Range‐separated density functional theory using multiresolution analysis and quantum computing

Author:

Poirier Nicolas12ORCID,Kottmann Jakob S.3ORCID,Aspuru‐Guzik Alán4567ORCID,Mongeau Luc1ORCID,Najafi‐Yazdi Alireza12

Affiliation:

1. Department of Mechanical Engineering McGill University Montreal Quebec Canada

2. Anyon Systems Inc. Dorval Quebec Canada

3. Institute for Computer Science University of Augsburg Augsburg Germany

4. Chemical Physics Theory Group, Department of Chemistry University of Toronto Toronto Ontario Canada

5. Department of Computer Science University of Toronto Toronto Ontario Canada

6. Vector Institute for Artificial Intelligence Toronto Ontario Canada

7. Canadian Institute for Advanced Research (CIFAR) Toronto Ontario Canada

Abstract

AbstractQuantum computers are expected to outperform classical computers for specific problems in quantum chemistry. Such calculations remain expensive, but costs can be lowered through the partition of the molecular system. In the present study, partition was achieved with range‐separated density functional theory (RS‐DFT). The use of RS‐DFT reduces both the basis set size and the active space size dependence of the ground state energy in comparison with the use of wave function theory (WFT) alone. The utilization of pair natural orbitals (PNOs) in place of canonical molecular orbitals (MOs) results in more compact qubit Hamiltonians. To test this strategy, a basis‐set independent framework, known as multiresolution analysis (MRA), was employed to generate PNOs. Tests were conducted with the variational quantum eigensolver for a number of molecules. The results show that the proposed approach reduces the number of qubits needed to reach a target energy accuracy.

Funder

Mitacs

Google

U.S. Department of Energy

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

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