Data-driven framework using short-time TUR inference and deep neural networks reconstructs high-dimensional dissipative force fields and localizes fluctuating entropy production in space and time.
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Localizing entropy production along non-equilibrium trajectories
Data-driven framework using short-time TUR inference and deep neural networks reconstructs high-dimensional dissipative force fields and localizes fluctuating entropy production in space and time.
- Information bottleneck for learning the phase space of dynamics from high-dimensional experimental data