Non-equilibrium Systems Group

Gunnar Pruessner

Reader in Mathematical Physics
  • Department of Mathematics
  • Room No: 6M32
  • Telephone No.: +44 (0)20 759 48534
  • E-Mail Address: g DOT pruessner AT imperial DOT ac DOT uk
    my @physics.org address is no longer in use
  • Office hours: Mon 11am-12noon, Fri 1pm-2pm
    [Please email beforehand.]
Full address: Gunnar Pruessner
Department of Mathematics
Imperial College London
180 Queen's Gate
London SW7 2AZ
 Photo of Gunnar

Complex Systems Dynamics Meeting Series

Teaching

Publications

Students:

 Callum Britton (PhD, field theory)
Emir Sezik (PhD, field theory)
Kevin Gao (MSci, data analysis)
Rehman Oomer (MSci, field theory)>
James Corcoran (MSci, stochastic processes)
Chloe Chan (MSci, field theory)

Research Interests and Projects:

Non-equilibrium Systems

All of life is driven by non-equlibrium processes. There is lots of exciting new physics hiding in plain sight, some of which is exemplified below.

Field theory of active matter

In active matter, individual agents draw on an energy supply from a medium to perform work or to self-propel. Paradigmatic examples are flocks of birds, collection of cells or artificial Janus particles. Even the simplest interactions with an external potential produce unexpected phenomena that are unthinkable in equilibrium. Field theory provides a very powerful tool to capture many degrees of freedom as they interact with external potentials as well as each other.

Entropy production

Entropy production measures the degree to which equilibrium is broken. Different tools exist to calculate it on the basis of microscopic or coarse-grained properties. A thorough theoretical understanding of entropy production is needed to efficiently extract useful work from a microscopic biological process. Many questions still need to be answered, such as how different tools are linked and how to coarse-grain more systematically.

Reaction and diffusion processes in biochemistry and cell biology

Many processes within cells and displayed by cells are subject to randomness and fluctuations, for example polymerisation and depolymerisation of microtubules, movement of motor proteins and interaction between cells and their motility. A quantitative description of these fluctuations helps to determine the underlying mechanisms and to predict behaviour. Apart from standard techniques from stochastic processes, where space and small numbers of constituents are involved, field theoretic techniques can be brought to bear.