Separating Electron Correlations by Energy Scale: A Systematically Improvable Fragment-based Approach

Document Type




Conference Title

American Chemical Society Meeting


American Chemical Society (ACS)


San Francisco, CA

Conference Dates

August 10-14, 2014

Date of Presentation



The accuracy of large-scale ab initio calculations is always desired, but they are unfortunately not usually practical in many fields, such as studies of heterogeneous catalysis, photosynthesis, and functional mechanisms of biomolecules. DFT serves as a prevailing method for large calculations due to its compromise between cost and accuracy, but it has a number of failure cases, like bond breaking. On the other hand, the simple theoretical nature of force-field simulations, which often work well, reminds us that large systems are not necessarily exponentially complicated. A recurring theme in the electronic structure of large systems is therefore the use of fragment-based approaches.

Existing fragment approaches typically treat the most powerful electron correlations perturbatively, on the same footing with dispersion forces (if at all). In our approach, electrons are not treated individually in the global calculation, but subunits will be chosen. (e.g., amino acid residues or individual water molecules). The most important local states are selected to account for inter-subunit interactions. Most familiar wavefunction methods (SCF, PT, coupled-cluster) can be applied directly to this internally correlated Hamiltonian, and the Hamiltonian itself is systematically improvable to exactitude. Furthermore, different parts of a system can be treated at different accuracy. Our initial investigations focus on the correlation structure of groups of harmonic oscillators, where the coupling inside of groups is stronger than between groups. This mimics discrete molecules while providing us with exact analytical solutions for comparison. Correlations between grouped oscillators will be characterized by both numerical and analytical methods, in order to shed light on building an algorithm for real molecules and systems.

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