Abstract
We introduce a new procedure for iterative selection of determinant spaces capable of describing highly correlated systems. This adaptive configuration interaction (ACI) determines an optimal basis by an iterative procedure in which the determinant space is expanded and coarse grained until self consistency. Two importance criteria control the selection process and tune the ACI to a user-defined level of accuracy. The ACI is shown to yield potential energy curves of N with nearly constant errors, and it predicts singlet-triplet splittings of acenes up to decacene that are in good agreement with the density matrix renormalization group.
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