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Multiscale Entropy and Its Implications to Critical Phenomena, Emergent Behaviors, and Information

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Abstract

Thermodynamics of critical phenomena in a system is well understood in terms of the divergence of molar quantities with respect to potentials. However, the prediction and the microscopic mechanisms of critical points and the associated property anomaly remain elusive. It is shown that while the critical point is typically considered to represent the limit of stability of a system when the system is approached from a homogenous state to the critical point, it can also be considered to represent the convergence of several homogeneous subsystems to become a macro-homogeneous system when the critical point is approached from a macro-heterogeneous system. Through the understanding of statistic characteristics of entropy in different scales, it is demonstrated that the statistic competition of key representative configurations results in the divergence of molar quantities when metastable configurations have higher entropy than the stable configuration. Furthermore, the connection between change of configurations and the change of information is discussed, which provides a quantitative framework to study complex, dissipative systems.

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Acknowledgments

ZKL is grateful for financial supports from many funding agencies in the United States as listed in the cited references, including the National Science Foundation (NSF with the latest Grant 1825538), the Department of Energy (with the latest Grants being DE-FE0031553 and DE-NE0008757), Army Research Lab, Office of Naval Research (with the latest Grant N00014-17-1-2567), Wright Patterson AirForce Base, NASA Jet Propulsion Laboratory, and the National Institute of Standards and Technology, plus a range of national laboratories and companies that supported the NSF Center for Computational Materials Design, the LION clusters at the Pennsylvania State University, the resources of NERSC supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, and the resources of XSEDE supported by NSF with Grant ACI-1053575. BL would like to acknowledge the partial financial support from the NSF Grant Number DMS-1713078. The authors thank Prof. Yi Wang at Penn State for stimulating discussions.

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Liu, ZK., Li, B. & Lin, H. Multiscale Entropy and Its Implications to Critical Phenomena, Emergent Behaviors, and Information. J. Phase Equilib. Diffus. 40, 508–521 (2019). https://doi.org/10.1007/s11669-019-00736-w

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