Energy and information processing in spatially extended open chemical reactions networks undergoing spatio-temporal symmetry breaking
The goal of this project is to develop a firm framework of microscopic phase transitions and early warning signals. From a physical perspective, the notion of CT refers to a qualitative change in the behaviour of a collective variable (i.e., a macro-variable) resulting from the joint action of a large number of individual variables (micro-variables). This concept has its roots in the theory of phase transition in equilibrium thermodynamics. However, many CTs belong to the much broader class of non-equilibrium phase transitions. These seem to play a particularly important role in biology, where they might control phenotypic variation and other key regime changes at the cellular level (Ge 2011). The fact that processes occurring at the cellular level are never, strictly speaking, macroscopic, but rather are mesoscopic, is probably important in enabling the switching between different states of the collective variable and in maintaining the versatility typical of biological systems. Characterising these switching mechanisms is thus crucial. No unified theory of non-equilibrium phase transition exists and the energetics and information aspects of CTs are poorly understood. The subproject aims to address this challenge using stochastic thermodynamics (van den Broeck 2015; Seifert 2012) and, in particular, to understand CT in open chemical networks, which plays a crucial role in biology (e.g., metabolism and signal transduction). We will use our background in the physical and mathematical theories required to characterize CTs to produce novel perspectives on critical transitions in chemistry and biology based on energy and information processing. This project will interact with the theoretical groups and experimental subprojects to characterise specific types of CTs in the realm of biology. The target disciplines of the PhD candidates to be recruited are statistical physics, stochastic processes, biochemistry and dynamical systems.