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Published March 28, 2012 | Published + Accepted Version + Supplemental Material
Journal Article Open

Spin-adapted density matrix renormalization group algorithms for quantum chemistry


We extend the spin-adapted density matrix renormalization group (DMRG) algorithm of McCulloch and Gulacsi [Europhys. Lett. 57, 852 (2002)]10.1209/epl/i2002-00393-0 to quantum chemical Hamiltonians. This involves using a quasi-density matrix, to ensure that the renormalized DMRG states are eigenfunctions of Ŝ^2, and the Wigner-Eckart theorem, to reduce overall storage and computational costs. We argue that the spin-adapted DMRG algorithm is most advantageous for low spin states. Consequently, we also implement a singlet-embedding strategy due to Tatsuaki [Phys. Rev. E 61, 3199 (2000)]10.1103/PhysRevE.61.3199 where we target high spin states as a component of a larger fictitious singlet system. Finally, we present an efficient algorithm to calculate one- and two-body reduced density matrices from the spin-adapted wavefunctions. We evaluate our developments with benchmark calculations on transition metal system active space models. These include the Fe_2S_2, [Fe_2S_2(SCH_3)_4]^(2−), and Cr_2 systems. In the case of Fe_2S_2, the spin-ladder spacing is on the microHartree scale, and here we show that we can target such very closely spaced states. In [Fe_2S_2(SCH_3)_4]^(2−), we calculate particle and spin correlation functions, to examine the role of sulfur bridging orbitals in the electronic structure. In Cr_2 we demonstrate that spin-adaptation with the Wigner-Eckart theorem and using singlet embedding can yield up to an order of magnitude increase in computational efficiency. Overall, these calculations demonstrate the potential of using spin-adaptation to extend the range of DMRG calculations in complex transition metal problems.

Additional Information

© 2012 American Institute of Physics. Received 16 August 2011; accepted 2 March 2012; published online 30 March 2012. This work was supported by the National Science Foundation (NSF) through Grant No. NSF-CHE-0645380.

Attached Files

Supplemental Material - 043212jcp_epaps.docx

Published - 1_2E3695642.pdf

Accepted Version - 1408.5039.pdf


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August 19, 2023
August 19, 2023