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Part 2<br />

Atomic Orbital Based Response Theory<br />

2.1 Introduction<br />

The first part of this thesis was concerned with the optimization of the one electron density matrix<br />

for Hartree-Fock (HF) and density-functional theory (DFT). From such an optimized density,<br />

information about excited states and how the system reacts to a perturbation (e.g. an external<br />

electric field) may be obtained using response theory. Response theory and the derivation of<br />

molecular properties will be the subject of this part of the thesis.<br />

Response theory provides a rigorous approach for calculating molecular properties. As for the SCF<br />

optimization algorithms, the theory has usually been formulated in the molecular orbital (MO) basis<br />

which is inherently delocal, making the implicated matrices non-sparse. A reformulation in the local<br />

atomic orbital (AO) basis is thus necessary to obtain linear scaling algorithms and permit<br />

calculations of properties for large systems. Such a reformulation, in which an exponential<br />

parameterization of the density matrix is employed, is given in a paper by Larsen et al. 61 .<br />

The AO formulation of the response functions has a number of advantages compared to the MO<br />

formulation, besides locality. The response equations and molecular property expressions are<br />

simpler in the AO basis as the involved matrices (e.g. the Fock and property matrices) enter the<br />

equations in the basis they are evaluated in originally. No transformation between bases is necessary<br />

in the AO formulation as it is in the MO formulation. The AO formulation is particular convenient<br />

for perturbation dependent basis sets. In the MO formulation a set of perturbation dependent<br />

orthonormal molecular orbitals must be introduced. These orbitals have no physical content and<br />

thus add artificial complexity to the problem. To exemplify the benefits of the AO formulation, the<br />

expression for the excited state geometrical gradient is derived in Section 2.4.<br />

59

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