Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 16 tok/s Pro
GPT-5 High 18 tok/s Pro
GPT-4o 105 tok/s Pro
GPT OSS 120B 471 tok/s Pro
Kimi K2 193 tok/s Pro
2000 character limit reached

Completeness of Sets of Shifts in Invariant Banach Spaces of Tempered Distributions via Tauberian conditions (2012.11127v2)

Published 21 Dec 2020 in math.FA

Abstract: The main result of this paper is a far reaching generalization of the completeness result given by V.~Katsnelson in a paper [35]. Instead of just using a collection of dilated Gaussians it is shown that the key steps of an earlier paper [27] by the authors, combined with the use of Tauberian conditions (i.e. the non-vanishing of the Fourier transform) allow us to show that the linear span of the translates of a single function $g \in {{{\boldsymbol{\mathcal {S}}}({\mathbb{R}}d)}}$ is a dense subspace of any Banach space satisfying certain double invariance properties. In fact, a much stronger statement is presented: for a given compact subset $M$ in such a Banach space $({\boldsymbol B}, \, |\,\cdot\,|_{\boldsymbol B})$ one can construct a finite rank operator, whose range is contained in the linear span of finitely many translates of $g$, and which approximates the identity operator over $M$ up to a given level of precision. The setting of tempered distributions allows to reduce the technical arguments to methods which are widely used in Fourier Analysis. The extension to non-quasi-analytic weights respectively locally compact Abelian groups is left to a forthcoming paper, which will be technically much more involved and uses different ingredients.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.