The algorithm uses a low-depth variational quantum algorithm based on the Hamiltonian variational ansatz and the variational quantum eigensolver (VQE). The algorithm optimises over quantum circuits, where the number of ansatz layers scales with the number of sites.
Stanisic, S., Bosse, J.L., Gambetta, F.M. et al. Observing ground-state properties of the Fermi-Hubbard model using a scalable algorithm on a quantum computer. Nat Commun 13, 5743 (2022). https://doi.org/10.1038/s41467-022-33335-4
Team name:
qumonkey
Team members:
Kazuki Matsumoto Srijan Srivastava
Project Description:
The algorithm uses a low-depth variational quantum algorithm based on the Hamiltonian variational ansatz and the variational quantum eigensolver (VQE). The algorithm optimises over quantum circuits, where the number of ansatz layers scales with the number of sites.
Presentation:
https://github.com/kazuki-matsumoto/QAGC_qumonkey/blob/main/QAGC_submission.pdf
Source code:
https://github.com/kazuki-matsumoto/QAGC_qumonkey/blob/main/problem/answer.py
Reference
Stanisic, S., Bosse, J.L., Gambetta, F.M. et al. Observing ground-state properties of the Fermi-Hubbard model using a scalable algorithm on a quantum computer. Nat Commun 13, 5743 (2022). https://doi.org/10.1038/s41467-022-33335-4