4 papers
Flow-based surrogate models for particle tracking
Matthias Remta, Yann Dutheil, Francesco Velotti
Particle tracking is a fundamental tool for particle-accelerator design and optimisation. Conventional tracking routines provide high accuracy but are computationally demanding, es…
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…
Proof-of-principle experiment of a novel beam extraction over millions of turns using stable resonance islands and bent crystal
D. E. Veres, P. Arrutia, S. Cettour Cave +6
A recent study [1] has introduced an advanced method aimed at extracting from a circular particle accelerator over millions of turns using stable islands and a bent crystal. This t…
Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization
Francisco Huhn, Francesco M. Velotti
Optimization of beamlines and lattices is a common problem in accelerator physics, which is usually solved with semi-analytical methods and numerical optimization routines. However…