Recursive entropy in thermodynamics: expounding the statistical-physics basis of the zentropy approach
Luke Allen Myers, Nigel Lee En Hew, Shun-Li Shang, Zi-Kui Liu

TL;DR
This paper establishes the statistical-physics foundation of the zentropy approach in thermodynamics, demonstrating its utility for multiscale analysis and coarse-graining of complex systems.
Contribution
It provides a rigorous derivation of thermodynamic quantities from recursive entropy principles, clarifying the physical meaning of temperature-dependent states and enabling multiscale modeling.
Findings
Helmholtz energy and partition function derived via recursive entropy maximization.
Framework successfully applied to magnetic materials and liquids.
Enables meaningful coarse-graining and captures emergent behavior.
Abstract
The recursive property of entropy is well known in information theory; however, the concept is underutilized in thermodynamics, despite being the field where the concept of entropy originated. The zentropy approach is built on this idea, and it has emerged as a useful framework for describing thermodynamic systems across multiple scales, yet its statistical-physics foundation has not been fully articulated. In this work, we establish that foundation by showing that the recursive property allows us to coarse-grain thermodynamic systems into the most useful groups, and deriving the Helmholtz energy and partition function by maximizing entropy in its recursive form. This derivation clarifies the thermodynamic meaning of so-called "states that depend on temperature" as coarse-grained configurations, and maintains a clear distinction between the physical and statistical aspects of…
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Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Statistical Mechanics and Entropy · Quantum many-body systems
