Particle Accelerators and Free-Electron Lasers

Neueste Paper

• RL-ABC: Reinforcement Learning for Accelerator Beamline Control

  Anwar Ibrahim, Fedor Ratnikov, Maxim Kaledin, Alexey Petrenko, Denis Derkach · 22. April 2026

  Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLABC (Reinforcement Learning for Accelerator Beamline Control), an open-source Python framework that automatically transforms standard Elegant beamlin…

• H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMs

  Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang, Sihao Hu, Yichang Xu, Zachary Yahn, Ling Liu · 22. Januar 2026

  The alignment of pre-trained LLMs continues to draw significant attention from both industry and academia, aiming to ensure responses that are helpful, harmless, and honest. However, identifying a point in the model's representation subspace that simultaneously satisfies all these properties remains…

• Efficient Dynamic and Momentum Aperture Optimization for Lattice Design Using Multipoint Bayesian Algorithm Execution

  Z. Zhang, I. Agapov, S. Gasiorowski, T. Hellert, W. Neiswanger, X. Huang, D. Ratner · 25. November 2025

  We demonstrate that multipoint Bayesian algorithm execution can overcome fundamental computational challenges in storage ring design optimization. Dynamic (DA) and momentum (MA) optimization is a multipoint, multiobjective design task for storage rings, ultimately informing the flux of x-ray sources…