2022/23 Undergraduate Module Catalogue
PHYS2320 Computing 2- Computational Physics
10 creditsClass Size: 200
Module manager: Dr Gavin Burnell
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2022/23
|Computing 1- Fundamentals of Programming
This module is mutually exclusive with
This module is not approved as a discovery module
Module summaryComputer programming is an important skill for Physics students to learn, preparing them for both higher level academic studies and a wide range of professional careers. This module builds upon the first year Computing 1 module to further develop skills in programming and focusses on applying programming to solve realistic data analysis problems in physics. This module covers tasks such as reading data files, manipulating and fitting data to theoretical models and visualising and presenting the results. For this module we use the Python programming language as it is modern, widely used in scientific environments, freely available and provides a rich set of libraries for carrying out data analysis.
ObjectivesThis module will enable students to translate descriptions of physical problems and data analysis processes into short programs to read and manipulate data, analyse and present the results for problems relevant to physics using the Python programming language.
On successful completion of this module, students will be able to:
• Model simple physical situations in computer code
• Read text-based data files and manipulate the data in computer code
• Fit data to simple models and extract relevant physical parameters with uncertainties
• Generate suitable visualisations of data and results.
An increased ability to use a general description of a problem and associated data analysis technique to generate working computer programs to solve problems relevant to physics and physics related disciplines.
This module covers the following areas:
• Structuring code in functions and modules
• Writing maintainable and documented code and finding and eliminating bugs in code
• Reading and parsing simple data files
• Use of common Python libraries such as numpyt and scipy for example, for scientific programming.
• Simple data visualisation in Python using widely adopted visualisation matplotlib
|Office Hour Discussions
|Private study hours
|Total Contact hours
|Total hours (100hr per 10 credits)
Private studyProgramming and reviewing background physics or maths as required
Opportunities for Formative FeedbackCoursework mini-assessment assignments
Methods of assessment
|% of formal assessment
|Mini-assessments based on Computer Lab Workshop tasks
|Extended Coursework project
|Total percentage (Assessment Coursework)
Attendance at certain activities is mandatory and a penalty for unexplained absences will be applied to the final module mark. Students must submit a serious attempt at all assessments for this module, in order to pass the module overall.
Reading listThe reading list is available from the Library website
Last updated: 29/04/2022 15:31:38
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