principles by completing basic exercises before you come to class, and then extending these skills in class in consultation with your peers and tutors. Resources including notes, tutorials and self-assessments will be linked through Canvas. It is recommended that you review your progress on specific skills at least weekly, especially if you have no prior programming experience. There will be regular short assessments to formally evaluate your progress.
You will then develop, test and demonstrate the use of a simple numerical algorithm that solves a physical problem. You will be expected to be able to explain how it works without assistance from others. You will present this work for assessment of your programming, understanding and communication, with feedback that will assist you with the final assessment.
You will choose a project topic and develop a plan with minimum and stretch targets and map out milestones for their completion, no later than the mid-session break. You should consult with a tutor before enacting this plan, and continue to review progess and update accordingly on a regular basis (e.g. weekly).
You will develop, test and demonstrate a working computer code that solves a non-trivial problem. It is expected that as you become more proficient at programming you will take control of your learning in this area. You should aim to have a basic code working soon after the break and then seek feedback on a documented test demonstration. You are expected to be able to explain how it works without assistance from others.
Finally, you will undertake a scientific exploration using your code, and report your findings. Peers and tutors will continue to be a useful source of advice, especially on your exploration of the topic. You should submit your draft report at least two weeks prior to the due date so that you have adequate time for review against the rubric and undertaking revisions.
As you progress, you will also continuously develop your professional communication as you and your colleagues review your work.
Assessment
Assessment task 1: Project
| Intent: | This assessment task contributes to the development of the following graduate attributes: 1. Disciplinary Knowledge 2. Research, inquiry, and critical thinking 3. Professional, ethical and social responsibility 4. Reflection, Innovation, Creativity 5. Communication |
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| Objective(s): | This assessment task addresses subject learning objective(s): 1, 2, 3 and 4 This assessment task contributes to the development of course intended learning outcome(s): 1.1, 2.1, 3.1, 4.1 and 5.1 |
| Type: | Project |
| Groupwork: | Individual |
| Weight: | 60% |
| Criteria: | The quality of the submitted work (both presentation and the outcomes it demonstrates) will be assessed using a rubric. The submitted work should address the specified graduate attributes and subjective objectives as detailed in the rubric. The submitted work should: Tutors will assess your understanding in response to questions about your submitted work. |
Assessment task 2: Programming assignments
| Intent: | This assessment task contributes to the development of the following graduate attributes: 1. Disciplinary Knowledge 5. Communication |
|---|---|
| Objective(s): | This assessment task addresses subject learning objective(s): 1 and 2 This assessment task contributes to the development of course intended learning outcome(s): 1.1 and 5.1 |
| Type: | Exercises |
| Groupwork: | Individual |
| Weight: | 10% |
| Criteria: | Program gives correct result Code appropriately documented Results appropriately presented |
Assessment task 3: Simple physics simulator
| Intent: | This assessment task contributes to the development of the following graduate attributes: 1. Disciplinary Knowledge 2. Research, inquiry, and critical thinking 3. Professional, ethical and social responsibility 4. Reflection, Innovation, Creativity 5. Communication |
|---|---|
| Objective(s): | This assessment task addresses subject learning objective(s): 1, 2 and 4 This assessment task contributes to the development of course intended learning outcome(s): 1.1, 2.1, 3.1, 4.1 and 5.1 |
| Type: | Report |
| Groupwork: | Individual |
| Weight: | 30% |
| Criteria: | Physics simulator Please refer to the rubric. In short: Peer Review The feedback given addresses the relevant criteria. The feedback given outlines "what" and "how" to improve. |
Recommended texts
Material will be supplied or suggested as needed (e.g. via Canvas)