TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhysCore.7.3.064
TI  - Kicking it off(-shell) with direct diffusion
PY  - 2024/09/16
UR  - https://scipost.org/SciPostPhysCore.7.3.064
JF  - SciPost Physics Core
JA  - SciPost Phys. Core
VL  - 7
IS  - 3
SP  - 064
A1  - Butter, Anja
AU  - Jezo, Tomas
AU  - Klasen, Michael
AU  - Kuschick, Mathias
AU  - Palacios Schweitzer, Sofia
AU  - Plehn, Tilman
AB  - Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We present a novel method to transform high-dimensional distributions based on a diffusion neural network and use it to generate a process with off-shell kinematics from the much simpler on-shell one. Applied to a toy example of top pair production at LO we show how our method generates off-shell configurations fast and precisely, while reproducing even challenging on-shell features.
ER  -

@Article{10.21468/SciPostPhysCore.7.3.064,
	title={{Kicking it off(-shell) with direct diffusion}},
	author={Anja Butter and Tomáš Ježo and Michael Klasen and Mathias Kuschick and Sofia Palacios Schweitzer and Tilman Plehn},
	journal={SciPost Phys. Core},
	volume={7},
	pages={064},
	year={2024},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCore.7.3.064},
	url={https://scipost.org/10.21468/SciPostPhysCore.7.3.064},
}