2023 Student Research Conference:
36th Annual Student Research Conference

Reviewing Scalable Algorithms for Quantum Computers to Analyse Ground-State Properties of the Fermi-Hubbard Model


Ben F. Cramer
Dr. Rasanjali Jayathissa, Faculty Mentor

The Fermi-Hubbard model is an approximation that describes the transition between conducting and insulating systems that has yet to be truly solved. It has become a famous problem for quantum computers, as its solution could lead to more efficient construction and operation of solar panels and batteries. We have reviewed and analyzed experiments attempting to represent the Fermi-Hubbard ground state solutions in medium-sized instances. We compared their data to the theoretical model in order to determine their accuracy. We also examined their experimental setups to determine whether they are able to be scaled up for higher-sized instances of the Fermi-Hubbard ground state. Our analysis showed that these experiments’ processes are sound and that the quantum algorithms used are likely scalable for larger quantum systems in the future.

Keywords: Quantum Computing, Quantum Mechanics, Solar Panels, Fermi-Hubbard Model

Topic(s):Physics
Computer Science

Presentation Type: Oral Presentation

Session: 110-5
Location: MG 1096
Time: 9:30

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