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The role of information flow in active matter

Applicant Dr. Sarah Loos
Subject Area Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
Term from 2022 to 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 498288081
 
Final Report Year 2024

Final Report Abstract

The world around us, including all living and many synthetic systems, is characterized by constant exchanges of energy. For example, our vital functions are only maintainable by the permanent conversion of energy from a ‘fuel’ source (food/ATP) into a directed motion. Similarly, a computer must be powered by an electrical energy source to compute. Such ongoing energy conversion is also needed to locally defeat the increase of entropy, which would ultimately destroy all order, complexity, and structure, resulting in a homogeneous distribution of matter and energy – as dictated by the second law of thermodynamics. Therefore, biological and artificial complex systems typically operate far from equilibrium. Not being restricted by the narrow confines of equilibrium, in turn, enables richer dynamics. Particularly stunning examples are the self-organized patterns of swarms of fish or birds. From a statistical physics perspective, the individual fish in a swarm can be thought of as a particle in a fluid. Unlike an ordinary particle, however, it can self-propel and is therefore called an active particle. Another crucial difference, which has only recently received attention in the research field, is that their interactions do not have to obey the action-reaction principle, i.e. can be nonreciprocal. Understanding the fundamental laws that govern nonequilibrium systems and how their dynamics is driven by energy and entropy flows is a major goal of modern statistical physics. A promising new approach is to apply concepts from stochastic thermodynamics such as the fluctuating entropy production, which directly quantifies time-reversal symmetry breaking of stochastic trajectories. In my Walter Benjamin project, I used models on different scales to work out the stochastic thermodynamic properties of active systems and their relationship to the formation of structures. A key idea was to incorporate tools from information theory that are already established in the thermodynamic description of computers and systems subject to external control. Indeed, like the latter, active systems sense and react, allowing them more complex stimulus-response relationships than equilibrium systems. An important result we obtained so far concerns systems with nonreciprocal interactions caused by limited vision cones: Nonreciprocity can lead to long-range order and directional information spreading, so that local defects travel unidirectionally, generating entropy. We also found that the emergence of dynamical phases in nonreciprocal binary fluids is associated with a surge in informatic entropy production. Such transitions a heralded by a collective self-propelled motion of the formed patterns. For a single active swimmer under external control, information flows associated with measurements can be utilized more efficiently than in passive systems. All these findings contribute to deciphering the relationships between entropy, energy, and information flows in nonequilibrium systems.

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