MODERN METHODS IN EXPERIMENT AND MODELLING - 2024/5

Module code: PHY3064

Module Overview

The module will introduce students to research level equipment and techniques that are used within the research groups of Physics via extended projects. The four-week projects will cover astrophysics, experimental and theoretical nuclear physics, experimental and theoretical soft matter physics, and quantum technologies. Students will gain experience using state-of-the-art equipment and software, analysing and working with large data sets and in problem solving.

The module builds upon experience gained during first- and second-year laboratory and computing classes with project-based work that is typically more open ended and less structured. Students are expected to take more responsibility for the planning and direction of work than in previous years. The goal is to help prepare students for independent research within a team and for future project work (e.g. Final Year Projects and MPhys research years).

Numbers will be limited on certain projects.

Module provider

Mathematics & Physics

Module Leader

DOHERTY Daniel (Maths & Phys)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): N/A

Overall student workload

Workshop Hours: 4

Independent Learning Hours: 56

Lecture Hours: 10

Tutorial Hours: 4

Laboratory Hours: 64

Guided Learning: 4

Captured Content: 8

Module Availability

Semester 1

Prerequisites / Co-requisites

None

Module content

Indicative content includes: 

Introduction to the module, module structure and assessments.

Lectures covering research techniques in various areas of physics and astronomy.

Students select two projects covering the breadth of research areas within Physics to be performed during the semester. An indicative list of projects includes

Astrophysics experimental: telescope projects using either imaging or spectroscopy techniques.

- Astrophysics modelling: dynamical modelling of stellar systems, stellar evolution modelling.

- Nuclear experimental: Coincidence measurements, related to PET imaging and angular correlations. Data analysis using modern tools such as the ROOT framework.

- Nuclear theory/ modelling: exploring nuclear models using existing codes; application to structure properties such as mass, size and shape, and reactions between nuclei

- Soft matter experimental: Optical microscope projects related to the concepts in soft matter or biological physics.

- Soft matter theory/ modelling: Simulations of modern soft matter or biological physics

- Quantum technology: Optical and electrical characterisation of quantum systems, involving an introduction to computer-controlled instrumentation with LabVIEW.

- Quantum computing: Introduction to quantum algorithms using classical simulators, practical use of Qiskit

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework First report on the experimental / modelling projects, presented in a research paper format 25
Oral exam or presentation First oral-type examination or presentation on the experimental / modelling projects 10
Coursework Second report on the experimental / modelling projects, presented in a research paper format 25
Oral exam or presentation Second oral-type examination or presentation on the experimental / modelling projects 10
Examination Essay-style examination questions describing, e.g., key experimental/ modelling techniques (60 minutes) 30

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate knowledge, practical and computation skills, project planning and teamwork.

The summative assessment for the module consists of:


  • Reports on the experimental/ modelling projects, which are presented in a research paper format and are completed individually. 

  • Oral presentations on the experimental/ modelling projects. 

  • A written examination of 1-hour duration where students choose 2 questions to answer. 



Formative assessment and feedback

Students receive regular feedback from Academics and Demonstrators during laboratory sessions and computing tutorials. 

 

Module aims

  • Introduce research level equipment and techniques used by the research groups at Surrey.
  • Enhance problem-solving skills, data analysis proficiency, and independent research capabilities by planning, implementing and performing experimental and/ or modelling work
  • Develop presentational skills.
  • Prepare students for future team and project work including final year projects, MPhys research years and in future employment.

Learning outcomes

Attributes Developed
001 Become familiar with, and be able to describe, the techniques used in modern physics research K
002 Develop and demonstrate proficiency in planning and carrying out complex projects PT
003 Use state-of-the-art physics equipment and software to analyse and visualise data KCPT
004 Effectively communicate key results and findings both as written reports and in oral presentations. PT
005 Apply appropriate techniques to work with large data sets and present important results KCPT
006 Develop advanced problem-solving skills and gain hands-on experience in fault finding and debugging techniques CPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to combine student-led and flipped learning, for the project components, with traditional lecture content.

This module is delivered collaboratively across Physics. The module leader oversees the administration for the module but the projects involve members from each of the research groups. The group contact leads the setup of equipment, delivers the initial tutorials on the operation of equipment/ relevant techniques and are then available to assist with and troubleshoot on the project. A list of projects is released to students in week 1 who then select two which would each be completed over a 4-week period during the semester. The group contact will also share relevant resources (e.g. a short lab script, instruction manuals, and relevant research papers). Students work together on the project and would write an individual short research paper and then deliver a presentation on their results.

The projects are accompanied by 10 hours of lectures across the semester, introducing state-of-the-art research techniques. This content is assessed during the 1-hour examination at the end of the semester.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: PHY3064

Other information

The School of Mathematics and Physics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:

Resourcefulness and Resilience Problem solving is a key component of this module with students given the opportunity to tackle more involved problems in Physics with more freedom and over a longer period of time. Students will be required draw upon individual and collective resourcefulness and develop a problem-solving mindset as they risk assess, adapt and respond to
challenges faced over a 4-week experiment/ project.

Employability The module introduces learners to experimental equipment and techniques used by professional scientists in both industry and academia. Students are given more responsibility for planning the project work (both experimental and theoretical), including the relevant health and safety and technical aspects and work together in small groups and then produce a succinct report and a presentation summarising the work. The module, therefore, represents a key opportunity to practise and develop problem solving skills.

Digital Capabilities Throughout the module students will engage with large and complex datasets (‘big data’) and will develop their computational skills in analysing this data using
both Python and other bespoke computational languages. Students will also develop skills in working with and presenting complex data with bespoke software packages used in academic and industrial physics research.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Physics with Astronomy BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Nuclear Astrophysics BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Nuclear Astrophysics MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Astronomy MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Quantum Computing BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Quantum Computing MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.