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Rademacher theorem states that every Lipschitz function on the Euclidean space is differentiable almost everywhere, where "almost everywhere" refers to the Lebesgue measure. In this paper we prove a differentiability result of similar type,…

Classical Analysis and ODEs · Mathematics 2015-03-27 Giovanni Alberti , Andrea Marchese

We derive an uncertainty principle for Lipschitz maps acting on subsets of Banach spaces. We show that this nonlinear uncertainty principle reduces to the Heisenberg-Robertson-Schrodinger uncertainty principle for linear operators acting on…

Functional Analysis · Mathematics 2026-03-26 K. Mahesh Krishna

We investigate the properties of a class of piecewise-fractional maps arising from the introduction of an invariance under rescaling into convex quadratic maps. The subsequent maps are quasiconvex, and pseudoconvex on specific convex cones;…

Optimization and Control · Mathematics 2025-04-25 Alexandra Zverovich , Matthew Hutchings , Bertrand Gauthier

This note is to concern a generalization to the case of twisted coefficients of the classical theory of Abelian differentials on a compact Riemann surface. We apply the Dirichlet's principle to a modified energy functional to show the…

Differential Geometry · Mathematics 2007-05-23 Yi-Hu Yang

We prove two rigidity theorems for maps between Riemannian manifolds. First, we prove that a Lipschitz map $f:M\to N$ between two oriented Riemannian manifolds, whose differential is almost everywhere an orientation-preserving isometry, is…

Differential Geometry · Mathematics 2019-01-23 Raz Kupferman , Cy Maor , Asaf Shachar

Z. Nehari developed a general technique for obtaining inequalities for conformal maps and domain functions from contour integrals and the Dirichlet principle. Given a harmonic function with singularity on a domain $R$, it associates a…

Complex Variables · Mathematics 2016-08-03 Eric Schippers

We are to establish necessary conditions (of the primal and dual types) for the set of weak sharp minima of a nonconvex optimization problem on a Riemannian manifold. Here, we are to provide a generalization of some characterizations of…

Optimization and Control · Mathematics 2019-03-21 M. Mahdi Karkhaneei , Nezam Mahdavi-Amiri

The main goal of this article is to study a Calder\'on type inverse problem for certain viscous nonlocal wave equations. We show that the partial Dirichlet to Neumann map uniquely determines on the one hand linear perturbations and on the…

Analysis of PDEs · Mathematics 2026-01-06 Philipp Zimmermann

In this note we prove that any $W^{1,2}$ mapping $u$ in the plane that minimizes an appropriate quasiconvex energy functional subject to the Jacobian constraint ${\rm det} \na u=1$ a.e., are necessarily Lipschitz. Furthermore we show that…

Analysis of PDEs · Mathematics 2007-05-23 Nirmalendu Chaudhuri

In this paper we study the Dirichlet problem for fully nonlinear second-order equations on a riemannian manifold. As in a previous paper we define equations via closed subsets of the 2-jet bundle. Basic existence and uniqueness theorems are…

Analysis of PDEs · Mathematics 2017-12-12 F. Reese Harvey , H. Blaine Lawson

We study the limiting behavior of minimizing $p$-harmonic maps from a bounded Lipschitz domain $\Omega \subset \mathbb{R}^{3}$ to a compact connected Riemannian manifold without boundary and with finite fundamental group as $p \nearrow 2$.…

Analysis of PDEs · Mathematics 2025-05-07 Bohdan Bulanyi , Jean Van Schaftingen , Benoît Van Vaerenbergh

We analyze a variational time discretization of geodesic calculus on finite- and certain classes of infinite-dimensional Riemannian manifolds. We investigate the fundamental properties of discrete geodesics, the associated discrete…

Numerical Analysis · Mathematics 2013-03-25 Martin Rumpf , Benedikt Wirth

The maximum principle forms an important qualitative property of second order elliptic equations, therefore its discrete analogues, the so-called discrete maximum principles (DMPs) have drawn much attention. In this paper DMPs are…

Numerical Analysis · Mathematics 2018-07-05 János Karátson , Balázs Kovács , Sergey Korotov

We study the Dirichlet problem for least gradient functions for domains in metric spaces equipped with a doubling measure and supporting a (1,1)-Poincar\'e inequality when the boundary of the domain satisfies a positive mean curvature…

Analysis of PDEs · Mathematics 2022-10-18 Josh Kline

The classical Rellich inequalities imply that the $L^2$-norms of the normal and tangential derivatives of a harmonic function are equivalent. In this note, we prove several refined inequalities, which make sense even if the domain is not…

Analysis of PDEs · Mathematics 2022-09-20 Siddhant Agrawal , Thomas Alazard

Continuous conformal transformation minimizes the conformal energy. The convergence of minimizing discrete conformal energy when the discrete mesh size tends to zero is an open problem. This paper addresses this problem via a careful error…

Numerical Analysis · Mathematics 2022-10-21 Zhenyue Zhang , Zhong-Heng Tan

Given an o-minimal structure, we show that every definable (in this structure) mapping that is Lipschitz with respect to the inner metric can be approximated by $\mathscr{C}^1$ mappings that are Lipschitz with respect to the inner metric…

Algebraic Geometry · Mathematics 2026-03-09 Nhan Nguyen , Anna Valette , Guillaume Valette

Recent quasi-optimal error estimates for the finite element approximation of total-variation regularized minimization problems require the existence of a Lipschitz continuous dual solution. We discuss the validity of this condition and…

Numerical Analysis · Mathematics 2021-06-28 Sören Bartels , Robert Tovey , Friedrich Wassmer

We study dentable maps from a closed convex subset of a Banach space into a metric space as an attempt of generalize the Radon-Nikod\'ym property to a "less linear" frame. We note that a certain part of the theory can be developed in rather…

Functional Analysis · Mathematics 2017-06-01 Luis García-Lirola , Matías Raja

This paper studies the problem of distributed Riemannian optimization over a network of agents whose cost functions are geodesically smooth but possibly geodesically non-convex. Extending a well-known distributed optimization strategy…

Signal Processing · Electrical Eng. & Systems 2026-05-26 Xiuheng Wang , Ricardo Borsoi , Cédric Richard , Ali H. Sayed