The d'Alembert Inevitability Theorem

TL;DR

This paper characterizes solutions to a specific functional equation involving symmetric polynomial combiners, revealing conditions under which solutions are of d'Alembert type and excluding nontrivial separable costs.

Contribution

It proves that symmetric polynomial combiners of degree at most two lead to classical d'Alembert solutions and excludes higher-degree combiners for continuous solutions.

Findings

Solutions with degree ≥ 3 do not admit nonconstant continuous solutions.

For degree ≤ 2, solutions are of d'Alembert type, including hyperbolic, trigonometric, and squared-logarithm families.

Only hyperbolic solutions with specific parameters are compatible with convexity and non-negativity constraints.

Abstract

We study functions satisfying the composition law $F(xy)+F(x/y)=P(F(x),F(y))$ with a symmetric polynomial combiner $P$. We prove that symmetry together with a quadratic degree bound on $P$ forces a composition law of d'Alembert type. We establish a degree mismatch exclusion criterion showing that symmetric polynomial combiners with $\mbox{deg} P(u,v) \ge 3$ do not admit nonconstant continuous solutions, provided the leading term does not cancel (Theorem 3.1.). For continuous nonconstant functions $F:\mathbb{R}_{>0}\to\mathbb{R}$ with $F(1)=0$ satisfying the composition law with a symmetric polynomial $P$ of degree at most two, the combiner is necessarily of the form $P(u,v)=2u+2v+c\,uv$, $c\in\mathbb{R}$ (Theorem 3.3.). The equation reduces in logarithmic coordinates to the classical d'Alembert functional equation. For $c\neq 0$, one obtains hyperbolic or trigonometric branches, while $c=0$ yields the squared-logarithm family. Under the cost-function assumptions $F\ge 0$ and convexity, only the hyperbolic branch with $c>0$ remains. A unit log-curvature calibration selects the canonical value $c=2$, which yields the canonical reciprocal cost $F(x)=\tfrac12(x+x^{-1})-1$. For $c\neq0$, the result extends to $\mathbb{R}_{>0}^n$: every solution depends only on a single linear combination of coordinate logarithms; for $c=0$, the solution is a general quadratic form $\sum_{i,j}a_{ij}\ln x_i\ln x_j$. In either case, nontrivial coordinate-wise separable costs are excluded.