On the Mathematics of Information-Thermodynamics

TL;DR

This paper validates the asdf information-theoretic method for calculating thermodynamic entropy from molecular configurations, showing it reproduces classical results for idealized systems and discussing its extension to interacting systems.

Contribution

It analytically demonstrates the consistency of the asdf framework with classical statistical mechanics for solvable systems and explores its potential for complex condensed phases.

Findings

The residual mapping's Shannon entropy matches classical entropy for ideal gas.

The residual mapping's conditional entropy coincides with ensemble entropy.

The framework generalizes to interacting Hamiltonians.

Abstract

We present a validation of the asdf method, an information-theoretic framework for computing thermodynamic entropy from molecular configurations. The method reformulates entropy estimation as the Shannon entropy of a residual mapping distribution defined between two decorrelated microstates. We demonstrate analytically that for the closed-form Hamiltonians with known solutions, the classical ideal gas and the one-dimensional harmonic oscillator's entropy obtained from the compressibility of the residual mapping object reproduces the exact thermodynamic entropy. In each case, the conditional entropy of the residual mapping object with respect to an uncorrelated microstate is shown to coincide with the ensemble entropy derived from the canonical partition function. These results establish consistency between the asdf formalism and classical statistical mechanics for analytically solvable systems. We further discuss how the framework generalizes to interacting Hamiltonians. The analysis supports the interpretation of thermodynamic entropy as an information measure encoded geometrically in inter-microstate mappings and motivates application of the method to complex condensed phases.