12 citations · 12 across the 4 of their papers we have counts for
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cDVAE: Multimodal Generative Conditional Diffusion Guided by Variational Autoencoder Latent Embedding for Virtual 6D Phase Space Diagnostics
Alexander Scheinker
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 an…
Conditional Guided Generative Diffusion for Particle Accelerator Beam Diagnostics
Alexander Scheinker
Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coheren…
Towards latent space evolution of spatiotemporal dynamics of six-dimensional phase space of charged particle beams
Mahindra Rautela, Alan Williams, Alexander Scheinker
Addressing the charged particle beam diagnostics in accelerators poses a formidable challenge, demanding high-fidelity simulations in limited computational time. Machine learning (…
Accelerator system parameter estimation using variational autoencoded latent regression
Mahindra Rautela, Alan Williams, Alexander Scheinker
Particle accelerators are time-varying systems whose components are perturbed by external disturbances. Tuning accelerators can be a time-consuming process involving manual adjustm…
A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
Mahindra Rautela, Alan Williams, Alexander Scheinker
Particle accelerators are complex systems that focus, guide, and accelerate intense charged particle beams to high energy. Beam diagnostics present a challenging problem due to lim…
Experimental Safe Extremum Seeking for Accelerators
Alan Williams, Alexander Scheinker, En-Chuan Huang +2
We demonstrate the recent designs of Safe Extremum Seeking (Safe ES) on the 1 kilometer-long charged particle accelerator at the Los Alamos Neutron Science Center (LANSCE). Safe ES…