Maximum Configuration Principle for Driven Systems with Arbitrary Driving

15623 8 85918 2 243642 document 85918 entropy-20-00838.pdf application/pdf 72f26809e24608abcdbe6134e608df2f MD5 511122 2018-12-04 14:25:44 https://pure.iiasa.ac.at/id/eprint/15623/1/entropy-20-00838.pdf 15623 1 1 application/pdf text en public cc_by_4

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published 85919 1 243649 document 85919 indexcodes.txt text/x-c++ 542448951dad7563303658b231a993b4 MD5 8340 2018-12-04 14:35:34 https://pure.iiasa.ac.at/id/eprint/15623/2/indexcodes.txt 15623 2 2 text/x-c++ other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/85918 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/85918 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/85918 archive 353 disk0/00/01/56/23 2018-12-04 14:27:00 2021-08-27 17:31:09 2018-12-04 14:27:00 article show Hanel R. Thurner S. 1918 Maximum Configuration Principle for Driven Systems with Arbitrary Driving pub prog_asa non-equilibrium; maximum configuration; maximum entropy principle; driven systems; statistical mechanics Depending on context, the term entropy is used for a thermodynamic quantity, a measure of available choice, a quantity to measure information, or, in the context of statistical inference, a maximum configuration predictor. For systems in equilibrium or processes without memory, the mathematical expression for these different concepts of entropy appears to be the so-called Boltzmann–Gibbs–Shannon entropy, H. For processes with memory, such as driven- or self- reinforcing-processes, this is no longer true: the different entropy concepts lead to distinct functionals that generally differ from H. Here we focus on the maximum configuration entropy (that predicts empirical distribution functions) in the context of driven dissipative systems. We develop the corresponding framework and derive the entropy functional that describes the distribution of observable states as a function of the details of the driving process. We do this for sample space reducing (SSR) processes, which provide an analytically tractable model for driven dissipative systems with controllable driving. The fact that a consistent framework for a maximum configuration entropy exists for arbitrarily driven non-equilibrium systems opens the possibility of deriving a full statistical theory of driven dissipative systems of this kind. This provides us with the technical means needed to derive a thermodynamic theory of driven processes based on a statistical theory. We discuss the Legendre structure for driven systems. 2018-11-01 published Molecular Diversity Preservation International (MDPI) 10.3390/e20110838 307 public Entropy 20 11 838 TRUE 1099-4300 FALSE no info:eu-repo/semantics/article