Physics-informed genetic algorithm for the beam dynamics design and optimization of RFQ

It is widely used in various fields, including nuclear energy, medical applications, industry, and fundamental physics research. The beam dynamics design of RFQ involves numerous coupled parameters, nonlinear physical constraints, and complex engineering limitations, while facing multi-objective optimization conflicts such as transmission efficiency, structural compactness, and emittance control.

Traditional design methods struggle to achieve a globally optimal solution within a reasonable computational time. To address this issue, this study proposes a beam dynamics-related physics-informed genetic algorithm. By introducing evolution rules for key physical parameters such as modulation, synchronous phase, and focusing strength during individual initialization, evolution guidance, and solution selection, the physical validity and optimization efficiency of the solutions are significantly improved.