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- W3117379057 abstract "Active systems, which are driven by non-conservative forces acting independently on individual particles, exhibit a variety of unique behaviors and structures, with potential applications in the design of novel materials. Towards designing such materials, an important open challenge is to precisely connect the structure of active systems to the dissipation of energy induced by the local driving. We approach this problem by developing a perturbative mean-field theory which predicts the static structure with good accuracy, even for strongly interacting systems. Significantly, this theory requires only equilibrium measurements of the structure to deduce, systematically, how driving forces shape the structure out-of-equilibrium. Second, based on this theory, we derive an expression for the rate of dissipation and we show that there exists a robust relation between dissipation and structure, which holds even as the system approaches an activity-induced phase transition far from equilibrium. Finally, we construct a neural network which maps static configurations of active particles to their dissipation rate, thus showing that the dissipation of energy can be inferred from purely static structural information, without any prior knowledge of the underlying dynamics." @default.
- W3117379057 created "2021-01-05" @default.
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- W3117379057 date "2020-12-18" @default.
- W3117379057 modified "2023-09-27" @default.
- W3117379057 title "Inferring dissipation from static structure in active matter." @default.
- W3117379057 hasPublicationYear "2020" @default.
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