Ultra-short, high-energy (up to few GeVs) electron beams can be accelerated over just a few centimeters by making an ultra-intense laser interact with a gas-jet, with a technique called “Laser Wakefield Acceleration” (LWFA). Thanks to their small size and the ultra-short duration of the accelerated electron beams, these devices are potentially interesting for a variety of scientific and technological applications. However, LWFA accelerators do not usually provide enough charge for most of the envisaged applications, in particular if a high beam quality and a high electron energy are also required.
The first goal of this thesis is to understand the basic physics of a novel LWFA injector concept recently conceived in our group. This injector consists of a solid target coupled with a gas-jet, and should be able to accelerate a substantially higher amount of charge with respect to conventional strategies, while preserving at the same time the quality of the beam. Large scale numerical simulation campaigns and machine learning techniques will be used to optimize the properties of the accelerated electrons. The interaction of these electron beams with various samples will be simulated with Monte Carlo code to assess their potential for applications such as Muon Tomography and radiobiology/radiotherapy. The proposed activity is essentially numerical, but with the possibility to be involved in the experimental activities of the team.
The PhD student will have the opportunity to be part of a dynamic team with strong national and international collaborations. They will also acquire the necessary skills to participate in laser-plasma interaction experiments in international facilities. Finally, they will acquire the required skills to contribute to the development of a complex software written in modern C++ and designed to run efficiently on the most powerful supercomputers in the world: the state-of-the-art Particle-In-Cell code WarpX (prix Gordon Bell en 2022). The development activity will be carried out in collaboration with the team led by Dr. J.-L. Vay at LBNL (US), where the candidate could have the opportunity to spend a few months during the thesis.