Mesoscopic Physics / Topological Phases of Matter tutorial
Panel Discussion
Scientific Communication
Poster session
Quantum Information Processing (QIP)
Quantum Information Processing is one of the most exciting applications of modern quantum physics, and has become a flourishing interdisciplinary field in its own right. In this short course we will concentrate on some aspects of the subject most relevant to condensed matter systems. We will start by defining qubits and quantum gates, then introduce quantum operations as a model for the action of a quantum system in a noisy environment and the Kraus representation theorem which provides a composite way to represent them. Then we will move on to quantum error correction and its connection to classical codes, and briefly discuss the physics of two of the most important solid-sate qubits: impurity spins in semiconductors and superconducting circuits. Finally we will talk about two alternatives to the standard gate model of quantum computation that particularly lend themselves to solid-state systems: adiabatic quantum computation (and the related topic of quantum annealing), and the topological computation (and related topological codes).
Andrew is Professor of Physics in the UCL Department of Physics and Astronomy and directory of the London Centre for Nanotechnology; formerly Junior Research Fellow at St John’s College Oxford (1989-93), Postdoctoral Fellow at the IBM Zurich Research Laboratory (1991-92), and Lecturer in Physics at the University of Durham (1993-95). He is Director of the new EPSRC Centre for Doctoral Training in Delivering Quantum Technologies, starting in 2014.
Quantum Information Processing / Topological Phases of Matter tutorial
Quantum Solids, Many Worlds Interpretation and the Exchange Interaction
Soft Condensed Matter (SCM)
This course deals with the physics of soft materials. As the name suggests these materials are soft to touch (e.g. jello, creams, pastes etc.) as opposed to hard ones (e.g. metals, alloys)which fall under the purview of “Solid State Physics”. The important distinction between soft materials as opposed to their hard counterparts is that entropy and not internal energy dictates their equilibrium properties. Further these materials mostly comprise of organic molecules that interact weakly and as a result their properties are strongly influenced by thermal fluctuations, external fields, and boundary effects. This strong ‘susceptibility’ of soft matter leads to many fascinating properties. We will review a few generic features of soft materials, e.g. dominance of entropy, interplay between broken-symmetry and dynamic mode structure and topological defects that are common to such systems. The outline is as follows i) Introduction to soft condensed matter physics, (ii) Liquid Crystals and Polymers (iii) Fluid Membranes, (iv) Fluctuations and response of non-equilibrium soft systems.
Buddhapriya (Buddho) is a senior lecturer in the biological physics group at the University of Sheffield. His main research interests include soft condensed matter physics and biological physics.
Soft Condensed Matter / Strongly Correlated Quantum Systems tutorial
Statistical Mechanics (STM)
Statistical Mechanics aims to provide a macroscopic description of a physical system starting from knowledge of its microscopic properties. The methodology and techniques are widely used throughout condensed matter physics and are also today being applied to understand the dynamics of model ecologies, economies and societies. In these lectures, we will revisit the equilibrium properties of matter – such as phase transitions and universality – from the perspective of dynamics (as opposed to statics, as is typically done in undergraduate courses). Then we will examine successively further-from-equilibrium systems, ending with a discussion of fluctuations in driven systems, a subject currently generating considerable excitement in this field.
Richard Blythe is a Professor of Complex Systems at the University of Edinburgh. Since his PhD days, he has been researching models and theories for nonequilibrium dynamical systems. Applications of these models include transport in biological systems, traffic flow, population dynamics and language change.