The Hamiltonian Variational Ansatz (HVA) is among the promising approaches for lattice model Hamiltonians. We employ the HVA for the Fermi-Hubbard Hamiltonian[1].
For VQE optimization, we selected Rotosolve and Rotoselect[2]. These optimizers leverage the analytical properties of the objective function landscape and are gradient-free.
[1] 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.
[2] Ostaszewski, M., Grant, E., & Benedetti, M. Structure optimization for parameterized quantum circuits.
Team name:
itscreek
Team members:
Itsuki Urakawa
Project Description:
The Hamiltonian Variational Ansatz (HVA) is among the promising approaches for lattice model Hamiltonians. We employ the HVA for the Fermi-Hubbard Hamiltonian[1].
For VQE optimization, we selected Rotosolve and Rotoselect[2]. These optimizers leverage the analytical properties of the objective function landscape and are gradient-free.
[1] 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. [2] Ostaszewski, M., Grant, E., & Benedetti, M. Structure optimization for parameterized quantum circuits.
Presentation:
https://drive.google.com/file/d/1ece_QWPpEZ86YCfEiaKjObOsmcXfi10S/view?usp=sharing
Source code:
https://github.com/itscreek/quantum-algorithm-grand-challenge-2024/blob/main/problem/answer.py
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