cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics

Abstract Imaging the 6D phase space of a beam in a particle accelerator in a single shot is currently impossible. Single shot beam measurements only exist for certain 2D beam projections and these methods are destructive. A virtual diagnostic that can generate an accurate prediction of a beam’s 6D p...

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Main Author: Alexander Scheinker
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-80751-1
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author Alexander Scheinker
author_facet Alexander Scheinker
author_sort Alexander Scheinker
collection DOAJ
description Abstract Imaging the 6D phase space of a beam in a particle accelerator in a single shot is currently impossible. Single shot beam measurements only exist for certain 2D beam projections and these methods are destructive. A virtual diagnostic that can generate an accurate prediction of a beam’s 6D phase space would be incredibly useful for precisely controlling the beam. In this work, a generative conditional diffusion- based approach to creating a virtual diagnostic of all 15 unique 2D projections of a beam’s 6D phase space is developed. The diffusion process is guided by a combination of scalar parameters and images that are converted to low-dimensional latent vector representation by a variational autoencoder (VAE). We demonstrate that conditional diffusion guided by a VAE (cDVAE) can accurately reconstruct all 15 of the unique 2D projections of a charged particle beam’s 6D phase space for the HiRES compact accelerator.
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spelling doaj-art-a2e5a96d19f3437e98dd8e4d12107afb2025-08-20T02:49:17ZengNature PortfolioScientific Reports2045-23222024-11-0114111610.1038/s41598-024-80751-1cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnosticsAlexander Scheinker0Applied Electrodynamics Group, Los Alamos National LaboratoryAbstract Imaging the 6D phase space of a beam in a particle accelerator in a single shot is currently impossible. Single shot beam measurements only exist for certain 2D beam projections and these methods are destructive. A virtual diagnostic that can generate an accurate prediction of a beam’s 6D phase space would be incredibly useful for precisely controlling the beam. In this work, a generative conditional diffusion- based approach to creating a virtual diagnostic of all 15 unique 2D projections of a beam’s 6D phase space is developed. The diffusion process is guided by a combination of scalar parameters and images that are converted to low-dimensional latent vector representation by a variational autoencoder (VAE). We demonstrate that conditional diffusion guided by a VAE (cDVAE) can accurately reconstruct all 15 of the unique 2D projections of a charged particle beam’s 6D phase space for the HiRES compact accelerator.https://doi.org/10.1038/s41598-024-80751-1
spellingShingle Alexander Scheinker
cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
Scientific Reports
title cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
title_full cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
title_fullStr cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
title_full_unstemmed cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
title_short cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
title_sort cdvae vae guided diffusion for particle accelerator beam 6d phase space projection diagnostics
url https://doi.org/10.1038/s41598-024-80751-1
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