Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We show how a generative diffusion network learns off-shell kinematics given the much simpler on-shell process. It 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”, Nov. 28, 2023, arXiv:2311.17175 (2023).


Related to Project C05