Automated inclusion of QED corrections in Monte Carlo event generators

TL;DR

This thesis develops automated, process-independent methods for calculating QED radiative corrections in Monte Carlo event generators, validating them against established resummation techniques and implementing them in a public framework.

Contribution

It introduces a QED parton shower, QCD+QED MC@NLO matching, and extends YFS resummation, providing new tools for precise simulations of particle physics processes.

Findings

QED parton shower predictions agree with YFS resummation.

QCD+QED MC@NLO preserves accuracy for mixed corrections.

Methods are implemented in a public Monte Carlo generator.

Abstract

In this thesis, we present automated, process-independent methods for the calculation of QED real radiative corrections. We review the construction of a parton shower based on Catani-Seymour dipole subtraction, and thus detail the implementation of a QED parton shower. We validate the predictions made by the shower against the YFS soft-photon resummation, and discuss the algorithmic choices made. We then present results for the production of a Higgs boson at the LHC and its decay to leptons, showing that the interleaved QCD+QED parton shower predicts distributions in excellent agreement with the YFS approach. We then study the MC@NLO method for matching a next-to-leading order calculation with a parton shower. Showing that the method preserves its accuracy for the case of QED corrections and of mixed QCD and QED corrections, we present the QCD+QED MC@NLO method. Validating the method against both the YFS resummation and the QED parton shower, we find very good agreement. Finally, we present an extension to the YFS soft-photon resummation, in which we use a one-step parton shower to resum the logarithms associated with charged particle pair production. Throughout this thesis we also discuss the impact of dressed lepton definitions on observables. The methods presented in this thesis are made available in a public Monte Carlo event generator and analysis framework.