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Title: Fast point cloud generation with diffusion models in high energy physics

Journal Article · · Physical Review. D.
ORCiD logo [1]; ORCiD logo [2];  [3]
  1. National Energy Research Scientific Computing Center, Berkeley, CA (United States)
  2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)
  3. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Many particle physics datasets like those generated at colliders are described by continuous coordinates (in contrast to grid points like in an image), respect a number of symmetries (like permutation invariance), and have a stochastic dimensionality. For this reason, standard deep generative models that produce images or at least a fixed set of features are limiting. We introduce a new neural network simulation based on a diffusion model that addresses these limitations named fast point cloud diffusion. We show that our approach can reproduce the complex properties of hadronic jets from proton-proton collisions with competitive precision to other recently proposed models. Additionally, we use a procedure called progressive distillation to accelerate the generation time of our method, which is typically a significant challenge for diffusion models despite their state-of-the-art precision.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP); National Energy Research Scientific Computing (NERSC); USDOE
Grant/Contract Number:
AC02-05CH11231; HEP-ERCAP0021099
OSTI ID:
1997043
Alternate ID(s):
OSTI ID: 2323436
Journal Information:
Physical Review. D., Vol. 108, Issue 3; ISSN 2470-0010
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English

References (26)

The anti- k t jet clustering algorithm journal April 2008
Controlling Physical Attributes in GAN-Accelerated Simulation of Electromagnetic Calorimeters journal September 2018
JUNIPR: a framework for unsupervised machine learning in particle physics journal February 2019
Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network journal January 2019
DCTRGAN: improving the precision of generative models with reweighting journal November 2020
CaloGAN: Simulating 3D high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks journal January 2018
Deep learning as a parton shower journal December 2018
Three dimensional Generative Adversarial Networks for fast simulation journal September 2018
Hadrons, better, faster, stronger journal June 2022
Jet-images — deep learning edition journal July 2016
Fast simulation of a high granularity calorimeter by generative adversarial networks journal April 2022
GAN with an Auxiliary Regressor for the Fast Simulation of the Electromagnetic Calorimeter Response journal February 2023
AtlFast3: The Next Generation of Fast Simulation in ATLAS journal March 2022
Event Generation and Density Estimation with Surjective Normalizing Flows journal September 2022
Jet-images: computer vision inspired techniques for jet tagging journal February 2015
Energy flow polynomials: a complete linear basis for jet substructure journal April 2018
Calorimetry with deep learning: particle simulation and reconstruction for collider physics journal July 2020
Accelerating accurate simulations of calorimeter showers with normalizing flows and probability density distillation journal June 2023
Fast and accurate simulations of calorimeter showers with normalizing flows journal June 2023
Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis journal September 2017
Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed journal May 2021
Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multilayer Calorimeters journal January 2018
Score-based generative models for calorimeter shower simulation journal November 2022
Decoding Photons: Physics in the Latent Space of a BIB-AE Generative Network journal January 2021
Machine learning and LHC event generation journal April 2023
Calomplification — the power of generative calorimeter models journal September 2022