Coherent Comparison as Information Cost: A Cost-First Ledger Framework for Discrete Dynamics
Sebastian Pardo-Guerra, Megan Simons, Anil Thapa, Jonathan Washburn

TL;DR
This paper introduces a novel information-theoretic framework for discrete dynamics using a cost functional based on ratios, leading to a ledger model that encodes recognition events with properties ensuring consistency, cycle closure, and scalar potentials on graphs.
Contribution
It develops a unique reciprocal cost functional grounded in coherence principles and applies it to construct a minimal, lossless ledger model with cycle closure and potential theory on graphs.
Findings
Derived a unique reciprocal cost functional J(x) for ratio deviations.
Established conditions for cycle closure and path-independence in graph flows.
Constructed explicit Gray-code realization for hypercube graphs.
Abstract
We develop an information-theoretic framework for discrete dynamics grounded in a comparison-cost functional on ratios. Given two quantities compared via their ratio \(x=a/b\), we assign a cost \(F(x)\) measuring deviation from equilibrium (\(x=1\)). Requiring coherent composition under multiplicative chaining imposes a d'Alembert functional equation; together with normalization (\(F(1)=0\)) and quadratic calibration at unity, this yields a unique reciprocal cost functional (proved in a companion paper): \[ J(x) = \tfrac{1}{2}\bigl(x + x^{-1}\bigr) - 1. \] This cost exhibits reciprocity \(J(x)=J(x^{-1})\), vanishes only at \(x=1\), and diverges at boundary regimes \(x\to 0^+\) and \(x\to\infty\), excluding ``nothingness'' configurations. Using \(J\) as input, we introduce a discrete ledger as a minimal lossless encoding of recognition events on directed graphs. Under deterministic…
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Taxonomy
TopicsControl and Stability of Dynamical Systems · Advanced Graph Neural Networks · Quantum chaos and dynamical systems
