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We prove smoothness of $W^{2,2}$ isometric immersions of surfaces endowed with a smooth Riemannian metric of positive Gauss curvature. We then derive the $\Gamma$-limit of three dimensional nonlinear shells with inhomogeneous energy…

Analysis of PDEs · Mathematics 2017-11-08 Peter Hornung , Igor Velcic

We study spectral properties of Schr\"odinger operators with random potentials of alloy type on $L^2(\RR)$ and their restrictions to finite intervals. A Wegner estimate for non-negative single site potentials with small support is proven.…

Mathematical Physics · Physics 2007-05-23 Werner Kirsch , Ivan Veselic'

We prove a pointwise version of the multi-dimensional central limit theorem for convex bodies. Namely, let X be an isotropic random vector in R^n with a log-concave density. For a typical subspace E in R^n of dimension n^c, consider the…

Metric Geometry · Mathematics 2007-08-21 Ronen Eldan , Bo'az Klartag

We study the variance in the number of points contained within a window $\Omega$ of arbitrary size, and to further illuminate our understanding of {\it hyperuniform} systems, i.e., point patterns that do not possess long-wavelength…

Statistical Mechanics · Physics 2009-11-10 Salvatore Torquato , Frank H. Stillinger

The aim of this paper is to establish the uniform convergence of the densities of a sequence of random variables, which are functionals of an underlying Gaussian process, to a normal density. Precise estimates for the uniform distance are…

Probability · Mathematics 2013-08-30 Yaozhong Hu , Fei Lu , David Nualart

We build penalized least-squares estimators using the slope heuristic and resampling penalties. We prove oracle inequalities for the selected estimator with leading constant asymptotically equal to 1. We compare the practical performances…

Statistics Theory · Mathematics 2015-03-13 Matthieu Lerasle

Given a compact Riemannian manifold $(M^n,g)$ and a fixed cohomology class, $[\alpha^*] \in H^k(M)$, we consider the existence of a minimizer $\alpha \in [\alpha^*]$ of the generalized minimal surface energy $\int_M \sqrt{1+|\alpha|^2}…

Differential Geometry · Mathematics 2018-03-07 Daniel Agress

The method to derive uniform bounds with Gaussian and Rademacher complexities is extended to the case where the sample average is replaced by a nonlinear statistic. Tight bounds are obtained for U-statistics, smoothened L-statistics and…

Statistics Theory · Mathematics 2019-05-13 Andreas Maurer , Massimiliano Pontil

We consider first order local minimization problems of the form $\min \int_{\mathbb{R}^N}f(u,\nabla u)$ under a mass constraint $\int_{\mathbb{R}^N}u=m$. We prove that the minimal energy function $H(m)$ is always concave, and that relevant…

Analysis of PDEs · Mathematics 2024-02-23 Antonin Monteil , Paul Pegon

We consider $\mathbb{S}^2$-valued maps on a domain $\Omega\subset\mathbb{R}^N$ minimizing a perturbation of the Dirichlet energy with vertical penalization in $\Omega$ and horizontal penalization on $\partial\Omega$. We first show the…

Analysis of PDEs · Mathematics 2021-07-01 Giovanni Di Fratta , Antonin Monteil , Valeriy Slastikov

We show that in any $d$-dimensional real normed space, unit balls can be packed with density at least \[\frac{(1-o(1))d\log d}{2^{d+1}},\] improving a result of Schmidt from 1958 by a logarithmic factor and generalizing the recent result of…

Metric Geometry · Mathematics 2025-04-23 Carl Schildkraut

We study the dynamics of $SL_{2}(\mathbb{R})$ on the stratum of translation surfaces $\mathcal{H}(2)$. Especially, we obtain effective density theorems on $\mathcal{H}(2)$ for orbits of the upper triangular subgroup $P$ of…

Dynamical Systems · Mathematics 2025-02-18 Siyuan Tang

We use a new approach that we call unification to prove that standard weighted double bubbles in $n$-dimensional Euclidean space minimize immiscible fluid surface energy, that is, surface area weighted by constants. The result is new for…

Differential Geometry · Mathematics 2012-12-20 Gary R. Lawlor

This paper discusses the regularity of multiple-valued Dirichlet minimizing maps into the sphere. It shows that even at branched point, as long as the normalized energy is small enough, we have the energy decay estimate. Combined with the…

Optimization and Control · Mathematics 2007-05-23 Wei Zhu

It is well-known that under suitable hypotheses, for a sequence of solutions of the (simplified) Ginzburg-Landau equations $-\Delta u_\varepsilon +\varepsilon^{-2}(|u_\varepsilon|^2-1)u_\varepsilon = 0$, the energy and vorticity concentrate…

Analysis of PDEs · Mathematics 2021-01-12 Andrew Colinet , Robert Jerrard , Peter Sternberg

We consider the numerical computation of a variational problem that arises from materials science. The target functional is a type of elastic energy that is influenced by obstacles and adhesion. Owing to its strong nonlinearity and…

Numerical Analysis · Mathematics 2016-04-13 T. Kemmochi

We consider a two-dimensional analogue of Jacobi theta functions and prove that, among all lattices $\Lambda \subset \mathbb{R}^2$ with fixed density, the minimal value is maximized by the hexagonal lattice. This result can be interpreted…

Classical Analysis and ODEs · Mathematics 2021-10-13 Laurent Bétermin , Markus Faulhuber , Stefan Steinerberger

We consider the numerical solution of the fractional Laplacian of index $s\in(1/2,1)$ in a bounded domain $\Omega$ with homogeneous boundary conditions. Its solution a priori belongs to the fractional order Sobolev space ${\widetilde…

Numerical Analysis · Mathematics 2018-10-18 Juan Pablo Borthagaray , Patrick Ciarlet

We propose a minimal and self-contained model in non-compact flat five dimensions which localizes the Standard Model (SM) on a domain wall. Localization of gauge fields is achieved by the condensation of Higgs field via a Higgs dependent…

High Energy Physics - Phenomenology · Physics 2019-12-06 Masato Arai , Filip Blaschke , Minoru Eto , Norisuke Sakai

Given $iid$ observations from an unknown absolute continuous distribution defined on some domain $\Omega$, we propose a nonparametric method to learn a piecewise constant function to approximate the underlying probability density function.…

Machine Learning · Statistics 2018-03-13 Dangna Li , Kun Yang , Wing Hung Wong