Strategies for solving the Fermi-Hubbard model on near-term quantum computers

Understand

The Fermi-Hubbard model is of fundamental importance in condensed-matter physics, yet is extremely challenging to solve numerically.

• Finding the ground state of the Hubbard model using variational methods has been predicted to be one of the first applications of near-term quantum computers.
• Here we carry out a detailed analysis and optimisation of the complexity of variational quantum algorithms for finding the ground state of the Hubbard model, including costs associated with mapping to a real-world hardware platform.
• The depth complexities we find are substantially lower than previous work.