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Related papers: On badly approximable subspaces

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It is well known due to Jarnik that the set Bad of badly approximable numbers is of Hausdorff-dimension one. If Bad(c) denotes the subset of x in Bad for which the approximation constant c > c(x), then Jarnik was in fact more precise and…

Dynamical Systems · Mathematics 2017-05-17 Steffen Weil

We explore and refine techniques for estimating the Hausdorff dimension of exceptional sets and their diffeomorphic images. Specifically, we use a variant of Schmidt's game to deduce the strong C^1 incompressibility of the set of badly…

Number Theory · Mathematics 2013-07-12 Ryan Broderick , Lior Fishman , David Simmons

In this paper we discuss some properties of completely irrational subspaces. We prove that there exist completely irrational subspaces that are badly approximable and, moreover, sets of such subspaces are winning in different senses. We get…

Number Theory · Mathematics 2025-02-18 Vasiliy Neckrasov

We prove that the Hausdorff dimension of the set of badly approximable systems of m linear forms in n variables over the field of Laurent series with coefficients from a finite field is maximal. This is a analogue of Schmidt's…

Number Theory · Mathematics 2007-05-23 Simon Kristensen

This paper is motivated by Davenport's problem and the subsequent work regarding badly approximable points in submanifolds of a Euclidian space. We study the problem in the area of twisted Diophantine approximation and present two different…

Number Theory · Mathematics 2017-05-17 Paloma Bengoechea , Nikolay Moshchevitin , Natalia Stepanova

In this paper we show that the set of mixed type badly approximable simultaneously small linear forms is of maximal dimension. As a consequence of this theorem we settle a conjecture of the first author.

Number Theory · Mathematics 2014-06-18 Mumtaz Hussain , Simon Kristensen

The badly approximable points in $\mathbb{R}^d$ are those for which Dirichlet's approximation theorem cannot be improved by more than a constant, that is, they are the points most difficult to approximate by rational vectors. An important…

Number Theory · Mathematics 2026-03-13 Roope Anttila , Jonathan M. Fraser , Henna Koivusalo

The subspace structure of Beidleman near-vector spaces is investigated. We characterise finite dimensional Beidleman near-vector spaces and we classify the R-subgroups of finite dimensional Beidleman near-vector spaces. We provide an…

Commutative Algebra · Mathematics 2018-10-18 P Djagba , K-T Howell

This paper is motivated by two problems in the theory of Diophantine approximation, namely, Davenport's problem regarding badly approximable points on submanifolds of a Euclidean space and Schmidt's problem regarding the intersections of…

Number Theory · Mathematics 2016-04-01 Victor Beresnevich

We prove a metric statement about approximation of a $n$-dimensional linear subspace $A$ in $\mathbb{R}^d$ by $n$-dimensional rational subspaces. We consider the problem of finding a rational subspace $B$ of bounded height $H=H(B)$ for…

Number Theory · Mathematics 2019-05-16 Nikolay Moshchevitin

The set of badly approximable $m \times n $ matrices is known to have Hausdorff dimension $mn $. Each such matrix comes with its own approximation constant $c$, and one can ask for the dimension of the set of badly approximable matrices…

Number Theory · Mathematics 2015-10-12 Ryan Broderick , Dmitry Kleinbock

In this paper, we study the weighted $n$-dimensional badly approximable points on manifolds. Given a $C^n$ differentiable non-degenerate submanifold $\mathcal{U} \subset \mathbb{R}^n$, we will show that any countable intersection of the…

Number Theory · Mathematics 2019-05-02 Lei Yang

Given an $n \times d$ dimensional dataset $A$, a projection query specifies a subset $C \subseteq [d]$ of columns which yields a new $n \times |C|$ array. We study the space complexity of computing data analysis functions over such…

Data Structures and Algorithms · Computer Science 2021-01-20 Graham Cormode , Charlie Dickens , David P. Woodruff

We study the Approximate Nearest Neighbor problem for metric spaces where the query points are constrained to lie on a subspace of low doubling dimension, while the data is high-dimensional. We show that this problem can be solved…

Computational Geometry · Computer Science 2012-09-19 Sariel Har-Peled , Nirman Kumar

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to…

We show that, for vector spaces in which distance measurement is performed using a gauge, the existence of best coapproximations in $1$-codimensional closed linear subspaces implies in dimensions $\geq 2$ that the gauge is a norm, and in…

Metric Geometry · Mathematics 2021-01-15 Thomas Jahn , Christian Richter

The merit of projecting data onto linear subspaces is well known from, e.g., dimension reduction. One key aspect of subspace projections, the maximum preservation of variance (principal component analysis), has been thoroughly researched…

Machine Learning · Computer Science 2022-09-27 Erik Thordsen , Erich Schubert

We show that finite dimensional Banach spaces fail to be uniformly non locally almost square. Moreover, we construct an equivalent almost square bidual norm on $\ell_\infty.$ As a consequence we get that every dual Banach space containing…

Functional Analysis · Mathematics 2020-03-10 Trond A. Abrahamsen , Petr Hájek , Stanimir Troyanski

This brief survey deals with multi-dimensional Diophantine approximations in sense of linear form and with simultaneous Diophantine approximations. We discuss the phenomenon of degenerate dimension of linear subspaces generated by the best…

Number Theory · Mathematics 2007-05-23 Nikolai G Moshchevitin

We study the best coapproximation problem in Banach spaces, by using Birkhoff-James orthogonality techniques. We introduce two special types of subspaces, christened the anti-coproximinal subspaces and the strongly anti-coproximinal…

Functional Analysis · Mathematics 2024-08-14 Shamim Sohel , Souvik Ghosh , Debmalya Sain , Kallol Paul
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