Kicking it off(-shell) with direct diffusion

Abstract:

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.

A. Butter, T. Jezo, M. Klasen, M. Kuschick, S. P. Schweitzer, T. Plehn, „Kicking it off(-shell)
with direct diffusion“, SciPost Phys. Core 7, 064 (2024).

https://scipost.org/10.21468/SciPostPhysCore.7.3.064

Related to Project C05