BSc (Hons) or MPhys — 2024 entry Physics with Quantum Computing

This module introduces students to inviscid fluid flows including surface waves. By the end of the module, students should be able to recognise dominant features of fluid motion, and to derive some simple solutions of the equations of motion. Students should also have an appreciation of the force balances that produce various classes of flows.

This module will build on the rudimentary knowledge of Atoms and Quanta taught in Level FHEQ 4 (PHY1039) and apply the ideas taught in the previous Quantum Physics module (PHY2069) to describe the properties of atoms, including the physics behind the full structure of atomic spectra. It will introduce the effects on atoms due to electric and magnetic fields. The physics of diatomic molecules will be discussed, including how spectroscopic techniques can be used to study more complex molecules. Finally by understanding how atoms interact with light, the module will introduce the principles of the laser, including basic explanations of common lasers, such as solid state and gas lasers. The module includes a laboratory component in which ideas from the lectures will be explored experimentally.

This module considers develops both the thermodynamic and statistical descriptions of energy and entropy. In addition it builds on the introductory Level FHEQ 4 computing modules to develop the skills needed for computational physics. The module will explore various meanings and definitions of entropy. Knowledge of thermodynamics will then be applied to problem solving. The module will build upon the knowledge obtained of the laws of thermodynamics introduced in Properties of Matter at Level FHEQ 4. It will introduce additional thermodynamic theory and show how statistical physics allows us to calculate thermodynamic functions such as the entropy. The computational physics component will develop the student’s skills in solving both ordinary and partial differential equations, in the context of both quantum and thermal physics.

The module will introduce the physical significance and the mathematical methods (and selected theorems) of the operators of vector calculus: div, grad and curl in different co-ordinate systems. The module will introduce the partial differential equations of mathematical physics and their solution for selected physical systems involving different co-ordinate systems and involving time. The module will introduce the foundations of electromagnetism, up to Gauss’ Law and Laplace’s equation, as a major application of the vector calculus and partial differential equations techniques.

The module reprises electrostatics (Gauss’ Law) and proceeds to introduce electromagnetic theory through a development of Maxwell’s Equations and concepts associated with the electric and magnetic polarisation of materials. The module introduces electromagnetic wave theory and its applications to a range of traditional applications and problems as well as the use of Fourier processing for wave signal analysis.

The general properties of nuclei and radioactivity are studied, with an introduction to the deeper structure of elementary particles and the Standard Model. The nuclear physics includes alpha- and beta- and gamma-ray decay, nuclear fission and models of nuclear structure. The high energy physics includes the quark structure of hadrons, CPT conservation and CP violation and the impact of conservation rules on simple reactions of elementary particles.

This module has two independent halves, on crystallography and on optical applications of solids. - The crystallography half-module will describe crystal structures, crystalline lattices and their study with X-rays. It will introduce the concept of quantisation of lattice vibrations (phonons). - The optical applications half-module will describe band theory of solids, how it can be controlled, and how it affects the absorption, reflection, propagation, emission from molecules to nano-materials to bulk solids. Modern optical and photonic devices such as semiconductor lasers, solar cells, nuclear radiation detectors and quantum computer qubits will be introduced.

The Quantum Physics course focuses on the basic formalism of quantum mechanics, its physical interpretation and its application to simple problems. The emphasis is on elementary (one-dimensional) quantum physics, including the infinite-potential well, the parabolic well, one-dimensional step and barrier potentials. 

This module presents a complete introduction to modern astronomy and astrophysics. We start by introducing astronomy as a unique science; measurement in astronomy (position on the sky, velocity and distance); and multi-messenger probes. We then discuss acceleration due to gravity (the dominant force in the Universe) and we show that timescales are typically so long that we must use models to calculate what happened in the past and what will happen in the future. Armed with an understanding of how to make measurements in astronomy and how to model gravity, we then move from the smallest scales to the largest, studying first the interstellar medium from which stars form; stellar structure and evolution; and stellar remnants (white dwarfs, neutron stars and black holes). We compare and contrast the latest models for how planets form and we discuss the prospects for detecting life and intelligent life beyond Earth. Finally, we discuss the formation and evolution of galaxies in the Universe and the Universe as a whole. We show that the Universe appears to be mostly dark: dark matter (~22%) and dark energy (~74%). Understanding what these mysterious components are is one of the key challenges for physics in the next decade. The module includes either a computer or telescope project. Students enrolled in physics with astronomy with undertake the telescope project where (weather willing) students will gain hands on experience of taking real observational data. They will develop software tools to analyse and interpret these data and write up a final report. Students not enrolled in physics with astronomy will undertake a computational project of similar scope and length, also culminating in a final report.

Expected prior learning:  Module EEE2042 – Electronic and Photonic Devices, or equivalent learning, is advisory but not required. Module purpose:  Semiconductor devices and optoelectronics play a major technology enabling amongst other things the internet. The course is given via a series of lectures and aims to give a background to the interaction of light with key photonic materials and devices. This module will introduce students to modern energy efficient electronic and photonic devices concentrating on the fundamental science of operation, device structure and characteristics.

This module introduces fundamental concepts in analytical dynamics and illustrates their application to real-world problems. The module covers the calculus of variations, Lagrangian and Hamiltonian formulations of dynamics, Poisson brackets, canonical transformations and symplectic manifolds. The module also leads to a deeper understanding of the role of symmetries and conservation laws in dynamical systems. This module builds on material from MAT1036 Classical Dynamics and lays the foundations for MAT3039 Quantum Mechanics.

This 30 credit project module is designed to give students the opportunity to explore an area of interest in physics in some depth, either through experimental, theoretical or computational means, or in the form of a literature survey.  The module also develops generic professional skills such as teamwork, scientific writing and professional ethics.  The module involves writing a dissertation and an oral assessment  

The course will follow the historical development of the main medical imaging techniques. The first part will consider, from a theoretical perspective, the fundamentals of X-ray image formation both in the planar modality and in the Computed Tomography modality. Elements of image processing and image reconstruction will be addressed. The second will look at the physical principles and methods of Nuclear Medicine. The third will look at the principles underlying the application of diagnostic ultrasound in medicine. The fourth will consider Magnetic Resonance Imaging (MRI), one of the most important techniques of medical imaging used in hospitals today. In parallel to the related theoretical classes, laboratory experiments will be carried out on X-ray imaging and ultrasound.

In this module, students will learn key methods adopted in astrophysics to carry out advanced research: scientific computing, statistics, data analysis, machine learning. Much of the course develops highly transferrable skills that apply to science research in general. The goal is to ensure that students are well-prepared for either their research year or their future careers.

This module aims to provide an advanced level understanding of the physics of stars and nuclear astrophysics. In particular, the course will provide an understanding of advanced nucleosynthetic pathways, an analytical underpinning of resonant reaction rates, together with the experimental techniques involved in their determination.

The module will introduce students to key concepts in education as well as the tools and strategies for effective public engagement in their discipline areas and for different audiences. Students will gain practical experience by planning, implementing, and evaluating an education or public engagement-based activity. Opportunities will also exist for classroom (e.g. school; early-year University) teaching experience and / or involvement in external exhibitions. The projects will be related to current Faculty, department and / or outreach needs thus leading to informed student partnership activities.

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.

The first half of this module covers various applications of statistical physics to model share prices and financial markets. This mathematics is then applied to calculating prices for some examples of financial derivatives. The second half of the module then focusses on optimization problems with examples including logistics, aerospace, traffic control and finance (which includes pricing, risk managements and portfolio optimizations in financial markets). There is a particular focus on the role of quantum optimization and the use of quantum computer algorithms in finance.

This module introduces six advanced topics in physics. Students will be assessed on only four of these topics, with individuals self-selecting the contact sessions, coursework options and exam questions that reflect their preference. An indicative list of these six topics include: biological physics, special relativity, physics of electronic & photonic materials, cosmology, nuclear astrophysics, and quantum computing.

Quantum computers are built around a central processing unit which is a physical device operating according to the rules of quantum mechanics. This module teaches the principles of how quantum processors are built and how they function. The module follows the superconducting architecture, which currently has a significant role in the industry and has been widely studied and implemented. The module will start with reviewing the basic physics required to understand superconducting qubits and the theory of superconducting circuits. It will then continue to the operation of such qubits to perform gates, storage, and readout. After studying the basic building blocks and operations, the module will discuss early demonstrations of important algorithms on superconducting processors. These will lead us naturally to the important topics of improving performance through protection of coherence, advanced control, and validation. The last part of the module will focus on state-of-the-art superconducting processors, focusing on the various challenges in scaling up and the strategies that the industry is pursuing to overcome them.

This module covers circuit-based quantum computers and some of the algorithms that can be implemented using them. The idea of a classical computational algorithm and its complexity is introduced, and used as a language to discuss quantum computational algorithms. Components of quantum circuits are discussed individually, and then built up to show how algorithms such as the quantum Fourier transform and Grover¿s search algorithm can be implemented, and how such algorithms can be used in applications such as factorizing integers using Shor's algorithm. The Python package qiskit is introduced and used as a tool to implement the algorithms on simulated quantum computers.

This module introduces students to inviscid fluid flows including surface waves. By the end of the module, students should be able to recognise dominant features of fluid motion, and to derive some simple solutions of the equations of motion. Students should also have an appreciation of the force balances that produce various classes of flows.

This module will build on the rudimentary knowledge of Atoms and Quanta taught in Level FHEQ 4 (PHY1039) and apply the ideas taught in the previous Quantum Physics module (PHY2069) to describe the properties of atoms, including the physics behind the full structure of atomic spectra. It will introduce the effects on atoms due to electric and magnetic fields. The physics of diatomic molecules will be discussed, including how spectroscopic techniques can be used to study more complex molecules. Finally by understanding how atoms interact with light, the module will introduce the principles of the laser, including basic explanations of common lasers, such as solid state and gas lasers. The module includes a laboratory component in which ideas from the lectures will be explored experimentally.

This module considers develops both the thermodynamic and statistical descriptions of energy and entropy. In addition it builds on the introductory Level FHEQ 4 computing modules to develop the skills needed for computational physics. The module will explore various meanings and definitions of entropy. Knowledge of thermodynamics will then be applied to problem solving. The module will build upon the knowledge obtained of the laws of thermodynamics introduced in Properties of Matter at Level FHEQ 4. It will introduce additional thermodynamic theory and show how statistical physics allows us to calculate thermodynamic functions such as the entropy. The computational physics component will develop the student’s skills in solving both ordinary and partial differential equations, in the context of both quantum and thermal physics.

The module will introduce the physical significance and the mathematical methods (and selected theorems) of the operators of vector calculus: div, grad and curl in different co-ordinate systems. The module will introduce the partial differential equations of mathematical physics and their solution for selected physical systems involving different co-ordinate systems and involving time. The module will introduce the foundations of electromagnetism, up to Gauss’ Law and Laplace’s equation, as a major application of the vector calculus and partial differential equations techniques.

The module reprises electrostatics (Gauss’ Law) and proceeds to introduce electromagnetic theory through a development of Maxwell’s Equations and concepts associated with the electric and magnetic polarisation of materials. The module introduces electromagnetic wave theory and its applications to a range of traditional applications and problems as well as the use of Fourier processing for wave signal analysis.

The general properties of nuclei and radioactivity are studied, with an introduction to the deeper structure of elementary particles and the Standard Model. The nuclear physics includes alpha- and beta- and gamma-ray decay, nuclear fission and models of nuclear structure. The high energy physics includes the quark structure of hadrons, CPT conservation and CP violation and the impact of conservation rules on simple reactions of elementary particles.

This module has two independent halves, on crystallography and on optical applications of solids. - The crystallography half-module will describe crystal structures, crystalline lattices and their study with X-rays. It will introduce the concept of quantisation of lattice vibrations (phonons). - The optical applications half-module will describe band theory of solids, how it can be controlled, and how it affects the absorption, reflection, propagation, emission from molecules to nano-materials to bulk solids. Modern optical and photonic devices such as semiconductor lasers, solar cells, nuclear radiation detectors and quantum computer qubits will be introduced.

The Quantum Physics course focuses on the basic formalism of quantum mechanics, its physical interpretation and its application to simple problems. The emphasis is on elementary (one-dimensional) quantum physics, including the infinite-potential well, the parabolic well, one-dimensional step and barrier potentials. 

This module presents a complete introduction to modern astronomy and astrophysics. We start by introducing astronomy as a unique science; measurement in astronomy (position on the sky, velocity and distance); and multi-messenger probes. We then discuss acceleration due to gravity (the dominant force in the Universe) and we show that timescales are typically so long that we must use models to calculate what happened in the past and what will happen in the future. Armed with an understanding of how to make measurements in astronomy and how to model gravity, we then move from the smallest scales to the largest, studying first the interstellar medium from which stars form; stellar structure and evolution; and stellar remnants (white dwarfs, neutron stars and black holes). We compare and contrast the latest models for how planets form and we discuss the prospects for detecting life and intelligent life beyond Earth. Finally, we discuss the formation and evolution of galaxies in the Universe and the Universe as a whole. We show that the Universe appears to be mostly dark: dark matter (~22%) and dark energy (~74%). Understanding what these mysterious components are is one of the key challenges for physics in the next decade. The module includes either a computer or telescope project. Students enrolled in physics with astronomy with undertake the telescope project where (weather willing) students will gain hands on experience of taking real observational data. They will develop software tools to analyse and interpret these data and write up a final report. Students not enrolled in physics with astronomy will undertake a computational project of similar scope and length, also culminating in a final report.

Expected prior learning:  Module EEE2042 – Electronic and Photonic Devices, or equivalent learning, is advisory but not required. Module purpose:  Semiconductor devices and optoelectronics play a major technology enabling amongst other things the internet. The course is given via a series of lectures and aims to give a background to the interaction of light with key photonic materials and devices. This module will introduce students to modern energy efficient electronic and photonic devices concentrating on the fundamental science of operation, device structure and characteristics.

This module introduces fundamental concepts in analytical dynamics and illustrates their application to real-world problems. The module covers the calculus of variations, Lagrangian and Hamiltonian formulations of dynamics, Poisson brackets, canonical transformations and symplectic manifolds. The module also leads to a deeper understanding of the role of symmetries and conservation laws in dynamical systems. This module builds on material from MAT1036 Classical Dynamics and lays the foundations for MAT3039 Quantum Mechanics.

This 30 credit project module is designed to give students the opportunity to explore an area of interest in physics in some depth, either through experimental, theoretical or computational means, or in the form of a literature survey.  The module also develops generic professional skills such as teamwork, scientific writing and professional ethics.  The module involves writing a dissertation and an oral assessment  

The course will follow the historical development of the main medical imaging techniques. The first part will consider, from a theoretical perspective, the fundamentals of X-ray image formation both in the planar modality and in the Computed Tomography modality. Elements of image processing and image reconstruction will be addressed. The second will look at the physical principles and methods of Nuclear Medicine. The third will look at the principles underlying the application of diagnostic ultrasound in medicine. The fourth will consider Magnetic Resonance Imaging (MRI), one of the most important techniques of medical imaging used in hospitals today. In parallel to the related theoretical classes, laboratory experiments will be carried out on X-ray imaging and ultrasound.

In this module, students will learn key methods adopted in astrophysics to carry out advanced research: scientific computing, statistics, data analysis, machine learning. Much of the course develops highly transferrable skills that apply to science research in general. The goal is to ensure that students are well-prepared for either their research year or their future careers.

This module aims to provide an advanced level understanding of the physics of stars and nuclear astrophysics. In particular, the course will provide an understanding of advanced nucleosynthetic pathways, an analytical underpinning of resonant reaction rates, together with the experimental techniques involved in their determination.

The module will introduce students to key concepts in education as well as the tools and strategies for effective public engagement in their discipline areas and for different audiences. Students will gain practical experience by planning, implementing, and evaluating an education or public engagement-based activity. Opportunities will also exist for classroom (e.g. school; early-year University) teaching experience and / or involvement in external exhibitions. The projects will be related to current Faculty, department and / or outreach needs thus leading to informed student partnership activities.

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.

The first half of this module covers various applications of statistical physics to model share prices and financial markets. This mathematics is then applied to calculating prices for some examples of financial derivatives. The second half of the module then focusses on optimization problems with examples including logistics, aerospace, traffic control and finance (which includes pricing, risk managements and portfolio optimizations in financial markets). There is a particular focus on the role of quantum optimization and the use of quantum computer algorithms in finance.

This module introduces six advanced topics in physics. Students will be assessed on only four of these topics, with individuals self-selecting the contact sessions, coursework options and exam questions that reflect their preference. An indicative list of these six topics include: biological physics, special relativity, physics of electronic & photonic materials, cosmology, nuclear astrophysics, and quantum computing.

Quantum computers are built around a central processing unit which is a physical device operating according to the rules of quantum mechanics. This module teaches the principles of how quantum processors are built and how they function. The module follows the superconducting architecture, which currently has a significant role in the industry and has been widely studied and implemented. The module will start with reviewing the basic physics required to understand superconducting qubits and the theory of superconducting circuits. It will then continue to the operation of such qubits to perform gates, storage, and readout. After studying the basic building blocks and operations, the module will discuss early demonstrations of important algorithms on superconducting processors. These will lead us naturally to the important topics of improving performance through protection of coherence, advanced control, and validation. The last part of the module will focus on state-of-the-art superconducting processors, focusing on the various challenges in scaling up and the strategies that the industry is pursuing to overcome them.

This module covers circuit-based quantum computers and some of the algorithms that can be implemented using them. The idea of a classical computational algorithm and its complexity is introduced, and used as a language to discuss quantum computational algorithms. Components of quantum circuits are discussed individually, and then built up to show how algorithms such as the quantum Fourier transform and Grover¿s search algorithm can be implemented, and how such algorithms can be used in applications such as factorizing integers using Shor's algorithm. The Python package qiskit is introduced and used as a tool to implement the algorithms on simulated quantum computers.

This module supports students’ development of personal and professional attitudes and abilities appropriate to a Professional Training placement.  It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment.  The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives.  Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement.  Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written and presentation skills.

This module supports students¿ development of personal and professional attitudes and abilities appropriate to a Professional Training placement. It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment. The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning and is a process that involves self-reflection. Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written skills.

This module supports students¿ development of personal and professional attitudes and abilities appropriate to a Professional Training placement. It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment. The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives. Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written skills.

This module introduces students to inviscid fluid flows including surface waves. By the end of the module, students should be able to recognise dominant features of fluid motion, and to derive some simple solutions of the equations of motion. Students should also have an appreciation of the force balances that produce various classes of flows.

This module presents a complete introduction to modern astronomy and astrophysics. We start by introducing astronomy as a unique science; measurement in astronomy (position on the sky, velocity and distance); and multi-messenger probes. We then discuss acceleration due to gravity (the dominant force in the Universe) and we show that timescales are typically so long that we must use models to calculate what happened in the past and what will happen in the future. Armed with an understanding of how to make measurements in astronomy and how to model gravity, we then move from the smallest scales to the largest, studying first the interstellar medium from which stars form; stellar structure and evolution; and stellar remnants (white dwarfs, neutron stars and black holes). We compare and contrast the latest models for how planets form and we discuss the prospects for detecting life and intelligent life beyond Earth. Finally, we discuss the formation and evolution of galaxies in the Universe and the Universe as a whole. We show that the Universe appears to be mostly dark: dark matter (~22%) and dark energy (~74%). Understanding what these mysterious components are is one of the key challenges for physics in the next decade. The module includes either a computer or telescope project. Students enrolled in physics with astronomy with undertake the telescope project where (weather willing) students will gain hands on experience of taking real observational data. They will develop software tools to analyse and interpret these data and write up a final report. Students not enrolled in physics with astronomy will undertake a computational project of similar scope and length, also culminating in a final report.

This module introduces fundamental concepts in analytical dynamics and illustrates their application to real-world problems. The module covers the calculus of variations, Lagrangian and Hamiltonian formulations of dynamics, Poisson brackets, canonical transformations and symplectic manifolds. The module also leads to a deeper understanding of the role of symmetries and conservation laws in dynamical systems. This module builds on material from MAT1036 Classical Dynamics and lays the foundations for MAT3039 Quantum Mechanics.

In this module, students will learn key methods adopted in astrophysics to carry out advanced research: scientific computing, statistics, data analysis, machine learning. Much of the course develops highly transferrable skills that apply to science research in general. The goal is to ensure that students are well-prepared for either their research year or their future careers.

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.

The first half of this module covers various applications of statistical physics to model share prices and financial markets. This mathematics is then applied to calculating prices for some examples of financial derivatives. The second half of the module then focusses on optimization problems with examples including logistics, aerospace, traffic control and finance (which includes pricing, risk managements and portfolio optimizations in financial markets). There is a particular focus on the role of quantum optimization and the use of quantum computer algorithms in finance.

This module introduces programming in Python for data science, with a focus on data pre-processing, data mining and analysis, machine learning and deep learning. Besides the practical hands-on experience with writing code, this course also covers the theoretical background on different data analysis techniques and machine learning approaches. The goal is to develop an understanding of how information can be extracted from data and how this information can be further used to make predictions, but importantly how this is done practically in terms of writing clear and transparent source code. Using real-world data sets and illustrative examples, this course will help to develop a theoretical understanding of data science as well as practical experience by developing useful software tools. Many of the techniques acquired through this module are likely to be of potential use in the dissertation project.

The early part of the Research Year involves a combination of developing generic research skills associated being on a research-based physics placement, and acquiring specific skills related to the particular project to enable successful completion of the students own research by the end of the research year. This module reflects parts of the specific skills developed for the students own project in the first half of the Research Year

This module introduces programming in Python for data science, with a focus on data pre-processing, data mining and analysis, machine learning and deep learning. Besides the practical hands-on experience with writing code, this course also covers the theoretical background on different data analysis techniques and machine learning approaches. The goal is to develop an understanding of how information can be extracted from data and how this information can be further used to make predictions, but importantly how this is done practically in terms of writing clear and transparent source code. Using real-world data sets and illustrative examples, this course will help to develop a theoretical understanding of data science as well as practical experience by developing useful software tools. Many of the techniques acquired through this module are likely to be of potential use in the dissertation project.

This 15-credit M-Level module introduces important topics and techniques in theoretical physics that have a wide range of applications in many areas physics and engineering and which the students will not have met before. Both the mathematical techniques and their applications are covered at a level appropriate for Masters level students coming to the end of their degree and who should be able to pull many different ideas in theoretical physics together.

This module aims to provide an advanced level understanding of explosive nuclear astrophysics and the physics of stars. In particular, the course will provide an analytical underpinning of resonant reaction rates, together with the experimental techniques involved in their determination, as well as a theoretical treatment of nuclear reactions and celestial objects.

This module will introduce the students to the principles and formalism of General Relativity and its applications to Black Holes and astrophysical phenomena.

The course provides an introduction to nuclear energy generation and applications of nuclear science. Nuclear reactors, their physics and operation are described. Nuclear reactor safety case work is also discussed. Future potential energy generation mechanisms such including nuclear fusion will be discussed. The module will also present a range of applications of radioactivity measurement including aspects of Environmental Science and Medical Diagnogstics and treatment therapy. The module will include some aspects of calculus and first order differential equations.