Optimization of quantum algorithms for near-term quantum computers

Bonet Monroig, X. (2022)

Doctoral Thesis

This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science. These aspects range from error mitigation and error modeling of a quantum computing device to a measurement scheduling to extract the relevant information of a quantum state for quantum chemistry calculations.
It also presents a benchmarking study of classical optimization methods for variational quantum algorithms. Additionally, a small quantum simulation is performed on a cloud-based quantum computer to understand the bottlenecks of such infrastructure. Finally, a method to calculate energy derivatives on a quantum computer, a relevant figure for quantum chemistry calculations.

• Quantum computing
• Variational quantum algorithms
• Quantum state tomography
• Optimization algorithms

• All authors: Bonet Monroig, X.
• Supervisor: Beenakker, C.W.J.
• Co-supervisor: O'Brien, T.E.
• Committee: Montanaro, A.; Visscher, L.; Aarts, J.; Achúcarro, A.; Tura i Brugués, J.
• Qualification: Doctor (dr.)
• Awarding Institution: Leiden Institute of Physics (LION), Faculty of Science, Leiden University
• Date: 2022-11-02
• Title of host publication: Casimir PhD Series
• ISBN (print): 9789085935414
• Name: 2022-31