Speaker
Description
Designing and optimizing target structures is one of the most critical steps in high-intensity laser experiments, like laser-driven neutron sources, which are increasingly recognized for their compactness and portability. Here, we propose an AI-assisted target design approach that leverages artificial intelligence algorithms in combination with particle-in-cell (PIC) simulations. This newly AI-optimized structure addresses the limitations of conventional approaches, such as foam targets or wire-array structures. Simulation results demonstrate a neutron yield exceeding 3 orders of magnitude compared to flat targets and over 18 times greater than that of wire-array targets. This dramatic result demonstrates that the AI-assisted target design method could be effectively applied to other high-intensity laser applications.
