In our diploma thesis, in which we collaborate with the Economou Group at Virginia Tech, we focus on optimizing the ADAPT-VQE algorithm, a hybrid quantum-classical approach developed for simulating molecular structures. This algorithm enables faster and more accurate calculations of molecular properties compared to conventional methods. Such simulations are crucial for advancing quantum chemistry, with potential applications in drug discovery, materials science, and energy research.

Project publications:

1. Strategies for Overcoming Gradient Troughs in the ADAPT-VQE Algorithm

I lead a student research project developing new optical media that can be efficiently pumped by polychromatic light. Conventional laser materials lose efficiency under broadband excitation, so I now focus on designing a medium with a wide absorption band. As lead scientist and developer I built an automated pipeline that combines quantum-chemical simulation with machine learning to screen and optimise molecular structures. Our results indicate that targeted modifications of molecular mechanics offer a really promising route to substantially higher laser efficiency under broadband pumping. If realised in hardware, these materials could improve medical lasers, materials processing, spectroscopy and optical communications.