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We prove an effective estimate for the counting function of Diophantine approximants on the sphere S$^n$. We use homogeneous dynamics on the space of orthogonal lattices, in particular effective equidistribution results and non-divergence…

Number Theory · Mathematics 2022-06-20 Zouhair Ouaggag

In this paper we study counting functions representing the number of solutions of systems of linear inequalities which arise in the theory of Diophantine approximation. We develop a method that allows us to explain the random-like behavior…

Dynamical Systems · Mathematics 2018-04-18 Michael Björklund , Alexander Gorodnik

We investigate the number of integer solutions to a multiplicative Diophantine approximation problem and show that the associated counting function converges in distribution to a normal law. Our approach relies on the analysis of…

Number Theory · Mathematics 2026-01-21 Michael Björklund , Reynold Fregoli , Alexander Gorodnik

We investigate in this paper the distribution of the discrepancy of various lattice counting functions. In particular, we prove that the number of lattice points contained in certain domains defined by products of linear forms satisfies a…

Number Theory · Mathematics 2017-09-22 Michael Björklund , Alexander Gorodnik

We establish effective convergence rates in the Doeblin-Lenstra law, describing the limiting distribution of approximation coefficients arising from continued fraction convergents of a typical real number. More generally, we prove…

Number Theory · Mathematics 2025-07-28 Gaurav Aggarwal , Anish Ghosh

We quantify the density of rational points in the unit sphere $S^n$, proving analogues of the classical theorems on the embedding of $\q^n$ into $\r^n$. Specifically, we prove a Dirichlet theorem stating that every point $\alpha \in S^n$ is…

Number Theory · Mathematics 2013-05-28 Dmitry Kleinbock , Keith Merrill

We use a method developed by Bj\"orklund and Gorodnik to show a central limit theorem (as $T$ tends to $\infty$) for the counting functions $\# \left( \Lambda \cap \Omega_T \right)$ where $\Lambda$ ranges over the space $Y_{2d}$ of…

Number Theory · Mathematics 2023-04-18 Kristian Holm

We prove a quantitative theorem for Diophantine approximation by rational points on spheres. Our results are valid for arbitrary unimodular lattices and we further prove 'spiraling' results for the direction of approximates. These results…

Number Theory · Mathematics 2022-08-01 Mahbub Alam , Anish Ghosh

We use a dictionary between lattice point counting inside dilated d-dimensional ellipsoids (Euclidean counting) and counting of lifts of a closed horosphere that intersect a ball of increasing radius, to obtain two types of results.…

Dynamical Systems · Mathematics 2021-12-28 Cornelia Druţu , Norbert Peyerimhoff

We consider rational points on the sphere and investigate their equidistribution in shrinking spherical caps. For the two-dimensional sphere, we leverage Hecke operators to obtain a significantly improved small-scale equidistribution bound,…

Number Theory · Mathematics 2025-02-26 Claire Burrin , Matthias Gröbner

The paper is devoted to the problem of estimating the constant of the best Diophantine approximations. The estimates of lower bound $ C_n $ for $ n = 5 $ and $ n = 6 $ was improved. The first chapter gives an overview of the history of…

Number Theory · Mathematics 2019-04-10 Yurij Basalov

We consider the estimation of two-sample integral functionals, of the type that occur naturally, for example, when the object of interest is a divergence between unknown probability densities. Our first main result is that, in wide…

Statistics Theory · Mathematics 2023-01-31 Thomas B. Berrett , Richard J. Samworth

We compute higher derivatives of the Fr\'{e}chet function on spheres with an absolutely continuous and rotationally symmetric probability distribution. Consequences include (i)~a practical condition to test if the mode of the symmetric…

Statistics Theory · Mathematics 2020-04-28 Do Tran

Each non-zero point in $\mathbb{R}^d$ identifies a closest point $x$ on the unit sphere $\mathbb{S}^{d-1}$. We are interested in computing an $\epsilon$-approximation $y \in \mathbb{Q}^d$ for $x$, that is exactly on $\mathbb{S}^{d-1}$ and…

Computational Geometry · Computer Science 2017-07-27 Daniel Bahrdt , Martin P. Seybold

We study metric Diophantine approximation in local fields of positive characteristic. Specifically, we study the problem of improving Dirichlet's theorem in Diophantine approximation and prove very general results in this context.

Number Theory · Mathematics 2019-08-15 Arijit Ganguly , Anish Ghosh

We study the distribution modulo $1$ of the values taken on the integers of $r$ linear forms in $d$ variables with random coefficients. We obtain quenched and annealed central limit theorems for the number of simultaneous hits into…

Dynamical Systems · Mathematics 2016-05-03 Dmitry Dolgopyat , Bassam Fayad , Ilya Vinogradov

We consider the problem of counting lattice points contained in domains in $\mathbb{R}^d$ defined by products of linear forms and we show that the normalized discrepancies in these counting problems satisfy non-degenerate Central Limit…

Dynamical Systems · Mathematics 2021-01-14 Michael Björklund , Alexander Gorodnik

We estimate linear functionals in the classical deconvolution problem by kernel estimators. We obtain a uniform central limit theorem with $\sqrt{n}$-rate on the assumption that the smoothness of the functionals is larger than the…

Statistics Theory · Mathematics 2020-06-12 Jakob Söhl , Mathias Trabs

We exploit dynamical properties of diagonal actions to derive results in Diophantine approximations. In particular, we prove that the continued fraction expansion of almost any point on the middle third Cantor set (with respect to the…

Dynamical Systems · Mathematics 2011-01-21 Manfred Einsiedler , Lior Fishman , Uri Shapira

We study the asymptotic shape of the trajectory of the stochastic gradient descent algorithm applied to a convex objective function. Under mild regularity assumptions, we prove a functional central limit theorem for the properly rescaled…

Machine Learning · Statistics 2026-02-18 Kessang Flamand , Victor-Emmanuel Brunel
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