Abstract

The basis of the Chou-Yang model is made up of a stochastic and non-stochastic distribution and has been successful in describing forward-backward multiplicities.[1] This project examines data drawn from CERN’s 7 TeV run where we revist the Chou-Yang model’s components. It also approaches phenomenological descriptions for cluster sizes from forward-backward multiplicaity correlation strength by the E735 collaboration.[6] For the stochastic binomial component, it examines the variance of the charge asymmetry parameter z with regards to fixed total charged multiplicities n. The fitting of the Generalized Multiplicity distribution along with the linear least square fitting of the forward backward multiplicity is analysed. The parameters for the Generalized Multiplicity Distribution is presented along with an investigation on the cluster size r.[3] This serves as an extention to the work done by W.Y Wang’sWeighted GMD model at7TeV, however the nonweighted GMD model is used here.[7]

Highlights

  • The basis of the Chou-Yang model is made up of a stochastic and non-stochastic distribution and has been successful in describing forward-backward multiplicities.[1]

  • There have been no successful attempts in explaining the mechanics of forwardbackward multiplicity distributions

  • The Chou-Yang model is a phenomenological attempt at describing the forward-backward multiplicity distributions.[1]

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Summary

Introduction

The basis of the Chou-Yang model is made up of a stochastic and non-stochastic distribution and has been successful in describing forward-backward multiplicities.[1] This project applies this model to CERN’s 7 TeV data along with phenomenological descriptions of cluster sizes from the forward-backward multiplicity correlation strength [2]. The stoachastic component is made up of the variance of the charge asymmetry parameter z. The non-stochastic component involves the total charged multiplicity distribution, in the form of either the Negative Binomial Distribution(NBD) or the Generalized Multiplicity Distribution(GMD). These are used to predict forward-backward multiplicity correlation and serves as an extention to the work done by W.Y Wang’s Weighted GMD model at 7 TeV, the non-weighted GMD model is used here.[3]

Chou-Yang Model
Generalized Multiplicity Distribution
Forward-Backward Multiplicity Distribution
Conclusion
Future Outlook
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