Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,…,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0≡{T0egy,T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates Ks with attributes above T1⩽T0. An eigenproblem of dimension d0+d1 for S0+S1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j⩾2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson’s eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0,1,2,…,R} regulate accuracy; for large-dimensional S, high accuracy requires S0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24×106, involving 1.2×1012 nonzero matrix elements, and 8.4×109 Slater determinants.