New analyses of event shape observables in electron-positron annihilation and the determination of αs running behavior in perturbative domain

In this paper, we give comprehensive analyses for event shape observables in electron-positron annihilation by using the Principle of Maximum Conformality (PMC) which is a rigorous scale-setting method to eliminate the renormalization scheme and scale ambiguities in perturbative QCD predictions. Conventionally the renormalization scale and theoretical uncertainties in event shape observables are often evaluated by setting the scale to the center-of-mass energy root s. The event shape distributions using this conventional scale setting are plagued by the large renormalization scale uncertainty and underestimate the experimental data. Moreover, since the renormalization scale is simply fixed to the center-of-mass energy root s, only one value of the coupling alpha(s) at the single scale root s can be extracted. In contrast, the PMC renormalization scales are determined by absorbing the nonconformal beta contributions that govern the behavior of the running coupling via the Renormalization Group Equation (RGE). The resulting PMC scales change with event shape kinematics, reflecting the virtuality of the underlying quark and gluon subprocess. The PMC scales thus yield the correct physical behavior of the scale and the PMC predictions agree with precise event shape distributions measured at the LEP experiment. More importantly, we can precisely determine the running of the QCD coupling constant alpha(s)(Q(2)) over a wide range of Q(2) in perturbative domain from event shape distributions measured at a single center-of-mass energy root s.

Automated summary

This paper presents a comprehensive analysis of event shape observables in electron-positron annihilation using the Principle of Maximum Conformality (PMC). By eliminating the uncertainties associated with scale-setting and renormalization scheme in perturbative QCD predictions, the PMC provides accurate predictions that agree with experimental data.