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This paper deals with a class of Sobolev spaces of vector-valued functions on a compact group. Some Sobolev embedding theorems are proved.

Functional Analysis · Mathematics 2025-01-22 Yaogan Mensah

We remark that a dyadic version of the Carleson embedding theorem for the Bergman space extends to vector-valued functions and operator-valued measures. This is in contrast to a result by Nazarov, Treil, Volberg in the context of the Hardy…

Functional Analysis · Mathematics 2014-09-15 Olivia Constantin , Laura Gavruta

A unified approach to embedding theorems for Sobolev type spaces of vector-valued functions, defined via their symmetric gradient, is proposed. The Sobolev spaces in question are built upon general rearrangement-invariant norms. Optimal…

Analysis of PDEs · Mathematics 2021-07-15 Dominic Breit , Andrea Cianchi

This paper introduces first order Sobolev spaces on certain rectifiable varifolds. These complete locally convex spaces are contained in the generally nonlinear class of generalised weakly differentiable functions and share key functional…

Classical Analysis and ODEs · Mathematics 2017-05-25 Ulrich Menne

Apart from an account of classical preliminaries, this volume contains a systematic introduction to Sobolev spaces and functions of bounded variation with selected applications. This is installment III of a four part discussion of certain…

History and Overview · Mathematics 2024-02-05 Garth Warner

We prove Sobolev embedding Theorems with weights for vector bundles in a complete riemannian manifold. We also get general Gaffney's inequality with weights. As a consequence, under a "weak bounded geometry" hypothesis, we improve classical…

Analysis of PDEs · Mathematics 2019-06-02 Eric Amar

This paper is a self-contained presentation of certain aspects of the theory of weighted Sobolev spaces and elliptic operators on non-compact Riemannian manifolds. Specifically, we discuss (i) the standard and weighted Sobolev Embedding…

Differential Geometry · Mathematics 2010-05-20 Tommaso Pacini

This article develops a unified and intrinsic framework for the theory of Sobolev spaces on vector bundles over Riemannian manifolds. The analytical core of our approach is an explicit higher-order geometric integration by parts formula,…

Analysis of PDEs · Mathematics 2026-05-19 Velázquez-Mendoza Carlos Daniel , Sandoval-Romero María de los Ángeles

An embedding theorem for Sobolev spaces built upon general Musielak-Orlicz norms is offered. These norms are defined in terms of generalized Young functions which also depend on the $x$ variable. Under minimal conditions on the latter…

Analysis of PDEs · Mathematics 2023-11-28 Andrea Cianchi , Lars Diening

We deduce an extension theorem for the so-called Sobolev-Grand Lebesgue Spaces defined on the suitable subsets of the whole finite-dimensional Euclidean space, and estimate the norms of correspondent extension operator, which may be choosed…

Functional Analysis · Mathematics 2022-06-02 M. R. Formica , E. Ostrovsky , L. Sirota

Sobolev embeddings, of arbitrary order, are considered into function spaces on domains of $\mathbb R^n$ endowed with measures whose decay on balls is dominated by a power $d$ of their radius. Norms in arbitrary rearrangement-invariant…

Functional Analysis · Mathematics 2019-12-10 Andrea Cianchi , Luboš Pick , Lenka Slavíková

A comprehensive approach to Sobolev-type embeddings, involving arbitrary rearrangement- invariant norms on the entire Euclidean space R^n, is offered. In particular, the optimal target space in any such embedding is exhibited. Crucial in…

Functional Analysis · Mathematics 2017-12-01 Angela Alberico , Andrea Cianchi , Lubos Pick , Lenka Slavikova

This is a survey of some recent applications of Boolean valued analysis to operator theory and harmonic analysis. Under consideration are pseudoembedding operators, the noncommutative Wickstead problem, the Radon-Nikodym Theorem for…

Functional Analysis · Mathematics 2015-02-18 A. G. Kusraev , S. S. Kutateladze

We study an extended Sobolev scale for smooth vector bundles over a smooth closed manifold. This scale is built on the base of inner product distribution spaces of generalized smoothness given by an arbitrary positive function OR-varying at…

Analysis of PDEs · Mathematics 2025-06-06 Aleksandr Murach , Tetiana Zinchenko

This paper is dedicated to the question of surjectivity of the Cauchy-Riemann operator on spaces $\mathcal{EV}(\Omega,E)$ of $\mathcal{C}^{\infty}$-smooth vector-valued functions whose growth on strips along the real axis with holes $K$ is…

Functional Analysis · Mathematics 2023-01-13 Karsten Kruse

In this paper we study weighted Hardy-Sobolev spaces of vector valued functions analytic on double-napped cones of the complex plane. We introduce these spaces as a tool for complex scaling of linear ordinary differential equations with…

Analysis of PDEs · Mathematics 2009-01-13 Victor Kalvin

The continouity and compactness of embedding operators in in Sobolev-Lions type spaces are derived. By applying this result separability properties of degenerate anisotropic differential operator equations, well-posedeness and Strichartz…

Functional Analysis · Mathematics 2017-05-26 Veli Shakhmurov

The purpose of this short article is to prove some potential estimates that naturally arise in the study of subelliptic Sobolev inequalites for functions. This will allow us to prove a local subelliptic Sobolev inequality with the optimal…

Classical Analysis and ODEs · Mathematics 2015-07-14 Po-Lam Yung

We give an extension of the theory of relaxation of variational integrals in classical Sobolev spaces to the setting of metric Sobolev spaces. More precisely, we establish a general framework to deal with the problem of finding an integral…

Classical Analysis and ODEs · Mathematics 2013-10-08 Omar Anza Hafsa , Jean-Philippe Mandallena

This study investigates the impact of Sobolev Training on operator learning frameworks for improving model performance. Our research reveals that integrating derivative information into the loss function enhances the training process, and…

Machine Learning · Computer Science 2024-02-15 Namkyeong Cho , Junseung Ryu , Hyung Ju Hwang
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