Integrating artificial intelligence into the simulation of structured laser-driven high harmonic generation

High harmonic generation (HHG) stands as one of the most complex processes in strong-field physics, as it enables the conversion of laser light from the infrared to the extreme-ultraviolet or even the soft x-rays, enabling the synthesis and control of pulses lasting as short as tens of attoseconds. Accurately simulating this nonlinear and non-perturbative phenomena requires the coupling the dynamics of laser-driven electronic wavepackets, described by the three-dimensional time-dependent Schrödinger equation (3D-TDSE), with macroscopic Maxwell’s equations. Such calculations are extremely demanding due to the duality of microscopic and macroscopic nature of the process, thereby requiring the use of approximations. We develop a HHG method assisted by artificial intelligence that facilitates the simulation of macroscopic HHG within the framework of 3D-TDSE. This approach is particularly suited to simulate HHG driven by structured laser pulses. In particular, we demonstrate a self-interference effect in HHG driven by Hermite-Gauss beams. The theoretical and experimental agreement allows us to validate the AI-based model, and to identify a unique signature of the quantum nature of the HHG process.