How to GAN Event Unweighting

Backes, Mathias; Butter, Anja; Plehn, Tilman; Winterhalder, Ramon

doi:10.21468/SciPostPhys.10.4.089

SciPost Physics

How to GAN Event Unweighting

Mathias Backes, Anja Butter, Tilman Plehn, Ramon Winterhalder

SciPost Phys. 10, 089 (2021) · published 23 April 2021

doi: 10.21468/SciPostPhys.10.4.089
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Abstract

Event generation with neural networks has seen significant progress recently. The big open question is still how such new methods will accelerate LHC simulations to the level required by upcoming LHC runs. We target a known bottleneck of standard simulations and show how their unweighting procedure can be improved by generative networks. This can, potentially, lead to a very significant gain in simulation speed.

TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhys.10.4.089
TI  - How to GAN Event Unweighting
PY  - 2021/04/23
UR  - https://www.scipost.org/SciPostPhys.10.4.089
JF  - SciPost Physics
JA  - SciPost Phys.
VL  - 10
IS  - 4
SP  - 089
A1  - Backes, Mathias
AU  - Butter, Anja
AU  - Plehn, Tilman
AU  - Winterhalder, Ramon
AB  - Event generation with neural networks has seen significant progress recently. The big open question is still how such new methods will accelerate LHC simulations to the level required by upcoming LHC runs. We target a known bottleneck of standard simulations and show how their unweighting procedure can be improved by generative networks. This can, potentially, lead to a very significant gain in simulation speed.
ER  -

@Article{10.21468/SciPostPhys.10.4.089,
	title={{How to GAN Event Unweighting}},
	author={Mathias Backes and Anja Butter and Tilman Plehn and Ramon Winterhalder},
	journal={SciPost Phys.},
	volume={10},
	pages={089},
	year={2021},
	publisher={SciPost},
	doi={10.21468/SciPostPhys.10.4.089},
	url={https://scipost.org/10.21468/SciPostPhys.10.4.089},
}

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Authors / Affiliation: mappings to Contributors and Organizations

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¹ Mathias Backes,
¹ Anja Butter,
¹ Tilman Plehn,
¹ Ramon Winterhalder

¹ Ruprecht-Karls-Universität Heidelberg / Heidelberg University

Funders for the research work leading to this publication