The most uniform distribution of points on the sphere
Journal article, 2024

How to distribute a set of points uniformly on a spherical surface is a longstanding 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, as an alternative to commonly adopted measures based on interaction potentials. We then use this new measure of uniformity to characterize several algorithms available in the literature. We also study the effect of optimizing the position of the points through the minimization of different interaction potentials via a gradient descent procedure. In this way, we can classify different algorithms and interaction potentials to find the one that generates the most uniform distribution of points on the sphere.

Theoretical

Algorithms

Models

Author

Luca Maria Del Bono

Sapienza University of Rome

Flavio Nicoletti

Data Science and AI 3

University of Gothenburg

Federico Ricci-Tersenghi

Sapienza

Sapienza University of Rome

National Institute for Nuclear Physics

PLoS ONE

1932-6203 (ISSN) 19326203 (eISSN)

Vol. 19 12 e0313863

Subject Categories (SSIF 2025)

Discrete Mathematics

Computational Mathematics

DOI

10.1371/journal.pone.0313863

More information

Latest update

1/14/2026