A spin-adapted Density Matrix Renormalization Group algorithm for quantum chemistry
Abstract
We extend the spin-adapted density matrix renormalization group (DMRG) algorithm of McCulloch and Gulacsi [Europhys. Lett.57, 852 (2002)] to quantum chemical Hamiltonians. This involves two key modifications to the non-spin-adapted DMRG algorithm: the use of a quasi-density matrix to ensure that the renormalised DMRG states are eigenvalues of , and the use of the Wigner-Eckart theorem to greatly reduce the overall storage and computational cost. We argue that the advantages of the spin-adapted DMRG algorithm are greatest for low spin states. Consequently, we also implement the singlet-embedding strategy of Nishino et al [Phys. Rev. E61, 3199 (2000)] which allows us to target high spin states as a component of a mixed system which is overall held in a singlet state. We evaluate our algorithm on benchmark calculations on the FeS and Cr transition metal systems. By calculating the full spin ladder of FeS , we show that the spin-adapted DMRG algorithm can target very closely spaced spin states. In addition, our calculations of Cr demonstrate that the spin-adapted algorithm requires only roughly half the number of renormalised DMRG states as the non-spin-adapted algorithm to obtain the same accuracy in the energy, thus yielding up to an order of magnitude increase in computational efficiency.
Cite
@article{arxiv.1408.5039,
title = {A spin-adapted Density Matrix Renormalization Group algorithm for quantum chemistry},
author = {Sandeep Sharma and Garnet Kin-Lic Chan},
journal= {arXiv preprint arXiv:1408.5039},
year = {2014}
}