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Conical coil focusing of laser-plasma accelerated proton beams for applications
Phys. Rev. Accel. Beams 28, 114701 – Published 24 November, 2025
DOI: https://doi.org/10.1103/656n-827p
Abstract
Laser-driven ion beams offer significant advantages over radio-frequency accelerated beams, making them particularly promising for biomedical applications. Key features include their ultrashort pulse duration, on the order of picoseconds, and high peak fluxes ranging from to particles per shot. These characteristics enable the delivery of ultrahigh dose rates, potentially reaching the FLASH therapy regime. The future implementation of laser-driven ion beams in clinical settings relies on the development of advanced focusing and beam transport systems capable of precisely controlling parameters such as energy range, beam focus, and dose distribution to meet stringent therapeutic requirements. However, the integration of ultrashort laser-driven ion beams into medical treatments presents challenges, particularly due to their broad energy spectrum and high angular divergence. We present 3D simulation-based studies investigating the focusing effects of different high-current solenoid configurations on laser-plasma-accelerated proton beams. To identify the optimal focusing solution, we designed, analyzed, and compared high-current solenoids of varying dimensions and shapes, both as stand-alone magnetic elements and as part of two-solenoid focusing systems. Our analysis focuses on magnetic fields between 6 and 9 T, generated by the high-current solenoids. The study considers a proton beam with an energy range from a few MeV to 20 MeV and an initial divergence of 21°. Results are evaluated in terms of collection efficiency, beam focusing position, and beam profile. The optimized beamline configuration was then used to assess the dose distribution in a cylindrical water target with a volume of by calculating the absorbed dose and dose delivery rates, demonstrating the potential of laser-plasma-accelerated proton beams for radiotherapy applications.
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