Density matrix embedding theory (DMET) is a quantum embedding theory for strongly correlated systems. From a computational perspective, one bottleneck in DMET is the optimization of the correlation potential to achieve self-consistency, especially for heterogeneous systems of large size. Two methods will be presented to reduce the computational cost. We demonstrate the performance of two methods on the 2D Hubbard model and 3D Hydrogen chain models.
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