Conveners
Generative: Sets and Point Clouds
- Claudius Krause (Rutgers University)
-
Adam Kania (Jagiellonian University)07/11/2023, 11:00
Based on: JHEP 09 (2023) 084:
Go to contribution page
Hadronization is a critical step in the simulation of high-energy particle and nuclear physics experiments. As there is no first principles understanding of this process, physically-inspired hadronization models have a large number of parameters that are fit to data. Deep generative models are a natural replacement for classical techniques, since they are more... -
Cedric Ewen07/11/2023, 11:15
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...
Go to contribution page -
Joschka Valentin Maria Birk07/11/2023, 11:30
In this talk, we introduce a method for efficiently generating jets in the field of High Energy Physics.
Go to contribution page
Our model is designed to generate ten different types of jets, expanding the versatility of
jet generation techniques.
Beyond the kinematic features of the jet constituents, our model also excels in generating
informative features that provide insight into the types of jet constituents,... -
Simon Schnake (DESY / RWTH Aachen University)07/11/2023, 11:45
In particle physics, precise simulations of the interaction processes in calorimeters are essential for scientific discovery. However, accurate simulations using GEANT4 are computationally very expensive and pose a major challenge for the future of particle physics. In this study, we apply the CaloPointFlow model, a novel generative model based on normalizing flows, to fast and high-fidelity...
Go to contribution page -
Debajyoti Sengupta (Universite de Geneve (CH))07/11/2023, 12:00
Building on the success of PC-JeDi we introduce PC-Droid, a substantially improved diffusion model for the generation of jet particle clouds. By leveraging a new diffusion formulation, studying more recent integration solvers, and training on all jet types simultaneously, we are able to achieve state-of-the-art performance for all types of jets across all evaluation metrics. We study the...
Go to contribution page -
Mr Moritz Scham (Deutsches Elektronen-Synchrotron (DE))07/11/2023, 12:15
In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, it needs to be able to generate large point clouds in a short time while correctly modeling complex dependencies between the particles.
Go to contribution page
For non-sparse problems on a regular grid, such a model would usually use (De-)Convolution...