Speaker
Description
High-intensity fixed-field alternating-gradient accelerators pose challenges for beam dynamics simulation due to their strongly nonlinear magnetic fields, energy-dependent closed orbits, and space-charge effects. These characteristics complicate the modeling of particle trajectories and collective beam dynamics during injection, acceleration, and extraction.
This presentation introduces a Python-based beam dynamics simulation framework developed to address these challenges. The framework supports particle tracking in nonlinear magnetic fields and incorporates a 2.5D space-charge model based on dynamically reconstructed local coordinate frames, enabling simulations of longitudinally extended beams along curved, energy-dependent reference trajectories. It also provides tools for studying multi-turn injection, transverse phase-space painting, beam accumulation, and extraction trajectories.
Parallel computing is employed for multi-particle simulations and parameter studies. Future developments include GPU acceleration for particle tracking and space-charge calculations, along with automated simulation workflows and artificial intelligence-assisted parameter optimization. Representative simulation results will be presented to illustrate the framework's capabilities.
