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

Quantum 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. The performance of existing quantum computers is limited by noise, especially for calculations which involve large molecular systems. One possible solution is to transfer some of the computational load to a classical computer. Such transfer can be achieved by assigning one portion of the electronic repulsion to a quantum computer and the remainder to a classical computer. The use of pair natural orbitals enables a further reduction of the computational load placed on a quantum computer.