We introduce the subspace density matrix functional embedding theory (sDMFET), in which optimization of the nonlocal embedding potential and subsequent embedded correlated wave function calculations are carried out within a truncated subspace determined by a Schmidt decomposition. As compared to the original density matrix functional embedding theory [K. Yu and E. A. Carter, Proceedings of the National Academy of Sciences 2017, 114, E10861 ], the computational cost of sDMFET is significantly reduced while the accuracy is preserved. We perform test calculations for both covalently and noncovalently bound molecular systems to demonstrate the feasibility of our theory.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Physical and Theoretical Chemistry