Principal component analysis of event-by-event fluctuations

TL;DR

This paper introduces principal component analysis to analyze event-by-event fluctuations in heavy-ion collisions, revealing new subleading modes in flow and momentum distributions using ALICE data and simulations.

Contribution

It provides a novel application of PCA to extract detailed fluctuation modes in heavy-ion collision data, enhancing understanding of flow phenomena.

Findings

Revealed previously unknown subleading fluctuation modes.

Analyzed elliptic and triangular flow as functions of momentum and rapidity.

Applied PCA successfully to both experimental and simulated data.

Abstract

We apply principal component analysis to the study of event-by-event fluctuations in relativistic heavy-ion collisions. This method brings out all the information contained in two-particle correlations in a physically transparent way. We present a guide to the method, and apply it to multiplicity fluctuations and anisotropic flow, using ALICE data and simulated events. In particular, we study elliptic and triangular flow fluctuations as a function of transverse momentum and rapidity. This method reveals previously unknown subleading modes in both rapidity and transverse momentum for the momentum distribution as well as elliptic and triangular flows.