Equation-of-motion orbital-optimized coupled-cluster doubles method with the density-fitting approximation: An...

Area of Science:

• Quantum Chemistry
• Computational Chemistry
• Theoretical Chemistry

Background:

• Orbital-optimized coupled-cluster (OCC) methods are crucial for accurately predicting molecular properties, especially excited states in complex systems.
• Accurate theoretical predictions of excited states are vital for understanding photochemistry and photophysics.

Purpose of the Study:

• To present an efficient implementation of the equation-of-motion orbital-optimized coupled-cluster doubles (EOM-OCCD) method using the density-fitting (DF) approach, termed DF-EOM-OCCD.
• To evaluate the computational performance of DF-EOM-OCCD for calculating excitation energies compared to the conventional EOM-OCCD method.

Main Methods:

• Implementation of the equation-of-motion orbital-optimized coupled-cluster doubles (EOM-OCCD) method incorporating the density-fitting (DF) approximation.
• Comparison of computational costs and accuracy for excitation energies between the conventional EOM-OCCD and the new DF-EOM-OCCD methods.
• Application to challenging chemical systems, including the $$ molecule and open-shell systems, using the aug-cc-pVTZ basis set and RHF reference.

Main Results:

• The DF-EOM-OCCD method demonstrates dramatic acceleration in calculating excitation energies, with up to a 17-fold reduction in computational cost for the $$ molecule.
• Performance improvements stem from reduced integral transformation costs and efficient evaluation of the particle-particle ladder (PPL) term.
• The DF-EOM-OCCD approach proves effective for computing excitation energies in open-shell molecular systems.

Conclusions:

• The developed DF-EOM-OCCD implementation offers significant computational advantages for predicting molecular excited states.
• This efficient method is highly promising for theoretical studies of excited states in large and complex chemical systems.
• DF-EOM-OCCD enhances the feasibility of studying challenging molecular properties computationally.