Quantum and Complexity Physics
Physics has the tools for investigating extremely complex systems, finding their most general properties and making detailed predictions about their behaviour.
Members: Alexander Balanov, Claudia Eberlein, Mark Greenaway, Feo Kusmartsev, John Samson, Sergey Saveliev, Alexandre Zagoskin
This creates the grounds for both the development of future technologies, and the understanding of most complicated natural phenomena.
Complexity Physics
Our world is full complex phenomena, which goes well beyond physics, and even science in general. However, physicists can usually provide a very useful insight analysing experimental data within a framework of physical and mathematical concepts: symmetry interactions, conservation laws, dimensionality, stochasticity etc. To model these complex phenomena is critically important for our wellbeing, prosperity, security, health, to name a few. Think about decisions we need to come every day, whether to take a risky medical treatment or where to invest money. Modelling uncertain, noisy, or poorly mathematically formulated phenomena is what Complexity Physics is about.
The Department has a long-standing expertise in modelling complex (chaotic and stochastic) dynamical phenomena in solid state and condensed matter physics, economy (econophysics), human behaviour (psychophysics), complex network dynamics, brain physics, artificial intelligence among many other mathematically challenging phenomena. We have an ongoing collaboration with the Loughborough School of Business and Economics on modelling price dynamics and collective behaviour of economic agents, with School of Sport, Exercise and Health Sciences and Salk Institute for Biological Studies on modelling physiological and psychophysical experiments and now working on extending our research towards geological, populational, ecological, and environmental research.
Quantum Engineering
The fabrication and control of macroscopic artificial quantum coherent structures, such as quantum bits (qubits), quantum computational devices and simulators, quantum sensors and quantum metamaterials, have achieved significant progress over the last 20 years. The fundamental impossibility of a direct modelling of such systems with classical means requires developing new approaches to their design, characterization, and optimization, which constitute an emerging discipline of quantum engineering. The development of this discipline will play the decisive role in the Second Quantum Revolution.