Erraticity of Rapidity Gaps

TL;DR

This paper introduces a novel method to analyze the spatial pattern of particle events using rapidity gaps, employing entropy-like measures to quantify erraticity, especially effective at low multiplicities.

Contribution

It proposes a new approach to characterize event erraticity through moments of rapidity gap distributions and entropy measures, supported by simulations.

Findings

Erraticity measures depend on the order of moments q.

Rapidity gaps provide more information than multiplicity spikes at low multiplicities.

Simulation results demonstrate the effectiveness of the proposed measures.

Abstract

The use of rapidity gaps is proposed as a measure of the spatial pattern of an event. When the event multiplicity is low, the gaps between neighboring particles carry far more information about an event than multiplicity spikes, which may occur very rarely. Two moments of the gap distrubiton are suggested for characterizing an event. The fluctuations of those moments from event to event are then quantified by an entropy-like measure, which serves to describe erraticity. We use ECOMB to simulate the exclusive rapidity distribution of each event, from which the erraticity measures are calculated. The dependences of those measures on the order of $q$ of the moments provide single-parameter characterizations of erraticity.