Simulation of Hadronic Interactions with Deep Generative Models Article Swipe
Tuan Minh Pham
,
X. Ju
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2310.07553
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2310.07553
Accurate simulation of detector responses to hadrons is paramount for all physics programs at the Large Hadron Collider (LHC). Central to this simulation is the modeling of hadronic interactions. Unfortunately, the absence of first-principle theoretical guidance has made this a formidable challenge. The state-of-the-art simulation tool, \textsc{Geant4}, currently relies on phenomenology-inspired parametric models. Each model is designed to simulate hadronic interactions within specific energy ranges and for particular types of hadrons. Despite dedicated tuning efforts, these models sometimes fail to describe the data in certain physics processes accurately. Furthermore, fine-tuning these models with new measurements is laborious. Our research endeavors to leverage generative models to simulate hadronic interactions. While our ultimate goal is to train a generative model using experimental data, we have taken a crucial step by training conditional normalizing flow models with \textsc{Geant4} simulation data. Our work marks a significant stride toward developing a fully differentiable and data-driven model for hadronic interactions in High Energy and Nuclear Physics.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2310.07553
- https://arxiv.org/pdf/2310.07553
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387596481
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387596481Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2310.07553Digital Object Identifier
- Title
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Simulation of Hadronic Interactions with Deep Generative ModelsWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-10-11Full publication date if available
- Authors
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Tuan Minh Pham, X. JuList of authors in order
- Landing page
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https://arxiv.org/abs/2310.07553Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2310.07553Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2310.07553Direct OA link when available
- Concepts
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Hadron, Physics, Phenomenology (philosophy), Particle physics, Large Hadron Collider, Leverage (statistics), Parametric statistics, Statistical physics, Computer science, Artificial intelligence, Epistemology, Statistics, Mathematics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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