Quantum Mechanics introduces a dramatically new and rich understanding of the universe. In addition to providing a much deeper insight into the world of atoms and subatomic particles than afforded by classical Newtonian physics, Quantum Mechanics underpins advances in science across all disciplines, from molecular biology to astrophysics. This subject provides a rigorous mathematical formalism for advanced quantum mechanics, laying the foundation for further fundamental theoretical physics and research-level experimental physics in frontier areas such as quantum communication and quantum computation.

The subject describes the Hilbert-space formulation of quantum wave mechanics, including density matrix descriptions for single and joint Hilbert space systems; symmetries and conservation laws including rotations and angular momentum; many-body systems of identical particles; time-dependent perturbation theory, and scattering theory.

This subject introduces quantum field theory, the combination of quantum mechanics and relativity that explains the fundamental structure of matter and the physics of the early universe. The course has an emphasis on quantum electrodynamics. Specific topics will include an introduction to classical field theory, the Euler-Lagrange equations and Noether’s theorem; the Dirac and Klein-Gordon equations; the quantisation of free scalar, Dirac and vector fields; covariant perturbation theory, the Smatrix and Feynman diagrams; the computation of elementary processes in quantum electrodynamics.

This subject provides an advanced introduction to Einstein's theory of general relativity. Specific topics may inlcude special relativity, manifolds and curvature, experimental tests, Einstein's equations, the Schwarzschild solution and black holes, weak fields and gravitational radiation. Examples will be drawn from particle physics, astrophysics and cosmology.

This subject provides an advanced introduction to non-equilibrium statistical mechanics. The subject focuses on collective phenomena in complex many-body systems with an emphasis on diffusive processes, stability and the emergence of long-range order, with examples drawn from physics, chemistry, biology and economics. Specific topics include diffusive stochastic processes (Fokker-Planck equations), birth-death processes (master equations), kinetic transport, and spatio-temporal pattern formation in unstable nonlinear systems (bifurcations, chaos, reaction-diffusion equations).

This subject provides an advanced introduction to physical cosmology. Specific topics may include the isotropic homogeneous Universe, the Robertson Walker metric, the Friedmann equations, baryogenesis, inflation, big-bang nucleosynthesis, the recombination era, density fluctuations as the origin of galaxies, the cosmic microwave background, linear and non-linear growth of structure, the Press-Schechter mass function, reionization of the IGM and gravitational lensing. Examples are drawn from past and current cosmological observations.

Particle Physics is the study of the elementary constituents of matter, and the fundamental forces of nature. The subject introduces modern elementary particle physics, with an emphasis on the theoretical description of the Standard Model of Particle Physics and its experimental basis. Specific topics may include basic group theory; parity and CP violation; global and local symmetries; non-abelian gauge theory; QCD and the quark model; running coupling constants and asymptotic freedom; spontaneous symmetry breaking and the Higgs mechanism; the complete Standard Model Lagrangian; interactions of particles with matter; accelerators and detectors; deep inelastic scattering and structure functions; flavour mixing and neutrino oscillations.

This subject provides an advanced introduction to condensed matter physics. The general topics covered are (i) experimental and theoretical aspects of the characterisation of condensed matter using electrons and x-rays and (ii) the quantum model of solids and its relevance to semiconductor and mesoscopic physics. Specific topics covered may include: (i) the imaging of condensed matter at the atomic level and (ii) the determination of how atoms are bonded; (iii) application of imaging beyond the nanoscale; (iv) magnetism; (v) superconductivity; (vi) the properties of semiconductor devices and (vii) mesoscopic systems.

Optics and photonics are vibrant international research areas, advancing many aspects of modern life. From the determination of the structure and function of biomolecules to the study of stars and galaxies; from high-efficiency lighting to innovative display technologies, our understanding of optics relies on fundamental underpinnings in advanced quantum mechanics and wave theory.

The course includes the foundations of modern optical theory, including Fourier transforms in optics and diffraction-based imaging; non-linear optical processes such as generation of white light from femtosecond laser pulses, gigahertz optical modulators, and liquid crystal displays; light-atom interactions, the Einstein description of lasers, and optical Bloch equations; holography; quantumoptics including zero-point energy and vacuum fluctuations; quantum states of light and quantum squeezing; laser cooling of atoms, atom interferometry, and Bose-Einstein condensation.

Students will develop both analytic and computational problem-solving methods, the latter using standard tools such as MATLAB.

What conclusion can be drawn from a pool of data? How can a scientist draw meaningful conclusions while not overreaching? How can modelling help the scientist interpret data? This subject will address these questions by teaching students critical thinking and data analysis skills. After completing this subject students will understand the basic principles of sampling and experimental design, how the results of statistical analyses are reported, the statistical thinking behind common statistical procedures and will be able to carry out a range of standard statistical techniques.

Modern science and business makes extensive use of computers for simulation, because complex real-world systems often cannot be analysed exactly, but can be simulated. Using simulation we can perform virtual experiments with the system, to see how it responds when we change parameters, which thus allows us to optimise its performance. We use the language R, which is one of the most popular modern languages for data analysis.

What is conflict of interest? What should a scientist do when they find fraud is occurring on a scientific research team? How does a scientist write and defend an animal ethics submission and get it approved? What are the ethical issues associated with peer review? This subject is intended to give students a broad overview of research ethics in a scientific context. It will include topics on scientific integrity; conflicts of interest; data recording management; authorship and peer review; animal experimentation and regulations; privacy and confidentiality of records; and, finally, research in humans.

This subject will give an overview of the tools required to operate successfully in an organisational environment. The focus of the subject is the internal workings of an organisation and specifically addresses three main areas: working with people, managing budgets and understanding basic accounting, and managing processes and projects.

This subject is designed to provide students with detailed training in statistical methods as applied to the design and analysis of projects undertaken by postgraduate students, across all disciplines.

As a scientist, it is not only important to be able to experiment, research and discover, it is also vital that you can communicate your research effectively in a variety of ways. Even the most brilliant research is wasted if no one knows it has been done or if your target audience is unable to understand it.

In this subject you will develop your written and oral communication skills to ensure that you communicate your science as effectively as possible. We will cover effective science writing and oral presentations across a number of formats: writing a thesis; preparing, submitting and publishing journal papers; searching for, evaluating and citing appropriate references; peer review, making the most of conferences; applying for grants and jobs; and using social media to publicise your research.

You will have multiple opportunities to practice, receive feedback and improve both your oral and written communication skills.

Please note: students must be undertaking their own research in order to enrol in this subject.

Why is it essential that scientists learn to communicate effectively to a variety of audiences? What makes for engaging communication when it comes to science? How does the style of communication need to change for different audiences? What are the nuts and bolts of good science writing? What are the characteristics of effective public speaking?

Weekly seminars and tutorials will consider the important role science and technology plays in twenty-first century society and explore why it is vital that scientists learn to articulate their ideas to a variety of audiences in an effective and engaging manner. These audiences may include school students, agencies that fund research, the media, government, industry, and the broader public. Other topics include the philosophy of science communication, talking about science on the radio, effective public speaking, writing press releases and science feature articles, science performance, communicating science on the web and how science is reported in the media.

Students will develop skills in evaluating examples of science and technology communication to identify those that are most effective and engaging. Students will also be given multiple opportunities to receive feedback and improve their own written and oral communication skills.

Students will work in small teams on team projects to further the communication skills developed during the seminar programme. These projects will focus on communicating a given scientific topic to a particular audience using spoken, visual, written or web-based communication.

The physical, social and engineering sciences make widespread use of numerical simulations and graphical representations that link underlying their theoretical foundations with experimental or empirical data. These approaches are routinely designed and conducted by researchers with little or no formal training in computation, assembling instead the necessary skills from a variety of sources. There is an art to assembling computational tools that both achieve their goals and make good effective use of the available computational resources.

This subject introduces students to a wide range of skills that are commonly encountered in the design and construction of computational tools in research applications:

• Formulation of the task as a sequence of operations or procedures that express the context of the assigned problem in a form accessible to digital computing (Mathematica).
• Implementation of this formulation using computer languages appropriate for numerically intensive computation (C, C++, Fortran)
• Modularization of computationally intensive tasks, either as user-written procedures or existing libraries (for example BLAS, lapack)
• Documentation of the code to explain both its design, operation and limitations (LaTeX)
• Instrumentation of the code to verify its correct operation and monitor its performance (gprof)
• Optimization of the code, including the use of parallelization (OpenMPI)
• Visualization of data using graphical packages or rendering engines (Geomview, OpenGL)
• Interaction with the code through a graphical user interface (Python, Matlab)

These skills are introduced to the student by undertaking a short project that is selected in consultation with the Subject Coordinator.

This subject will introduce students to the world of quantum information technology, focusing on the fast developing area of quantum computing. The subject will cover basic principles of quantum logic operations in both digital and analogue approaches to quantum processors, through to quantum error correction and the implementation of quantum algorithms for real-world problems. In lab-based classes students will learn to use state-of-the-art quantum computer programing and simulation environments to complete a range of projects.