Possibility to disentangle anisotropic flow, flow fluctuation, and nonflow assuming Gaussian fluctuations

TL;DR

This paper proposes a method to separate anisotropic flow, flow fluctuations, and nonflow effects in particle collision data by assuming Gaussian fluctuations, especially effective when fluctuations are large.

Contribution

It introduces a novel approach to disentangle flow components assuming Gaussian fluctuations, verified through Monte Carlo simulations.

Findings

Disentanglement is feasible with large flow fluctuations.

Small fluctuations make disentanglement challenging.

Monte Carlo simulations support the proposed method.

Abstract

We suggest the possibility to disentangle anisotropic flow, flow fluctuation, and nonflow using two-, four-, and six-particle azimuthal moments assuming Gaussian fluctuations. We show that such disentanglement is possible when the flow fluctuations are large, comparable to the average flow magnitude. When fluctuations are small, the disentanglement becomes difficult. We verify our results with a toy-model Monte Carlo simulation.