An Analytic Initial-State Parton Shower

TL;DR

This paper introduces a novel analytic initial-state parton shower algorithm that precisely defines the probability distribution of all branchings, enabling event reweighting and improved accuracy in high-energy physics simulations.

Contribution

It presents the first construction of an analytic initial-state parton shower, including scale choices and angular ordering, with comparisons to existing showers and experimental data.

Findings

The algorithm allows exact calculation of event probabilities.

It successfully merges with matrix elements for high-energy tails.

Results agree well with experimental data from LEP, Tevatron, and LHC.

Abstract

We present a new algorithm for an analytic parton shower. While the algorithm for the final-state shower has been known in the literature, the construction of an initial-state shower along these lines is new. The aim is to have a parton shower algorithm for which the full analytic form of the probability distribution for all branchings is known. For these parton shower algorithms it is therefore possible to calculate the probability for a given event to be generated, providing the potential to reweight the event after the simulation. We develop the algorithm for this shower including scale choices and angular ordering. Merging to matrix elements is used to describe high-energy tails of distributions correctly. Finally, we compare our results with those of other parton showers and with experimental data from LEP, Tevatron and LHC.