Lyapunov Functions Certify Stability via Scalar Monotonic Decrease — E8 Intelligence Research

FINDING: Lyapunov functions provide a rigorous, scalar-valued certificate for stability of dynamical systems, reducing high-dimensional convergence to monotonic decrease along trajectories. | MATH: For system \\( \\dot{x} = f(x) \\) with equilibrium \\( x^* \\), a Lyapunov function \\( V: \\mathbb{R}^n \\to \\mathbb{R} \\) satisfies: (i) \\( V(x^*) = 0 \\), \\( V(x) > 0 \\) for \\( x \\neq x^* \\); (ii) \\( \\dot{V}(x) = \\nabla V(x) \\cdot f(x) \\leq 0 \\) (semidefinite) for stability, \\( < 0 \\) for asymptotic stability. Global stability requires \\( V(x) \\to \\infty \\) as \\( \\|x\\| \\to \\infty \\) (radial unboundedness). For discrete maps \\( x_{k+1} = T(x_k) \\), the discrete analogue is \\( V(x_{k+1}) - V(x_k) \\leq 0 \\). In the distributionally robust case (arXiv:2212.01554), one searches for \\( V \\) satisfying \\( \\mathbb{E}_\\xi[V(T(x,\\xi))] - V(x) \\leq -\\gamma \\|x\\|^2 \\) for all distributions within a Wasserstein ball of radius \\( \\varepsilon \\) around the empirical distribution — a min-max SDP. | CONNECTION: T Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-19
DOI
https://doi.org/10.5281/zenodo.22841530
Primary Topic
Statistical Mechanics and Entropy
Type
preprint
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preprint

Lyapunov Functions Certify Stability via Scalar Monotonic Decrease — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Statistical Mechanics and Entropy
preprint

Lyapunov Functions Certify Stability via Scalar Monotonic Decrease — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

FINDING: Lyapunov functions provide a rigorous, scalar-valued certificate for stability of dynamical systems, reducing high-dimensional convergence to monotonic decrease along trajectories. | MATH: For system \( \dot{x} = f(x) \) with equilibrium \( x^* \), a Lyapunov function \( V: \mathbb{R}^n \to \mathbb{R} \) satisfies: (i) \( V(x^*) = 0 \), \( V(x) > 0 \) for \( x \neq x^* \); (ii) \( \dot{V}(x) = \nabla V(x) \cdot f(x) \leq 0 \) (semidefinite) for stability, \( < 0 \) for asymptotic stability. Global stability requires \( V(x) \to \infty \) as \( \|x\| \to \infty \) (radial unboundedness). For discrete maps \( x_{k+1} = T(x_k) \), the discrete analogue is \( V(x_{k+1}) - V(x_k) \leq 0 \). In the distributionally robust case (arXiv:2212.01554), one searches for \( V \) satisfying \( \mathbb{E}_\xi[V(T(x,\xi))] - V(x) \leq -\gamma \|x\|^2 \) for all distributions within a Wasserstein ball of radius \( \varepsilon \) around the empirical distribution — a min-max SDP. | CONNECTION: T Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Statistical Mechanics and Entropy
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