Multidimensional Tauberian theorems for vector-valued distributions

TL;DR

This paper establishes new multidimensional Tauberian theorems for vector-valued distributions using regularizing transforms, with applications to asymptotic analysis, Laplace transform Tauberian theorems, and distribution traces.

Contribution

It introduces novel multidimensional Tauberian theorems for vector-valued distributions and applies them to various problems in asymptotic analysis and distribution theory.

Findings

Proved several new Tauberian theorems for vector-valued distributions.

Applied results to asymptotic stability in Cauchy problems.

Provided a new proof of Littlewood's Tauberian theorem.

Abstract

We prove several Tauberian theorems for regularizing transforms of vector-valued distributions. The regularizing transform of $f$ is given by the integral transform $M^{f}_{\varphi}(x,y)=(f\ast\varphi_{y})(x),$ $(x,y)\in\mathbb{R}^{n}\times\mathbb{R}_{+}$, with kernel $\varphi_{y}(t)=y^{-n}\varphi(t/y)$. We apply our results to the analysis of asymptotic stability for a class of Cauchy problems, Tauberian theorems for the Laplace transform, the comparison of quasiasymptotics in distribution spaces, and we give a necessary and sufficient condition for the existence of the trace of a distribution on $\left\{x_0\right\}\times \mathbb R^m$. In addition, we present a new proof of Littlewood's Tauberian theorem.