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Physical Review Accelerators and Beams

Articles Citing

Latent diffusion can map beam loss to two-dimensional phase-space projections

Alexander Scheinker* and Alan Williams

  • *Contact author: ascheink@lanl.gov

Physics-informed deep generative model for longitudinal phase space reconstruction during beam merging at HIAF

Xiangwen Qiao, Jiancheng Yang, Guimei Ma, Jie Liu, Fucheng Cai, Zhongtian She, Liping Yao, Liangzhou Yao, Yunpeng Zhu, and Jiangdong Li

Nuclear Engineering and Technology 59 104788 (2027)

Machine-state embeddings as an operational reference space for accelerator operation

Chris Tennant, Jundong Li, and Song Wang

Phys. Rev. Accel. Beams 29 105101 (2026)

Conditional Latent Diffusion for High-Resolution Prediction of Electrochemical Surface Morphology

Alexander Scheinker, Michael McBride, Nathan Brown, Alex Mirabal, Reeju Pokharel, and Daniel E. Hooks

J. Electrochem. Soc. 173 022502 (2026)

Adaptive Control Meets Deep Learning: EXTREMUM SEEKING IN LATENT SPACE WITH PARTICLE ACCELERATOR APPLICATIONS

Alexander Scheinker

IEEE Control Syst. 46 150 (2026)

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Alexander Scheinker

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