Analysis note: measurement of thrust in $e^{+}e^{-}$ collisions at $\sqrt{s}$ = 91 GeV with archived ALEPH data

TL;DR

This paper presents a new measurement of the thrust distribution in electron-positron collisions at 91 GeV using archived ALEPH data, employing machine learning for detector effect correction, and aims to improve understanding of strong interaction parameters.

Contribution

It introduces a novel machine learning based unbinned unfolding method for detector correction in $e^{+}e^{-}$ collision data, providing more precise thrust measurements.

Findings

First application of ML-based unfolding in $e^{+}e^{-}$ data

Provides new constraints on $oldsymbol{ ext{α}_s}$ and non-perturbative effects

Enhances precision in hadronic event shape analysis

Abstract

A measurement of the thrust distribution in $e^{+}e^{-}$ collisions at $\sqrt{s} = 91.2$ GeV with archived data from the ALEPH experiment at the Large Electron-Positron Collider is presented. The thrust distribution is reconstructed from charged and neutral particles resulting from hadronic $Z$-boson decays. For the first time with $e^{+}e^{-}$ data, detector effects are corrected using a machine learning based method for unbinned unfolding. The measurement provides new input for resolving current discrepancies between theoretical calculations and experimental determinations of $\alpha_{s}$, constraining non-perturbative effects through logarithmic moments, developing differential hadronization models, and enabling new precision studies using the archived data.