Fitting the strong coupling constant with soft-drop thrust

Abstract

Soft drop has been shown to reduce hadronisation effects at e + e − colliders for the thrust event shape. In this context, we perform fits of the strong coupling constant for the soft-drop thrust distribution at NLO+NLL accuracy to pseudo data generated by the Sherpa event generator. In particular, we focus on the impact of hadronisation corrections, which we estimate both with an analytical model and a Monte-Carlo based one, on the fitted value of α s (m Z ). We find that grooming can reduce the size of the shift in the fitted value of α s due to hadronisation. In addition, we also explore the possibility of extending the fitting range down to significantly lower values of (one minus) thrust. Here, soft drop is shown to play a crucial role, allowing us to maintain good fit qualities and stable values of the fitted strong coupling. The results of these studies show that soft-drop thrust is a promising candidate for fitting α s at e + e − colliders with reduced impact of hadronisation effects.3. if the splitting fails the soft-drop condition, the softer subjet is discarded (groomed away) and the steps are repeated for the resulting jet (the harder subjet); 4. if instead the subjets pass the condition, the procedure is terminated and the resulting jet is the combination of subjets i and j.The soft-drop algorithm features two parameters: z cut and β. The first determines how stringent the cut on the subjet energies is, whereas the latter provides an angular suppression to grooming. While β → ∞ corresponds to no grooming, for β = 0 no angular dependence is taken into account and the soft-drop algorithm reduces to the modified Mass-Drop Tagger (mMDT) [29,30]. For practical purpose, we have implemented the above procedure using FastJet [31] for the jet clustering and additional manipulations.The event shape thrust [17] is defined aswhere p i labels the three-momentum of particle i and the sum extends over all particles in the event E. The resulting vector n defines the thrust axis. Often the related variable τ ≡ 1 − T = min n

Soft-drop thrust

“…where the last term ensures IRC safety for every β ≥ 0, including the potentially problematic case of β = 0 [50].…”

Two- and three-loop data for the groomed jet mass

“…This factorization theorem enabled calculation to next-to-next-to-leading logarithmic (NNLL) accuracy for jet observables, resulting in predictions with controlled theoretical uncertainties over a wide, and experimentally-relevant, region of phase space. Many other calculations for mMDT/soft drop groomed jet mass (and related observables) have followed [9][10][11][12][13][14][15][16][17][18][19][20][21], and both ATLAS and CMS have measured these groomed jet masses in collisions [22][23][24] and compared directly to theoretical predictions. Further calculations have been performed of groomed observables that are sensitive to additional structure in jets [25][26][27][28], and related grooming procedures have been introduced [29] that exploit the nice theoretical properties of these groomers.…”

Soft drop thrust in lepton collisions

“…Indeed, in Ref. [27] the extraction of α s (M Z ) was performed using matched NLO+NLL prediction for the soft drop thrust. The result is promising, and the reduction of the hadronization uncertainty is observed.…”