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In this paper, we have considered a uniform probability distribution supported by a stretched Sierpi\'nski triangle. For this probability measure, the optimal sets of $n$-means and the $n$th quantization errors are determined for all $n\geq…

Dynamical Systems · Mathematics 2019-06-17 Dogan Comez , Mrinal Kanti Roychowdhury

Quantization for probability distributions refers broadly to estimating a given probability measure by a discrete probability measure supported by a finite number of points. We consider general geometric approaches to quantization using…

Dynamical Systems · Mathematics 2020-02-11 Joseph Rosenblatt , Mrinal Kanti Roychowdhury

Quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with support containing a finite number of elements. If in the quantization some of the elements in the support are…

Probability · Mathematics 2025-03-24 Pigar Biteng , Mathieu Caguiat , Tsianna Dominguez , Mrinal Kanti Roychowdhury

Quantization for a probability distribution refers to the idea of estimating a given probability by a discrete probability supported by a finite set. In this article, we consider a probability distribution generated by an infinite system of…

Dynamical Systems · Mathematics 2022-04-26 Dogan Comez , Mrinal Kanti Roychowdhury

We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit…

Information Theory · Computer Science 2010-08-24 Yuriy A. Reznik

Constrained quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with a finite number of supporting points lying on a specific set. The specific set is known as the…

We study quantum algorithms for verifying properties of the output probability distribution of a classical or quantum circuit, given access to the source code that generates the distribution. We consider the basic task of uniformity…

Quantum Physics · Physics 2024-11-08 Clément L. Canonne , Robin Kothari , Ryan O'Donnell

We study the problem of uncertainty quantification for the numerical solution of elliptic partial differential equation boundary value problems posed on domains with stochastically varying boundaries. We also use the uncertainty…

Numerical Analysis · Mathematics 2018-07-17 Jehanzeb H Chaudhry , Nathanial Burch , Donald Estep

Given an elliptic curve $E$ and a point $P$ in $E(\mathbb{R})$, we investigate the distribution of the points $nP$ as $n$ varies over the integers, giving bounds on the $x$ and $y$ coordinates of $nP$ and determining the natural density of…

Number Theory · Mathematics 2020-09-29 Alex Cowan

Recent results in quantization theory show that the mean-squared expected distortion can reach a rate of convergence of $\mathcal{O}(1/n)$, where $n$ is the sample size [see, e.g., IEEE Trans. Inform. Theory 60 (2014) 7279-7292 or Electron.…

Statistics Theory · Mathematics 2015-04-02 Clément Levrard

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions are a special case where the density matrix is restricted to be diagonal. Density…

Quantum Physics · Physics 2014-08-14 Manfred K. Warmuth , Dima Kuzmin

Zador's celebrated theorem is a cornerstone of optimal quantisation, establishing both the weak limit of the empirical distribution of an $n$-point optimal quantiser in $R^d$ and the decay rate of the associated $L_s$-mean quantisation…

Statistics Theory · Mathematics 2026-05-14 Luc Pronzato , Anatoly Zhigljavsky

Kernel mean embeddings are a popular tool that consists in representing probability measures by their infinite-dimensional mean embeddings in a reproducing kernel Hilbert space. When the kernel is characteristic, mean embeddings can be used…

Machine Learning · Computer Science 2021-06-29 Boris Muzellec , Francis Bach , Alessandro Rudi

This paper develops a systematic and geometric theory of optimal quantization on the unit sphere $\mathbb S^2$, focusing on finite uniform probability distributions supported on the spherical surface - rather than on lower-dimensional…

Optimization and Control · Mathematics 2026-01-08 Mrinal Kanti Roychowdhury

In this paper, for a given family of constraints and the classical Cantor distribution we determine the constrained optimal sets of $n$-points, $n$th constrained quantization errors for all positive integers $n$. We also calculate the…

Dynamical Systems · Mathematics 2024-03-05 Megha Pandey , Mrinal Kanti Roychowdhury

How to distribute a set of points uniformly on a spherical surface is a very old problem that still lacks a definite answer. In this work, we introduce a physical measure of uniformity based on the distribution of distances between points,…

Statistical Mechanics · Physics 2025-01-09 Luca Maria Del Bono , Flavio Nicoletti , Federico Ricci-Tersenghi

Let $(x_n)_{n=1}^{\infty}$ be a sequence on the torus $\mathbb{T}$ (normalized to length 1). We show that if there exists a sequence of positive real numbers $(t_n)_{n=1}^{\infty}$ converging to 0 such that $$\lim_{N \rightarrow \infty}{…

Number Theory · Mathematics 2020-11-02 Stefan Steinerberger

We obtain multidimensional metric uniform distribution results involving sequences in ${\mathbb R}^k$ parametrized by analytic curves. Our theorems extend the classical theorems of Weyl and Koksma in a variety of ways. One of our main…

Classical Analysis and ODEs · Mathematics 2025-09-09 Vitaly Bergelson , Joel Moreira

Let $\{S_j : 1\leq j\leq 3\}$ be a set of three contractive similarity mappings such that $S_j(x)=rx+\frac {j-1}{2}(1-r)$ for all $x\in \mathbb R$, and $1\leq j\leq 3$, where $0<r<\frac 1 3$. Let $P=\sum_{j=1}^3 \frac 13 P\circ S_j^{-1}$.…

Dynamical Systems · Mathematics 2022-10-18 Mrinal Kanti Roychowdhury

By a classical theorem of Koksma the sequence of fractional parts $(\{x^n\})_{n \geq 1}$ is uniformly distributed for almost all values of $x$. In the present paper we obtain an exact quantitative version of Koksma's theorem, by calculating…

Number Theory · Mathematics 2013-08-16 Christoph Aistleitner