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We approximate the spectral data (eigenvalues and eigenfunctions) of compact Riemannian manifold by the spectral data of a sequence of (computable) discrete Laplace operators associated to some graphs immersed in the manifold. We give an…

Analysis of PDEs · Mathematics 2013-01-17 Erwann Aubry

We introduce $(k,l)$-regular maps, which generalize two previously studied classes of maps: affinely $k$-regular maps and totally skew embeddings. We exhibit some explicit examples and obtain bounds on the least dimension of a Euclidean…

Differential Geometry · Mathematics 2007-05-23 Gordana Stojanovic

Consider the space $W^{2,2}(\Omega;N)$ of second order Sobolev mappings $\ v\ $ from a smooth domain $\Omega\subset\R^m$ to a compact Riemannian manifold $N$ whose Hessian energy $\int_\Omega |\nabla^2 v|^2\, dx$ is finite. Here we are…

Functional Analysis · Mathematics 2013-06-03 Robert Hardt , Tristan Rivière

We show that in all homotopy classes of mappings from complex projective space to Riemannian manifolds, the infimum of the energy is proportional to the infimal area in the homotopy class of mappings of the 2-sphere which represents the…

Differential Geometry · Mathematics 2024-11-14 Joseph Hoisington

Pointwise error analysis of the linear finite element approximation for $-\Delta u + u = f$ in $\Omega$, $\partial_n u = \tau$ on $\partial\Omega$, where $\Omega$ is a bounded smooth domain in $\mathbb R^N$, is presented. We establish…

Numerical Analysis · Mathematics 2018-04-03 Takahito Kashiwabara , Tomoya Kemmochi

We investigate local minimizers of Ginzburg--Landau-type functionals in dimension $n\geq 3$ that satisfy logarithmic energy bounds, assuming the potential has a vacuum manifold with a finite fundamental group. We show that the normalized…

Analysis of PDEs · Mathematics 2026-05-07 Giacomo Canevari , Haotong Fu , Wei Wang

Consider the sum of the first $N$ eigenspaces for the Laplacian on a Riemannian manifold. A basis for this space determines a map to Euclidean space and for $N$ sufficiently large the map is an embedding. In analogy with a fruitful idea of…

Differential Geometry · Mathematics 2014-04-30 Eric Potash

Given two Riemannian manifolds $M$ and $N\subset\mathbb{R}^L$, we consider the energy concentration phenomena of the penalized energy functional $$E_{\epsilon}(u)=\int_M\frac{\vert\nabla u\vert^2}{2}+\frac{F(u)}{\epsilon^2},u\in…

Analysis of PDEs · Mathematics 2025-04-01 Xuanyu Li

Given a Hilbert space $\mathcal H$ and a finite measure space $\Omega$, the approximation of a vector-valued function $f: \Omega \to \mathcal H$ by a $k$-dimensional subspace $\mathcal U \subset \mathcal H$ plays an important role in…

Numerical Analysis · Mathematics 2024-08-07 Daniel Kressner , Tingting Ni , André Uschmajew

Let X and Y be planar Jordan domains of the same finite connectivity, Y being inner chordarc regular (such are Lipschitz domains). Every homeomorphism h:X->Y in the Sobolev space $W^{1,2}$ extends to a continuous map between closed domains.…

Complex Variables · Mathematics 2013-02-12 Tadeusz Iwaniec , Leonid V. Kovalev , Jani Onninen

In this paper, we propose and analyze a finite element discretization for the computation of fractional minimal graphs of order~$s \in (0,1/2)$ on a bounded domain $\Omega$. Such a Plateau problem of order $s$ can be reinterpreted as a…

Numerical Analysis · Mathematics 2020-03-26 Juan Pablo Borthagaray , Wenbo Li , Ricardo H. Nochetto

(1) For a compact Riemannian manifold without boundary $(M,g)$ containing $n+1$ points $p_i$ and the $n$-dimensional standard simplex $\Delta$, the miniser of \[ E: M \times \Delta \to {\mathbf R}, (a,\lambda) \mapsto \lambda^0 d^2(a,p_0) +…

Numerical Analysis · Mathematics 2015-05-15 Stefan von Deylen

We discuss approximations of the Riemannian geometry near the horizon. If a D+1 dimensional manifold N has a bifurcate Killing horizon then we approximate N by a product of the two-dimensional Rindler space and a D-1 dimensional Riemannian…

High Energy Physics - Theory · Physics 2009-03-27 Z. Haba

We derive a priori error estimates for Nitsche's method applied to elliptic problems on approximate domains. Such approximations arise, for example, in unfitted finite element methods, data-driven simulations, and evolving domain problems,…

Numerical Analysis · Mathematics 2026-04-02 Mats G. Larson , Karl Larsson , Shantiram Mahata

We derive a family of high-order, structure-preserving approximations of the Riemannian exponential map on several matrix manifolds, including the group of unitary matrices, the Grassmannian manifold, and the Stiefel manifold. Our…

Numerical Analysis · Mathematics 2017-05-17 Evan S. Gawlik , Melvin Leok

In the context of unfitted finite element discretizations the realization of high order methods is challenging due to the fact that the geometry approximation has to be sufficiently accurate. Recently a new unfitted finite element method…

Numerical Analysis · Mathematics 2017-09-01 Christoph Lehrenfeld , Arnold Reusken

A $W^{1,p}$-metric on an $n$-dimensional closed Riemannian manifold naturally induces a distance function, provided $p$ is sufficiently close to $n$. If a sequence of metrics $g_k$ converges in $W^{1,p}$ to a limit metric $g$, then the…

Differential Geometry · Mathematics 2021-04-27 Conghan Dong , Yuxiang Li , Ke Xu

In this paper, we prove a finite dimensional approximation scheme for the Wiener measure on closed Riemannian manifolds, establishing a generalization for $L^{1}$-functionals, of the approach followed by Andersson and Driver on [1]. We…

Differential Geometry · Mathematics 2022-01-28 Juan Carlos Sampedro

Given a positive integer $p$, we consider $W^{1,p}$-maps from a Euclidean domain of dimension $p+1$ into a closed Riemannian manifold $\mathcal{N}$. The target manifold is required to satisfy suitable topological conditions; in particular,…

Functional Analysis · Mathematics 2026-05-28 Giacomo Canevari , Giandomenico Orlandi

Under a set of assumptions on a family of submanifolds $\subset {\mathbb R}^D$, we derive a series of geometric properties that remain valid after finite-dimensional and almost isometric Diffusion Maps (DM), including almost uniform…

Machine Learning · Statistics 2026-05-15 Wenyu Bo , Marina Meilă