Quantum algorithms design for molecular electronic structure theory

This doctoral thesis introduces quantum computational methods for efficiently computing ground-state properties of molecular systems. The research extends electronic structure theory showing that it is possible control the quantum dynamics of a molecule to prepare its ground state. Further, we incorporated solvent effects, for the first time in quantum computational chemistry, enhancing the realism of quantum simulations in chemical environments. Additionally, the study addresses the quantum-mechanical calculation of forces within molecular systems, by using machine learning techniques such as automatic differentiation in the framework of quantum computing. A key aspect of the research involves analyzing the asymptotic scaling behavior of proposed algorithms, contributing insights for their optimization and implementation towards a scalable quantum advantage.