Unraveling the non-equilibrium dynamics of soft living matter

Soft living systems such as cytoskeletal networks, membranes, and chromosomes are driven out of thermodynamic equilibrium by internal enzymatic activity. Measuring and characterizing the non-equilibrium properties in such systems is a major challenge, owing to the large number of interacting degrees of freedom. By observing the dynamics of such systems, we obtain stochastic trajectories. What can these noisy trajectories teach us about the underlying non-equilibrium physics of the system? Using several experimental examples, I will discuss how to extract information from steady-state fluctuations in active biological assemblies employing non-equilibrium measures such as phase space currents and entropy production rates. Based on a simple model, I will argue that the scaling behavior of such non-equilibrium measures can reveal physical properties of the internal driving. Finally, I will discuss a new tracking-free approach for the unsupervised analysis time-lapse microscopy data. To this end we developed Dissipative Component Analysis - a dimensional reduction scheme selecting a basis of modes based on dissipation. Subsequently, we learn the non-equilibrium dynamics in this reduced mode space, thereby estimating the entropy production rate and time-resolved force maps. we illustrate the applicability of our approach with an example inspired by active biopolymer gels.