Quantum Simulations of Laser-Induced Electron Diffraction using Recurrent Neural Networks

DASHH Doctoral Researcher: Álvaro Fernández

Supervisors: Prof. Jochen Küpper (DESY, UHH), Dr. Andrey Yachmenev (DESY), Prof. Armin Iske (UHH)

Strong-field ionisation is a powerful tool to visualise and control chemical and biological structural changes. Accurate quantum-mechanical simulations of strong field ionisation processes help analyse observations and often provide the only way to retrieve molecular structure from such experiments. The existing theoretical models are computationally expensive and limited to calculations of relatively small electron excursions, making it impossible to simulate the laser-induced self-diffraction imaging experiments. The goal of this project is to develop a computationally tractable paradigm of laser-induced strong-field ionisation that is accurate enough to retrieve structural information from experimental observations. The method development will rely on physics informed neural network approaches for both classical trajectory simulations and time-dependent Schrödinger equation solutions.