Thermodynamic efficiency of self-organization in nonequilibrium steady states maximizes at phase transitions and diverges from inferential efficiency in proportion to distance from equilibrium.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
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.
citing papers explorer
-
Thermodynamic efficiency of self-organisation in nonequilibrium steady states
Thermodynamic efficiency of self-organization in nonequilibrium steady states maximizes at phase transitions and diverges from inferential efficiency in proportion to distance from equilibrium.
-
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.