Embedding Tensor Network Study of the Fermi-Hubbard Model

Projected Entangled Pair States (PEPS) are a powerful tool for simulating 2D strongly correlated systems, but their applicability is often limited by high computational costs. By combining density matrix embedding theory (DMET) with finite PEPS, we are able to tackle larger system sizes. In this study, we investigate the Fermi-Hubbard model and compare our results with those from other established methods. Finally, we explore potential directions for improving this approach in future work.