Learning the Non-Equilibrium Dynamics of Brownian Movies

Abstract

Time-lapse microscopy imaging provides direct access to the dynamics of soft and living systems. At mesoscopic scales, such microscopy experiments reveal intrinsic fluctuations, which may have both thermal and non-equilibrium origins. These intrinsic fluctuations, together with measurement noise, pose a major challenge for the analysis of the dynamics of these "Brownian movies". Traditionally, methods to analyze such experimental data rely on tracking embedded or endogenous probes. However, it is in general unclear how to select appropriate tracers; it is not evident, especially in complex many-body systems, which degrees of freedom are the most informative about their non-equilibrium nature. Here, we introduce an alternative, tracking-free approach that overcomes these difficulties via an unsupervised analysis of the Brownian movie. We develop a dimensional reduction scheme that selects a basis of modes based on dissipation, and we subsequently learn the non-equilibrium dynamics in this basis and estimate the entropy production rate. In addition, we infer time-resolved force maps in the system and show that this approach is scalable to large systems, thus providing a potential alternative to microscopic force-probes. After benchmarking our method against a minimal two-beads model, we illustrate its broader applicability with an example inspired by active biopolymer gels.

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• Improved bounds on entropy production in living systems
• Estimating entropy production from waiting time distributions
• Estimating time-dependent entropy production from non-equilibrium trajectories
• Quantitative analysis of non-equilibrium systems from short-time experimental data
• Inference of Markov models from trajectories via Large Deviations at Level 2.5 with applications to random walks in disordered media
• Information-driven transitions in projections of underdamped dynamics
• Neural force functional for non-equilibrium many-body colloidal systems
• Irreversibility in linear systems with colored noise
• From predicting to learning dissipation from pair correlations of active liquids
• Estimate of entropy generation rate can spatiotemporally resolve the active nature of cell flickering
• Information Thermodynamics of the Transition-Path Ensemble
• Stochastic line integrals and stream functions as metrics of irreversibility and heat transfer
• Nonequilibrium Probability Currents in Optically-Driven Colloidal Suspensions
• Attaining entropy production and dissipation maps from Brownian movies via neural networks
• 3D tracking of particles in a dusty plasma by laser sheet tomography
• Quantifying spatio-temporal patterns in classical and quantum systems out of equilibrium
• Inferring nonequilibrium thermodynamics from tilted equilibrium using information-geometric Legendre transform
• From reductionism to realism: Holistic mathematical modelling for complex biological systems
• Force-free kinetic inference of entropy production
• Functional Decomposition and Estimation of Irreversibility in Time Series via Machine Learning