Speaker
Cedric Ewen
Description
We introduce two novel techniques for the efficient generation of jets as low-level particle clouds. Firstly, we present EPiC-JeDi, which integrates the score-based diffusion model from PC-JeDI with the fast and computationally efficient equivariant point cloud (EPiC) layers used in the EPiC-GAN. Secondly, we introduce EPiC-FM, which shares the same architecture but employs a continuous normalizing flow approach trained using optimal transport flow matching (FM). Our models not only achieve competitive performance compared to the current state-of-the-art methods in terms of various metrics assessing the quality of generated jets but also maintain rapid generation speeds.
Primary authors
Cedric Ewen
Darius Faroughy
(University of Zurich)
David Shih
Debajyoti Sengupta
(Universite de Geneve (CH))
Erik Buhmann
(Hamburg University (DE))
Gregor Kasieczka
(Hamburg University (DE))
Guillaume Quétant
(Universite de Geneve (CH))
Johnny Raine
(Universite de Geneve (CH))
Mr
Matthew Leigh
(University of Geneva)
Tobias Golling
(Universite de Geneve (CH))
