Sprecher
Beschreibung
Peking University is developing a proton radiotherapy system based on a petawatt-class laser accelerator (Compact laser plasma accelerator-II, CLAPA-II). Given the ultrashort pulse duration of laser-accelerated proton beams, the dose rate per pulse can reach up to billions of grays per second. This gives laser proton radiotherapy systems unique advantages in FLASH radiotherapy for malignant tumors, which requires dose rates exceeding 40 Gy/s. However, for a medical accelerator, the stability and controllability of the proton beam are very strict. Acting as the nervous system of the entire apparatus, the control system is crucial for ensuring reliability, stability, and overall efficiency. It must also meet both technical and medical standards, making the development process quite challenging. To this end, we have applied artificial intelligence algorithms to optimize the performance of the CLAPA-II, including automatic correction of target position, automatic optimization of beam envelopes along the beamline system, enhancement of the function of the safety interlocks, and accuracy dose irradiation in the case of unstable beam flow. Results have validated that relevant AI algorithms are effective tools for enhancing the operational efficiency and stability of the laser accelerator.
