Quantum computing innovation to stimulate quantum systems

The emerging technology of quantum computing promises a revolution in numerical simulations of quantum systems for which classical algorithms suffer from computational costs that scale exponentially with the system size. This project will develop and optimize innovative quantum computing techniques to simulate small quantum systems using this rapidly evolving technology.

The project will begin by using existing noisy intermediate-scale quantum (NISQ) devices to simulate small physical systems, such as the lattice-regularized Wess-Zumino model - a supersymmetric quantum field theory that can exhibit spontaneous supersymmetry breaking. As part of this work, you will investigate the capabilities of a variety of NISQ devices, including systems based on binary qubits, d-state qudits, or continuous-variable qumodes, as well as the possibility of hybrid devices.

In the next stage of the project you will develop customized error mitigation techniques to optimize the performance of the most promising of these devices. In addition to maximizing the capabilities of existing devices, through this work you may also contribute to the co-design of future quantum hardware. Depending on the progress of the technology, it may also be possible to incorporate simple quantum error correction into certain aspects of this work.

Throughout the project you will benefit from comprehensive postgraduate training in theoretical physics as a member of the University of Liverpool's Department of Mathematical Sciences. There may be opportunities to collaborate with other quantum computing researchers in Europe, Japan, and the United States. You will additionally receive training in research skills and techniques, project management, networking, and communication as part of a cohort within the 'Liv.Inno' Centre for Doctoral Training for Innovation in Data Intensive Science.

This project will be carried out over 48 months starting in October 2024, including a mandatory 6-month industrial placement that will broaden your research skills and career opportunities. This position will be funded by the Liv.Inno Centre for Doctoral Training and the Science and Technology Facilities Council.