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The Subspace Theorem is a powerful tool in number theory. It has appeared in various forms and been adapted and improved over time. It's applications include diophantine approximation, results about integral points on algebraic curves and…

Combinatorics · Mathematics 2013-11-18 Ryan Schwartz , Jozsef Solymosi

We provide a new existence result for weak solutions to the one-dimensional Euler equations with a maximal density constraint, corresponding to a unilateral constraint on the density. Such models arise in the description of congestion…

Analysis of PDEs · Mathematics 2026-04-06 Charlotte Perrin

We extend the data compression theorem to the case of ergodic quantum information sources. Moreover, we provide an asymptotically optimal compression scheme which is based on the concept of high probability subspaces. The rate of this…

Quantum Physics · Physics 2007-05-23 Igor Bjelakovic , Arleta Szkola

We propose a computational framework for computing low-rank approximations to the ensemble of solutions of a parametrized system of the form $A(\xi)x(\xi)+g(x(\xi))=b(\xi)$ for multiple parameter values. The central idea is to reinterpret…

Numerical Analysis · Mathematics 2026-04-09 Marco Sutti , Tommaso Vanzan

We introduce a new type of Krasnoselskii's result. Using a simple differentiability condition, we relax the nonexpansive condition in Krasnoselskii's theorem. More clearly, we analyze the convergence of the sequence…

Functional Analysis · Mathematics 2022-06-07 Hassan Khandani , Farshid Khojasteh

In this work we use variational methods to prove results on existence and concentration of solutions to a problem in $\mathbb{R}^N$ involving the $1-$Laplacian operator. A thorough analysis on the energy functional defined in the space of…

Analysis of PDEs · Mathematics 2017-02-23 C. O. Alves , M. T. O. Pimenta

This paper presents a general formulation of equations of motion of a pendulum with n point mass by use of two different methods. The first one is obtained by using Lagrange Mechanics and mathematical induction(inspection), and the second…

Classical Physics · Physics 2020-02-11 Boran Yesilyurt

The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under a standard assumption formulated in terms of…

Functional Analysis · Mathematics 2023-04-13 F. Dai , E. Kosov , V. Temlyakov

The ever-growing amounts of visual contents captured on a daily basis necessitate the use of lossy compression methods in order to save storage space and transmission bandwidth. While extensive research efforts are devoted to improving…

Image and Video Processing · Electrical Eng. & Systems 2021-03-30 Yuval Bahat , Tomer Michaeli

Let $\{a_n\}_{n\in\mathbb{N}}$, $\{b_n\}_{n\in \mathbb{N}}$ be two infinite subsets of positive integers and $\psi:\mathbb{N}\to \mathbb{R}_{>0}$ be a positive function. We completely determine the Hausdorff dimensions of the set of all…

Number Theory · Mathematics 2024-09-30 Bing Li , Ruofan Li , Yufeng Wu

When introducing a nanoparticle into an optical trap, its mass and shape are not immediately apparent. We combine a charge-based mass measurement with a shape determination method based on light scattering and an analysis of the damping…

We formulate a precise conjecture about the size of the $L^\infty$-mass of the space of Jacobi forms on $\mathbb H_n \times \mathbb C^{g \times n}$ of matrix index $S$ of size $g$. This $L^\infty$-mass is measured by the size of the Bergman…

Number Theory · Mathematics 2023-02-28 Pramath Anamby , Soumya Das

In distribution compression, one aims to accurately summarize a probability distribution $\mathbb{P}$ using a small number of representative points. Near-optimal thinning procedures achieve this goal by sampling $n$ points from a Markov…

Machine Learning · Statistics 2022-10-19 Abhishek Shetty , Raaz Dwivedi , Lester Mackey

This article develops nonparametric inference procedures for estimation and testing problems for means on manifolds. A central limit theorem for Frechet sample means is derived leading to an asymptotic distribution theory of intrinsic…

Statistics Theory · Mathematics 2007-06-13 Rabi Bhattacharya , Vic Patrangenaru

The ever-increasing parameter counts of deep learning models necessitate effective compression techniques for deployment on resource-constrained devices. This paper explores the application of information geometry, the study of…

Machine Learning · Computer Science 2025-07-15 Zakhar Shumaylov , Vasileios Tsiaras , Yannis Stylianou

In this paper we consider eigenfunctions of the Laplacian on a planar domain with polygonal boundary with Dirichlet, Neumann, or mixed boundary conditions. The main result is a quantitative estimate on the $L^2$ mass of eigenfunctions near…

Analysis of PDEs · Mathematics 2018-08-13 Hans Christianson

We give upper and lower bounds for Diophantine exponents measuring how well a point in the plane can be approximated by points in the orbit of a lattice $\Gamma<\mathrm{SL}_2(\mathbb{R})$ acting linearly on $\mathbb{R}^2$. Our method gives…

Number Theory · Mathematics 2016-06-29 Dubi Kelmer

Functional lifting methods provide a tool for approximating solutions of difficult non-convex problems by embedding them into a larger space. In this work, we investigate a mathematically rigorous formulation based on embedding into the…

Optimization and Control · Mathematics 2020-07-07 Thomas Vogt , Roland Haase , Danielle Bednarski , Jan Lellmann

We revise the cosmological standard model presuming that matter, i.e. baryons and cold dark matter, exhibits a non-vanishing pressure mimicking the cosmological constant effects. In particular, we propose a scalar field Lagrangian $\mathcal…

General Relativity and Quantum Cosmology · Physics 2018-11-28 Orlando Luongo , Marco Muccino

We analyze the approximation by mixed finite element methods of solutions of equations of the form $-\mbox{div\,} (a\nabla u) = g$, where the coefficient $a=a(x)$ can degenerate going to cero or infinity. First, we extend the classic error…

Numerical Analysis · Mathematics 2019-03-14 Maria E. Cejas , Ricardo G. Duran , Maria I. Prieto