Self-replicating patterns and information dynamics

Non-linear dynamics in chemical systems can exhibit a variety of complex phenomena, ranging from chaotic oscillations to spatio- temporal patterns like spiral waves. In the 1990’s a special phenomenon was observed, both experimentally and in computer simulations, showing self-replication of spatial patterns or “spots”. In this talk I will discuss two aspects of this area. The first part deals with the question on how to characterise spatial patterns in complex chemical dynamics. A framework based on information theory is presented. Due to the connection between information theory and statistical mechanics, we can connect information-theoretic characteristics of the patterns to thermodynamic constraints for the chemical dynamics, primarily the need of free energy to balance the information loss from entropy production. The second part deals with the question on which conditions can we observe self-replicating patterns. In particular we have been investigating a model that supports the phenomenon in a chemical reactor architecture that has been developed on a microfluids platform. This work is part of the European project PACE (Programmable Artifical Cell Evolution), in which one general goal is to investigate the possibility to create life-like properties in artificial chemical systems, with self- replication as one such example.