most citedApplying Machine Learning Methods to Laser Acceleration of Protons: Lessons Learned from Synthetic Data

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

physics.acc-ph2026

Particle tracking with physics-informed deep learning methods

Matthias Remta, Anja Beck, Shanthalakshmi Kilambi +2

Simulating the motion of charged particles in electromagnetic fields is essential for designing and optimising particle accelerators. Conventional tools rely on symplectic integrat…

physics.plasm-ph2023★ 1 cited

Applying Machine Learning Methods to Laser Acceleration of Protons: Lessons Learned from Synthetic Data

Ronak Desai, Thomas Zhang, Ricky Oropeza +6

Researchers in the field of ultra-intense laser science are beginning to embrace machine learning methods. In this study we consider three different machine learning methods -- a t…