Generic framework for anisotropic flow analyses with multi-particle azimuthal correlations

Abstract

We present a new generic framework which enables exact and fast evaluation of all multi-particle azimuthal correlations. The framework can be readily used along with a correction framework for systematic biases in anisotropic flow analyses due to various detector inefficiencies. A new recursive algorithm has been developed for higher order correlators for the cases where their direct implementation is not feasible. We propose and discuss new azimuthal observables for anisotropic flow analyses which can be measured for the first time with our new framework. Effects of finite detector granularity on multi-particle correlations are quantified and discussed in detail. We point out the existence of a systematic bias in traditional differential flow analyses which stems solely from the applied selection criteria on particles used in the analyses, and is also present in the ideal case when only flow correlations are present. Finally, we extend the applicability of our generic framework to the case of differential multi-particle correlations.