Neural network predictions for Z' boson within LEP2 data set of Bhabha process

TL;DR

This paper applies neural networks to analyze LEP2 data for the e+ e- -> e+ e- process, aiming to detect Z' bosons, and estimates its couplings and mass with improved data reduction and parameter fitting.

Contribution

It introduces a neural network approach to search for Z' bosons in LEP2 data, providing new estimates of couplings and mass within a two-parameter fit.

Findings

Data set reduced by 20 percent

Z' mass estimated at 0.53-1.05 TeV

Couplings estimated at 95% confidence level

Abstract

The neural network approach is applied to search for the Z'-boson within the LEP2 data set for e+ e- -> e+ e- scattering process. In the course of the analysis, the data set is reduced by 20 percent. The axial-vector and vector couplings of the Z' are estimated at 95 percent CL within a two-parameter fit. The mass is determined to be 0.53-1.05 TeV. Comparisons with other results are given.