Intermittency Analysis of Toy Monte Carlo Events

TL;DR

This paper investigates the intermittency behavior of high multiplicity events in Toy Monte Carlo simulations, analyzing normalized factorial moments to understand self-similar fluctuations and effects of detector efficiency.

Contribution

It provides a baseline for experimental intermittency analysis and clarifies how efficiency corrections impact the interpretation of factorial moments.

Findings

Normalized factorial moments follow a power law with bin number, indicating intermittency.

Detector efficiency affects the measured factorial moments, requiring correction.

Results serve as a reference for experimental data analysis.

Abstract

Event-by-event intermittency analysis of Toy Monte Carlo events is performed in the scenario of high multiplicity events as is the case at recent colliders RHIC and LHC for AA collisions. A power law behaviour of Normalized Factorial Moments (NFM), $F_{q}$ as function of number of bins ($M$) known as intermittency, is a signature of self-similar fluctuations. Dependence of NFM on the detector efficiencies and on the presence of fluctuations have been studied. Results presented here provide a baseline to the experimental results and clarity on the application of efficiency corrections to the experimental data.