On functional equations characterizing derivations: methods and examples

TL;DR

This paper explores functional equations related to additive functions and derivations, providing multivariate characterizations, solution methods, and examples, with applications to higher order derivations and algebraic structures.

Contribution

It introduces multivariate characterizations of higher order derivations and refines solution methods for related functional equations using spectral analysis.

Findings

Multivariate formulas characterize higher order derivations.

Diagonalization yields univariate characterizations.

Spectral analysis proves equations characterize derivations.

Abstract

Functional equations satisfied by additive functions have a special interest not only in the theory of functional equations, but also in the theory of (commutative) algebra because the fundamental notions such as derivations and automorphisms are additive functions satisfying some further functional equations as well. It is an important question that how these morphisms can be characterized among additive mappings in general. The paper contains some multivariate characterizations of higher order derivations. The univariate characterizations are given as consequences by the diagonalization of the multivariate formulas. The method allows us to refine the process of computing the solutions of univariate functional equations of the form \[ \sum_{k=1}^{n}x^{p_{k}}f_{k}(x^{q_{k}})=0, \] where $p_k$ and $q_k$ ($k=1, \ldots, n$) are given nonnegative integers and the unknown functions $f_{1}, \ldots, f_{n}\colon R\to R$ are supposed to be additive on the ring $R$. It is illustrated by some explicit examples too. As another application of the multivariate setting we use spectral analysis and spectral synthesis in the space of the additive solutions to prove that such a functional equation characterizes derivations of higher order. The results are uniformly based on the investigation of the multivariate version of the functional equations.