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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


PHYS1220Computing 1- Fundamentals of Programming

This module is mutually exclusive with

COMP1036Computer Programming

This module is not approved as a discovery module

Module summary

Computer 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.


This 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.

Learning outcomes
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.

Skills outcomes
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

Teaching methods

Delivery typeNumberLength hoursStudent hours
Office Hour Discussions91.009.00
Drop-in Session91.009.00
Private study hours77.00
Total Contact hours32.00
Total hours (100hr per 10 credits)109.00

Private study

Programming and reviewing background physics or maths as required

Opportunities for Formative Feedback

Coursework mini-assessment assignments

Methods of assessment

Assessment typeNotes% of formal assessment
ReportMini-assessments based on Computer Lab Workshop tasks15.00
AssignmentExtended Coursework project85.00
Total percentage (Assessment Coursework)100.00

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 list

The reading list is available from the Library website

Last updated: 29/04/2022 15:31:38


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