Understanding how chemical reaction networks can support steady states out of equilibrium is of crucial importance in the study of the origin of life, and in the study of cell metabolism. Recent advances in non-equilibrium statistical physics strongly constrain models for such behaviour, but a comprehensive framework is lacking. This project will involve simulating the dynamics of chemical reaction networks and testing a theoretical framework proposed by the supervisor to quantify non-equilibrium steady states. This framework aims to play the same fundamental role in the physics of large chemical reaction networks as the dynamical matrix, with its concomitant quasiparticles, plays in condensed matter physics. After validating the simulations and theory on model systems, you will simulate the metabolism of e-coli and yeast using publicly available data. You will test the theory on these organisms, and then compare their behaviour to that of random chemical reaction networks.
This project is suitable for students who are finishing their 3rd or 4th year of an undergraduate physics degree. Programming will be in MATLAB or Python. Background knowledge in statistical physics and/or chemistry would be useful but is not required.
Project Supervisor: Dr. Eric De Guili