10-15 March 2019
Steinmatte conference center
Europe/Zurich timezone

Recurrent GANs for particle-based simulation at the LHC

12 Mar 2019, 16:10
Steinmatte Room A

Steinmatte Room A

Oral Track 2: Data Analysis - Algorithms and Tools Track 2: Data Analysis - Algorithms and Tools


Thong Nguyen (California Institute of Technology (US))


Generative models, and in particular generative adversarial networks, are gaining momentum in hep as a possible way to speed up the event simulation process. Traditionally, gan models applied to hep are designed to return images. On the other hand, many applications (e.g., analyses based on particle flow) are designed to take as input lists of particles. We investigate the possibility of using recurrent GANs as a generator of particle lists. We discuss a prototype implementation, challenges and limitations in the context of specific applications.

Primary authors

Dr Jean-Roch Vlimant (California Institute of Technology (US)) Maurizio Pierini (CERN) Jesus Arjona Martinez (California Institute of Technology (US)) Prof. Maria Spiropulu (California Institute of Technology) Thong Nguyen (California Institute of Technology (US))

Presentation materials

Peer reviewing