KD5081 - Theory, Computation and Experiment

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What will I learn on this module?

This module aims to equip physics students with the knowledge and transferable skills involved in computational methods and experimental techniques. Students will analyse and present experimental data, create computational models for appropriate physical systems and perform comparisons between theory and experiment. Quantitative, analytical and modelling training acquired in this module will support students’ professional and personal skills. This module offers the additional opportunity of research-orientated learning through a hands-on approach to analysing research-based data.

Experiments - Topics may include (note this is indicative rather than prescriptive):
1. Doppler Effect
2. Optical properties of semiconductors
3. Particle accumulation on a glass surface (c.f. sand particles on photovoltaic modules and link to Monte Carlo)
4. The heat engine
5. Hall Effect
6. Fundamentals properties of X-rays
7. Radioactive decay of ?, ? and ? particles
8. Microwave Diffraction
9. PID Control
10. Thermal Conductivity
11. Cosmic Ray Detection
12. Solar photovoltaic efficiency measurement.

Computation - Topics may include (note this is indicative rather than prescriptive):
1. Curve fitting (linear and non-linear), statistical analysis and data presentation
2. Matrices to the level of eigenvectors and eigenvalues
3. Discretisation and series analysis
4. Ordinary differential equations
5. Partial differential equations (links to stock market modelling, radioactivity, electrical and mechanical systems)
6. Thermal modelling
7. Probability distribution functions

How will I learn on this module?

The learning strategy of this module is based on a combination of lectures and laboratories. Lectures give a formal introduction to physical and mathematical aspects to be applied in laboratories. Laboratories provide hands-on training in experimental and computational Physics, but will often address topics with links beyond the discipline, thus strengthening the students’ transferable skills and employability.

Experimental work
Students will work in small groups in the laboratory, supported by tutors, developing hands-on experimental training through execution of lab-scripts. Data will be treated using statistical error analysis and data fitting techniques to compare with theoretical models underpinned by fundamental physics.

Computational work
An appropriate computational software such as MATLAB will be introduced to a level including matrices, expressions, indexing, linear and non-linear functions, data analysis and presentation, flow control, programs and functions. Computational labs focused on data analysis will use data from research sources.
The computational aspect of this module offers several technology-enhanced learning opportunities for students, including computational programming and scripting, data visualization and reporting.

This module is assessed by a laboratory-based assignment worth 50% and a computer-based assignment also worth 50%. The lab-based assignment will provide an opportunity for student’s to demonstrate knowledge of particular aspects of experimental physics. The computer-based assignment will cover the modelling aspects of the module and will assess the students’ problem solving abilities in creating an appropriate computational program to address a physics-based problem.

Laboratory sessions will be used to gain key formative feedback during suitable experiments, either verbally or through a lab-book.

Independent study is supported by further technology-enhanced resources provided via the e-learning portal, including lecture notes, e-hand outs, sample problems and past-paper questions.

How will I be supported academically on this module?

Lectures and labs will be the main point of academic contact, offering the student with a formal teaching environment for core learning. Labs will provide students with opportunities for critical enquiry and exchanges.

Outside formal scheduled teaching, students will be able to contact the module team (module tutor, year tutor, programme leader) either via email or the open door policy operated throughout the programme.

Further academic support will be provided through technology-enhanced resources via the e-learning portal. Students will have the opportunity to give their feedback formally through periodic staff-student committees and directly to the module tutor at the end of the semester.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:
• Apply Physics and Mathematics concepts to formulate and tackle experimental and computational problems.

Intellectual / Professional skills & abilities:
• Plan and implement experimental investigations using standard and specialist laboratory equipment
• Develop and implement computing algorithms based on analytical and physical models


Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
• Perform critical comparisons of experimental data with theory and derive suitable conclusions
• Analyse, discuss and report experimental and computational results in a professional manner using appropriate software?

How will I be assessed?

SUMMATIVE
1. Lab Assignment (50%) – KU1, ISA1, PVA1, PVA2
2. Computational Assignment (50%) – KU1, ISA2, PVA1, PVA2

FORMATIVE
1. Lab-book KU1, ISA1, ISA2

Feedback will take several forms including: individual verbal / written comments on lab work delivered in class or via blackboard; verbal feedback on the seminar work; written feedback on the report based on the experimental laboratories and on the assignment.

Pre-requisite(s)

N/A

Co-requisite(s)

N/A

Module abstract

Combining theory, computation and experiment for problem-solving is a key transferable skill in Physics. In this module you will tackle topical problems in Physics via a hand-on approach based on experiments, their analysis and the development of mathematical and computational models to treat and understand data. The content of the module is often informed by research data and research ideas, helping your develop your scientific curiosity and acumen. Via specialist Lab and IT facilities, the module offers a sandbox to develop your experimental and computational skills enhanced by technology. Building on formative assessment via lab and log-books, you will prepare and submit two components of assessment consisting of a 10-page lab report and a computational script. On completion of this module, you will have strengthened your ability to formulate, experimentally-test, analyse and rationalise Physics-related problems, increasing your skills base and appeal as a Physicist either in the academic or industrial sectors.

What will I learn on this module?

This module aims to equip physics students with the knowledge and transferable skills involved in computational methods and experimental techniques. Students will analyse and present experimental data, create computational models for appropriate physical systems and perform comparisons between theory and experiment. Quantitative, analytical and modelling training acquired in this module will support students’ professional and personal skills. This module offers the additional opportunity of research-orientated learning through a hands-on approach to analysing research-based data.

Experiments - Topics may include (note this is indicative rather than prescriptive):
1. Doppler Effect
2. Optical properties of semiconductors
3. Particle accumulation on a glass surface (c.f. sand particles on photovoltaic modules and link to Monte Carlo)
4. The heat engine
5. Hall Effect
6. Fundamentals properties of X-rays
7. Radioactive decay of ?, ? and ? particles
8. Microwave Diffraction
9. PID Control
10. Thermal Conductivity
11. Cosmic Ray Detection
12. Solar photovoltaic efficiency measurement.

Computation - Topics may include (note this is indicative rather than prescriptive):
1. Curve fitting (linear and non-linear), statistical analysis and data presentation
2. Matrices to the level of eigenvectors and eigenvalues
3. Discretisation and series analysis
4. Ordinary differential equations
5. Partial differential equations (links to stock market modelling, radioactivity, electrical and mechanical systems)
6. Thermal modelling
7. Probability distribution functions

Course info

UCAS Code F3F5

Credits 20

Level of Study Undergraduate

Mode of Study 3 years full-time or 4 years with a placement (sandwich)/study abroad

Department Mathematics, Physics and Electrical Engineering

Location City Campus, Northumbria University

City Newcastle

Start September 2019 or September 2020

Current, Relevant and Inspiring

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Your Learning Experience find out about our distinctive approach at 
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