# Implementing NLO DGLAP evolution in Parton Showers

## TL;DR

This paper introduces a next-to-leading order (NLO) DGLAP evolution implementation within parton showers, enhancing the precision of simulations by incorporating advanced splitting functions and avoiding double counting.

## Contribution

It presents a novel NLO DGLAP evolution algorithm integrated into parton showers, compatible with existing frameworks, and demonstrates improved accuracy in Monte Carlo simulations.

## Key findings

- Enhanced simulation precision with NLO DGLAP implementation
- Successful integration into Pythia and Sherpa frameworks
- Effective soft double counting avoidance

## Abstract

We present a parton shower which implements the DGLAP evolution of parton densities and fragmentation functions at next-to-leading order precision up to effects stemming from local four-momentum conservation. The Monte-Carlo simulation is based on including next-to-leading order collinear splitting functions in an existing parton shower and combining their soft enhanced contributions with the corresponding terms at leading order. Soft double counting is avoided by matching to the soft eikonal. Example results from two independent realizations of the algorithm, implemented in the two event generation frameworks Pythia and Sherpa, illustrate the improved precision of the new formalism.