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Outline:

This module consists of a Python-based computing course and a digital thermometer electronics project. The module will cover a range of topics in advanced data analysis, numerical analysis techniques and computational physics.

Aims:

This module aims to develop students’ skills in Python-based computer programming and data analysis and fitting, and their ability to conduct an extended structured practical investigation.

Intended Learning Outcomes:

By the end of the module the students should have:

• Improved ability to record their work concisely and precisely in the laboratory notebook, as it is done;
• Improved ability to take reliable data, to identify the main sources of uncertainty in it, and to propagate random uncertainties into an estimate of the uncertainty on the final result, and conduct and interpret chi-squared minimization;
• Increased ability and confidence to plan and undertake scientific investigation by completing a structured experiment extending over several weeks;
• Increased their knowledge and understanding of electronics and physical measurement;
• Increased their skills in computer programming using Python, and to have developed sufficient competence to be able to apply these skills to a wide variety of physical problems and models.

Teaching and Learning Methodology:

This module is delivered via weekly practical sessions for both the computing and laboratory components. During each computing session, students will complete a task under the close supervision of the course staff, and be given immediate verbal and written feedback. In the digital thermometer sessions, students will work under the supervision of module demonstrators and technical staff.

In addition to timetabled sessions, it is expected that students engage in self-study in order to master the material. This can take the form, for example, of further analysis and reading in textbooks and online.

Indicative Topics:

• Computing: Using the Jupyter Notebook as the main format, Python programming skills acquired during PHAS0007 will be developed and extended, using structured coursework assignments based on a range of physical examples related to lecture and laboratory course material. The course will cover a range of topics in advanced data analysis, numerical analysis techniques and computational physics.
• Digital Thermometer electronics project: This gives the student the opportunity to plan and undertake an extended piece of structured practical work. Students calibrate a temperature sensor and then build and test an operational digital thermometer, with display, and interface it to a computer for automatic collection of data.Ìý