PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
- URL: http://arxiv.org/abs/2303.05376v2
- Date: Wed, 21 Feb 2024 13:38:39 GMT
- Title: PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
- Authors: Matthew Leigh, Debajyoti Sengupta, Guillaume Qu\'etant, John Andrew
Raine, Knut Zoch, and Tobias Golling
- Abstract summary: We present a new method to efficiently generate jets in High Energy Physics called PC-JeDi.
This method uses score-based diffusion models in conjunction with transformers which are well suited to the task of generating jets as particle clouds.
PC-JeDi achieves competitive performance with current state-of-the-art methods across several metrics that evaluate the quality of the generated jets.
- Score: 0.8246494848934447
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In this paper, we present a new method to efficiently generate jets in High
Energy Physics called PC-JeDi. This method utilises score-based diffusion
models in conjunction with transformers which are well suited to the task of
generating jets as particle clouds due to their permutation equivariance.
PC-JeDi achieves competitive performance with current state-of-the-art methods
across several metrics that evaluate the quality of the generated jets.
Although slower than other models, due to the large number of forward passes
required by diffusion models, it is still substantially faster than traditional
detailed simulation. Furthermore, PC-JeDi uses conditional generation to
produce jets with a desired mass and transverse momentum for two different
particles, top quarks and gluons.
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