GenEvA (II): A phase space generator from a reweighted parton shower

TL;DR

The paper presents an efficient phase space generator using a reweighted parton shower, enabling flexible event distribution and automatic matrix element improvement, applicable in advanced event generation frameworks.

Contribution

Introduces a novel phase space generation algorithm utilizing a reweighted parton shower within the GenEvA framework, enhancing event generation efficiency and accuracy.

Findings

Successfully reproduces e+e- -> n jets results

Demonstrates automatic improvement of matrix elements with resummation

Provides a versatile tool for advanced event generation

Abstract

We introduce a new efficient algorithm for phase space generation. A parton shower is used to distribute events across all of multiplicity, flavor, and phase space, and these events can then be reweighted to any desired analytic distribution. To verify this method, we reproduce the e+e- -> n jets tree-level result of traditional matrix element tools. We also show how to improve tree-level matrix elements automatically with leading-logarithmic resummation. This algorithm is particularly useful in the context of a new framework for event generation called GenEvA. In a companion paper [arXiv:0801.4026], we show how the GenEvA framework can address contemporary issues in event generation.