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The main result of the paper shows that the regular $n$-gon is a local minimizer for the first Dirichlet-Laplace eigenvalue among $n$-gons having fixed area for $n \in \{5,6\}$. The eigenvalue is seen as a function of the coordinates of the…

Numerical Analysis · Mathematics 2024-06-18 Beniamin Bogosel , Dorin Bucur

A classical result of Cheng states that the bottom spectrum of complete manifolds of fixed dimension and Ricci curvature lower bound achieves its maximal value on the corresponding hyperbolic space. The paper establishes an analogous result…

Differential Geometry · Mathematics 2024-06-05 Ovidiu Munteanu , Jiaping Wang

In this paper we use min-max theory to study the existence free boundary minimal hypersurfaces (FBMHs) in compact manifolds with boundary $(M^{n+1}, \partial M, g)$, where $2\leq n\leq 6$. Under the assumption that $g$ is a local maximizer…

Differential Geometry · Mathematics 2020-12-03 Yucheng Tu

Guaranteed lower Dirichlet eigenvalue bounds (GLB) can be computed for the $m$-th Laplace operator with a recently introduced extra-stabilized nonconforming Crouzeix-Raviart ($m=1$) or Morley ($m=2$) finite element eigensolver. Striking…

Numerical Analysis · Mathematics 2022-03-03 Carsten Carstensen , Sophie Puttkammer

We demonstrate lower bounds for the eigenvalues of compact Bakry-Emery manifolds with and without boundary. The lower bounds for the first eigenvalue rely on a generalised maximum principle which allows gradient estimates in the Riemannian…

Spectral Theory · Mathematics 2020-12-14 Nelia Charalambous , Zhiqin Lu , Julie Rowlett

The purpose of this article is study rigidity of free boundary minimal two-disks that locally maximize the modified Hawking mass on a Riemannian three-manifold with positive lower bound on its scalar curvature and mean convex boundary.…

Differential Geometry · Mathematics 2024-06-19 Rondinelle Batista , Barnabé Lima , João Silva

We suggest a method for simultaneously generating high order quadrature weights for integrals over Lipschitz domains and their boundaries that requires neither meshing nor moment computation. The weights are determined on pre-defined…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Bruno Degli Esposti

We prove a \emph{query complexity} lower bound on rank-one principal component analysis (PCA). We consider an oracle model where, given a symmetric matrix $M \in \mathbb{R}^{d \times d}$, an algorithm is allowed to make $T$ \emph{exact}…

Machine Learning · Computer Science 2017-04-18 Max Simchowitz , Ahmed El Alaoui , Benjamin Recht

In this paper we derive an estimate on the number of local maxima of the free boundary of some variational inequalities with pointwise gradient constraints. This also gives an estimate on the number of connected components of the free…

Analysis of PDEs · Mathematics 2018-07-04 Mohammad Safdari

Finite-sum optimization plays an important role in the area of machine learning, and hence has triggered a surge of interest in recent years. To address this optimization problem, various randomized incremental gradient methods have been…

Machine Learning · Computer Science 2022-06-22 Min Zhang , Yao Shu , Kun He

This is a continuation of our earlier work [14] on the Monge-Amp\`ere obstacle problem \[ \det D^2 v = v^q \chi_{\{v>0\}}, \quad v \geq 0 \text{ convex} \] with $q \in [0,n)$, where we studied the regularity of the strictly convex part of…

Analysis of PDEs · Mathematics 2025-06-11 Tianling Jin , Xushan Tu , Jingang Xiong

Motivated by applications to matrix multiplication algorithms, Pratt asked (ITCS'24) how large a subset of $[n] \times [n]$ could be without containing a skew-corner: three points $(x,y), (x,y+h),(x+h,y')$ with $h \ne 0$. We prove any skew…

Combinatorics · Mathematics 2025-09-30 Michael Jaber , Shachar Lovett , Anthony Ostuni

In this paper we initiate the investigation of free boundary minimization problems ruled by general singular operators with $A_2$ weights. We show existence and boundedness of minimizers. The key novelty is a sharp $C^{1+\gamma}$ regularity…

Analysis of PDEs · Mathematics 2020-01-08 Jimmy Lamboley , Yannick Sire , Eduardo V. Teixeira

Finite element approximations of minimal surface are not always precise. They can even sometimes completely collapse. In this paper, we provide a simple and inexpensive method, in terms of computational cost, to improve finite element…

Numerical Analysis · Mathematics 2018-05-18 Aymeric Grodet , Takuya Tsuchiya

We prove sharp wavenumber-explicit error bounds for first- or second-family-N\'ed\'elec-element (a.k.a. edge-element) conforming discretisations, of arbitrary (fixed) order, of the variable-coefficient time-harmonic Maxwell equations posed…

Numerical Analysis · Mathematics 2026-01-09 Théophile Chaumont-Frelet , Jeffrey Galkowski , Euan A. Spence

Let $\gamma$ be a smooth, non-closed, simple curve whose image is symmetric with respect to the $y$-axis, and let $D$ be a planar domain consisting of the points on one side of $\gamma$, within a suitable distance $\delta$ of $\gamma$.…

Spectral Theory · Mathematics 2018-07-25 B. Brandolini , F. Chiacchio , E. B. Dryden , J. J. Langford

In this paper, we prove uniform curvature estimates for immersed stable free boundary minimal hypersurfaces which satisfy a uniform area bound. Our result is a natural generalization of the celebrated Schoen-Simon-Yau interior curvature…

Differential Geometry · Mathematics 2020-01-06 Qiang Guang , Martin Li , Xin Zhou

We study non-stationary averaging processes, where each term of a sequence is a weighted average of previous terms, namely $a_{n+1} = \sum_{j=1}^n p_n(j) a_j$. Our results extend classical theory in two distinct regimes. First, we prove a…

Probability · Mathematics 2026-03-18 Saba Lepsveridze , Elchanan Mossel

This paper is devoted to providing quantitative bounds on the location of eigenvalues, both discrete and embedded, of non self-adjoint Lam\'e operators of elasticity $-\Delta^\ast + V$ in terms of suitable norms of the potential $V$. In…

Spectral Theory · Mathematics 2021-01-26 Biagio Cassano , Lucrezia Cossetti , Luca Fanelli

Stochastic convex optimization is one of the most well-studied models for learning in modern machine learning. Nevertheless, a central fundamental question in this setup remained unresolved: "How many data points must be observed so that…

Machine Learning · Computer Science 2023-11-10 Daniel Carmon , Roi Livni , Amir Yehudayoff