Physics with Computing MPhys (Hons) degree

Physics is completely dependent on rigorous, scientific experiments in
both the discovery of new phenomena and in the testing of physical hypothesis.
To be an experimental physicist requires the ability to make accurate
measurements of physical properties, to gain insight from the observation of
natural phenomena, and to design and construct experiments that can
discriminate between different hypotheses. This module will provide an
environment in which these skills can be gained and will, in addition to training in
basic skills, have a strong emphasis of the creative aspect of designing
experiments.

A part aim for this module is to enable students to become aware of and develop their academic, professional and personal skills through Personal Best. Personal Best is a development programme available to all students at Loughborough University

As with all science and engineering disciplines, computing has become part of the core toolset of the professional physicist. Through problem solving, this module introduces its use for modelling and simulation of physical systems to students of all levels, regardless of computational background. It aims to introduce good programming practice and develop skills in scientific computation. Good programming practice is emphasised throughout the module so that students should begin to appreciate the discipline of programming beyond that of developing simulations of simple physical systems. By the end of the module students should be equipped with the skills so that they can make meaningful progress on substantive problems that add real value to current technological problems.

The overarching aim is to equip students with the necessary skills and knowledge to effectively utilise computational tools for solving complex problems in physics, while instilling ethical standards and best practices in coding to uphold integrity and reliability in scientific research.

The two key aims of this module are (i) to introduce classical and analytical mechanics and some of the foundational principles of modern physics, and (ii) to introduce physics thinking, the world view of the physicist and their problem solving approaches.

The students will gain knowledge in concepts in classical mechanics and experience in problem-solving. They will use foundational ideas and principles such as the principle of least action. Skills range from using vectors to represent a system and applying Newton's laws, through to determining and analysing the equations of motion of a system using analytical mechanics and Noether's theorem. The student should be able to use these ideas and principles to begin to be able to set up and solve models to better understand physical systems within the area of classical mechanics thus providing a strong foundation for the modules to be studied later in the programme.

The aims of this module are to

• provide an overview of the history and
  philosophy of science and familiarise students with the basic concepts and terminology of philosophy.
• introduce elements of modern practice from
  existing departmental research
• introduce techniques, methods and habits that support physical and mathematical reasoning.

This module aims to provide a comprehensive understanding of electromagnetic theory, integrating Maxwell's equations, the principles of relativity, and the covariant formulation of electromagnetism with an exploration of gauge fields, wave propagation, and optics. It seeks to equip students with a deep theoretical foundation and analytical problem-solving skills, emphasising the unification of electric and magnetic fields, the implications of gauge invariance, and the application of electromagnetic principles to modern physics and technology.

Building on existing programming competence, the aim of this module is to equip students with practical approach to computational problem solving supported by a formal understanding of data structures, algorithm design, and introduction to numerical optimisation and regression.

The aim of this module is to equip students with mathematical concepts and methods applicable to theoretical physics.

Quantum mechanics is foundational to modern physics and technology, underpinning advancements in fields like quantum computing and materials science. It challenges classical notions of reality with concepts like entanglement and superposition, offering deep insights into the nature of the universe. Studying quantum mechanics is crucial for innovation and research, equipping individuals with the mathematical and physical skills needed to understand nature and contribute and create emerging and future technologies.

Overall, the module aims to equip students with a solid foundation in quantum mechanics and its applications to a level where they are able to critically access recent advances in the subject. Our unique programme leverages students existing knowledge of Hamiltonian mechanics to provide deep insights into the similarities and differences between quantum and classical physics. We further provide a comprehensive introduction to the key contributions of quantum mechanics to science and problem solving in these arears. Topics include tunnelling, hydrogenic atoms as well as the chemical bond and molecular spectra.

Building on Physics Laboratory I, the central aim here is for the student to become a competent experimental physicist who not only understands good experimental technique but can also engineer laboratory equipment and instrumentation.

This module includes a mix of experimental practical sessions, computer workshops and seminars to develop the key skills of an experimental physicist and enhance our students' employability. Students will have the opportunity to design and build their own equipment, collect and analyse data, and link their experimental work to theories that they are investigating in other modules of their programme. Both semesters include a long form project spread over multiple weeks, and in Semester 2 this takes the form of a group project where students can choose their own area of interest.

The aim of this module is for students to become capable in the use of computers in the solution of physics-based problems and experience in a variety of software and language solutions. This involves developing an understanding of the application of computers not just for but also beyond numerical simulation for modelling and simulation related to real-world quantum physics, condensed matter and semiconductor device physics.

Building on existing programming competence, the aim of this module is to equip students with practical approach to computational problem solving supported by a formal understanding of data structures, algorithm design, and introduction to numerical optimisation and regression.

The aims of this module are to:

• further develop aptitude in physics in areas pertinent to Loughborough research strengths. The focus here is on condensed matter and solid state physics.
• to apply notions of electromagnetism, quantum mechanics and statistical mechanics to explain the stability of matter and basic physical properties of metals, insulators and semiconductors starting from microscopic principles.
• to understand the principles of modern characterisation techniques of materials.
• to relate microscopic parameters to properties of solids, often based on the powerful method of dimensional analysis.
• to estimate numerical values of material quantities.
• to retrieve and make use of scientific resources, experimental data from papers and online databases.

The aims of this module are to provide students with a comprehensive understanding of the fundamental principles of thermodynamics and statistical physics. This will include: developing a solid understanding of the laws of thermodynamics and their applications; exploring the microscopic origins of macroscopic thermodynamic properties through kinetic theory; analysing phase transitions and critical phenomena; introducing the principles of statistical physics and their role in describing thermal systems at the microscopic level.

The aim of this module is to provide the student with a set of techniques used to develop AI systems in both theory and practice.

The ability to undertake research, and apply the scientific method and physics thinking in seeking solutions to advanced open-ended problems is one of the key skills that all physicists should have. The MPhys programme offers students the opportunity to contribute towards departmental research in part D. The module develops, through a combination of lectures and lab-based experiments, a range of skills that will support the more advanced research expected in the MPhys project. This module seeks to make clear the interplay between experimental and theoretical physics at an advanced level.

Statistical mechanics main purpose is to study properties of assemblies of systems in terms of physical laws. Its applications include many problems in the fields of physics, biology, chemistry, economics, neuroscience.
In Advanced Statistical Mechanics we will develop the fundamental formalisms of equilibrium statistical mechanics from microscopic properties of systems (which include electrons, atoms, molecules and magnetic moments on the sites of lattices). Then we will relate them to the
thermodynamic quantities such as internal energy, free energy, entropy, specific heat and related properties of both classical and quantum-mechanical systems. We will discuss real systems from classical and quantum world. The last part of the module will be devoted to phase transitions and their description.

The aims of this module are to introduce a variety of physical phenomena that occur in condensed matter physics and show how they can be understood in terms of microscopic processes.

A crystal interacts with the environment through its surface. Since surface atoms have fewer chemical bonds than atoms inside the crystal, surfaces may differ from bulk crystals in terms of crystallographic order, chemical composition, electronic and ionic conductivity, lattice vibrations, mechanical properties etc. Surfaces need to be studied and understood in order to work with catalysis, metal oxidation, corrosion, adhesion, crystal and thin film growth. Further, both the thin film growth technology and experimental surface science use high vacuum equipment. Thin films are used to manufacture semiconductor electronics, optoelectronics, magnetic data storage, nanostructures, optical, conductive and hard coatings.

You will study interactions of vapour molecules with surfaces, physics and technology of high vacuum, electron spectroscopy, physics of surface structures and diffraction of electrons, preparation of thin solid films and a range of further techniques that are available for the investigation of surfaces and thin films, for example scanning probe microscopy.

This is a 10 credit module from the University-wide language programme.

This module aims to introduce key concepts in data mining and machine learning by focusing on the fundamental ideas that are applicable in both fields.

The module will provide students with the knowledge and experience of using existing tools to analyse and model data associated with practical applications.

The module will also provide a general overview of artificial intelligence (AI), its scope and applications.

The aims of the module are:

• to develop a range of skills within students and provide an early introduction to teaching for those interested in pursuing it, or a related field, as a career.
• to develop confidence and competence in communicating their subject.
• to provide opportunities to devise and develop science and mathematics projects and teaching methods appropriate to the age and ability of those the student is working with.

Photonics is the science of light. The Photonics module aims to equip students with a robust understanding of the fundamental physics underpinning the development and advancement of photonic technologies. It has keen focus on the physical principles at the base of the development that underpin sectors as diverse as healthcare, telecommunications, and defense and the links with classical and quantum background related to light. The vision is to provide the background of key aspects of technologies relevant for impactful careers in a sector that mirrors the innovation and resilience of the UK's £15.2 billion photonics economy.

The module is rooted in the exploration of electromagnetic energy and intensity, monochromatic fields, and complex formalism, and delves into the intricacies of field-matter interaction within both linear and nonlinear optics. Students will engage with core concepts such as, the complex refractive index, and the mechanisms of radiation-matter interaction, the principles underlying absorption and emission of light. By the end of this module, students will have acquired the essential background to understand the physics of photonic technology, the analytical tools to assess photonic systems, and the design skills to develop cutting-edge photonic devices and systems.

The aim of this module is to give students an overview of the uses of physics in medicine and allow them to gain an appreciation of how physics contributes to society. With a thorough grounding in the basics, students will be able to independently investigate more advanced techniques and draw informed conclusions about published health-related research. They will also be more prepared to go into healthcare or healthcare-adjacent careers.

The module aims to give a broad introduction to the theories and experiments of modern elementary particle physics, and to acquaint the student with the latest developments in the subject. Particle phenomenology is introduced, followed by an exploration of the basic concepts of relativistic quantum mechanics, which predicts and explains anti-particles.
The fundamental interactions are described using Feynman diagrams, and Feynman's rules are used to convert these diagrams into amplitudes for scattering calculations to explain results from the big particle physics experiments.

The ideas of quantum field theory, which treats the field as the fundamental entity and all the particles and antiparticles as excitations of their respective fields, and which constitute the standard model of particle physics, are developed.Qualitative concepts around symmetries and symmetry breaking are introduced to explain the pattern of particles that exist and the origin of the nucleons' mass, of which only 1% is explained by the explicit quark masses.

The module aims to provide students with a comprehensive understanding of the physics of semiconducting and magnetic nanodevices, with a particular emphasis on their applications in modern data storage and information processing technologies.

This is a 10 credit module from the University-wide language programme.

This advanced module is specifically designed to expand your research skills by engaging you in high-level scientific inquiry and complex problem-solving. You are expected to apply rigorous scientific methods and in-depth physics knowledge to address difficult open-ended problems with the aim of producing outcomes that could be worthy of publication.

Throughout this intensive project, you will be encouraged to deeply investigate a specialized area of physics that aligns with your knowledge, interests and academic goals. This will involve not only applying your specific expertise in particular areas of physics, but also pushing the boundaries of these fields to create innovative and original research outputs.

The goal of this Master's level project is to develop and practice a wide array of advanced skills, including:
The ability to plan and execute a comprehensive and extended research project that could contribute new insights to the field.
Proficiency in reviewing scientific literature to frame your research within the context of existing knowledge.
Skills in critical analysis, allowing you to evaluate your results and those of others to understand the implications of your findings.
Competence in scientific communication, enabling you to articulate complex ideas clearly and effectively, potentially preparing your work for publication.

By the end of this module, you should have not only enhanced your practical understanding of applying general principles in real-world scenarios, but have the opportunity to produce research that meets the rigorous standards of academic journals, thereby setting a strong foundation for your future career in academia or industry.

This module aims to prepare students to apply modern machine learning techniques to solve various real-world challenges as well as exploring state-of-the- art deep learning technology.

This self-contained module will introduce conventional machine learning methods and new deep neural network development.

With the understanding of the techniques, the students will gain the ability to apply and develop practical machine learning solutions for real-world applications, thus to satisfy industrial needs under different scenarios.

The aims of this module are to provide students with the relevant concepts of robotics from the AI perspective and the skills for developing planning and learning systems that apply to robotics.

The aims of this module are:

• to develop skills in the mathematical modelling of real life situations
• to develop the ability to work effectively in a group

Studying complex systems is vital because it enables us to understand and predict behaviors in real-world scenarios that are otherwise chaotic and unpredictable, from weather patterns to economic markets. This module offers students an essential understanding of the theoretical frameworks and analytical methods needed to approach the complexities of various physical systems.

Exploring universal concepts like chaos, superconductivity, and economic dynamics, it prepares students to tackle challenges in physics and related fields, encouraging a flexible and thorough approach to solving problems in complex systems. It aims to provide basic knowledge in non-linear dynamics and complex stochastic processes, helping students to navigate and contribute to both theoretical and applied physics effectively.

The aim of this module is to introduce students to current ideas on advanced applications of quantum mechanics.

Understanding and applying advanced mathematical methods is crucial for dissecting complex real-world problems across interdisciplinary fields, from environmental science to engineering. This module is designed to enhance students' mathematical prowess, particularly in solving differential equations and employing variational techniques, which are essential for their research endeavors. It delves into a comprehensive study of ordinary and partial differential equations, integral equations, and qualitative analysis, equipping students with the skills to tackle sophisticated models in various scientific domains.

By fostering an in-depth understanding and practical application of these methods, the module not only sharpens students' mathematical abilities relevant to their research but also empowers them with key transferable skills, enabling them to address a broad spectrum of interdisciplinary challenges effectively.

The main aim of this module is to introduce students to computer-based understanding, analysis and processing of images taken with digital cameras. The module introduces various methods and algorithms that allow computers to store images, process images (eg enhance images), extract useful information from images, classify images, and organise image collections.

The module also aims to specify and discuss the problems of image understanding and of various computer vision applications.

The aim of this module is:

• to introduce both supervised and unsupervised methods for learning from data
• to introduce methods of dimensionality reduction
• to introduce the R statistical programming language for implementing methods using real data

This module aims to:

• introduce numerical methods and associated theory for modelling of financial options
• teach students how to implement such numerical methods on computers
• gain experience in interpreting numerical results

The aims of this module are:

• to develop skills in the mathematical modelling of real life situations
• to develop the ability to work effectively in a group

The aim of this module is to obtain understanding of the principles underlying applied superconductivity and the functioning of superconducting devices.

This module is designed to provide an in-depth exploration of the principles, capabilities, and limitations of quantum computers, as well as their various approaches to computation and physical implementations. Students will be introduced to the foundational theories and practical aspects that underpin quantum computing, setting the stage for a comprehensive understanding of this cutting-edge technology. The curriculum aims to bridge the gap between theoretical quantum mechanics and real-world applications, enabling students to grasp both the potential and the challenges of quantum computing.

In addition to foundational knowledge, the module also focuses on the development of critical skills necessary to navigate the complex landscape of quantum technology. Students will learn to critically assess the state of current technology and explore possible future directions for the development of quantum computers. Through detailed study and hands-on practice, the module aims to prepare students for advanced academic research or careers in the quantum computing industry, with the capability to contribute to the development of innovative quantum technologies and solutions.

Monte Carlo methods are an incredibly powerful tool that can be used to accurately model radiation transport for applications in many fields of science, including medical physics. This module aims to (i) introduce Monte Carlo radiation transport methods to model medical physics scenarios; (ii) teach students how to implement such numerical methods on computers, using industry-standard toolkits commonly used in a range of applications (high energy physics, medical physics, space science, etc.); (iii) gain experience in interpreting numerical results.

Photonics stands as a core platform of contemporary technology, driving revolution in fields ranging from telecommunications to healthcare. This Advanced Photonics module is designed to provide students with a comprehensive understanding of advanced (MSc-MPhys level) photonics architectures, devices, and their diverse applications in communication, sensing, and metrology. The module delves into the intricate theoretical and technological framework of photonic waveguides, exploring their roles in manipulating and guiding light with precision.

By engaging with the advanced principles of guided wave modelling and nonlinear photonic systems, students will gain insights into the underpinnings of optical manipulation. Ultrafast optics, a pivotal aspect of the curriculum, will equip students with the expertise to navigate and innovate in the realm of high-speed optical networks, an area of critical importance in our data-driven world, and ultrafast sensing.

Beyond the widespread ramifications of current technologies, the module explores photonics as a platform enabling multidisciplinary research. With applications spanning quantum computing, biomedical imaging, and even renewable energy, the knowledge garnered here is key for future scientists and engineers aspiring to drive innovation across a wide spectrum of disciplines.
The module builds upon a blend of theoretical foundations and practical problem-solving experiences. Students will be poised to contribute to, and shape, a technological market where photonics is already indispensable.