On feasibility of azimuthal flow studies with Principal Component Analysis

TL;DR

This paper demonstrates that Principal Component Analysis can effectively analyze azimuthal flow in particle physics, offering an alternative to traditional multi-particle correlation methods, with minimal impact from statistical fluctuations.

Contribution

It introduces PCA as a viable method for azimuthal flow analysis, comparable to traditional approaches, and shows its robustness against statistical fluctuations.

Findings

PCA can be used for flow analysis similar to multi-particle correlations.

Higher order PCA-based cumulants are minimally affected by statistical fluctuations.

Symmetric cumulants are effectively analyzed using PCA.

Abstract

It is shown that the Principal Component Analysis applied to azimuthal single-particle distributions allows to perform flow analysis in ways that are analogous to the traditional approaches based on multi-particle correlations. In particular, symmetric cumulants are considered. It is demonstrated also that statistical fluctuations due to a finite number of particles per event practically do not play a role for higher order PCA-based cumulants.