Divide-and-conquer variational quantum algorithms for large-scale electronic structure simulations

TL;DR

This paper introduces divide-and-conquer strategies integrated with variational quantum algorithms to enable large-scale electronic structure simulations on near-term quantum computers, addressing resource limitations.

Contribution

It combines MBE and DMET divide-and-conquer schemes with VQE to tackle complex quantum chemistry problems efficiently on current quantum hardware.

Findings

Successful application to systems with tens of atoms

Demonstrated feasibility of large-scale quantum chemistry simulations

Encourages further development of divide-and-conquer quantum algorithms

Abstract

Exploring the potential application of quantum computers in material design and drug discovery has attracted a lot of interest in the age of quantum computing. However, the quantum resource requirement for solving practical electronic structure problems are far beyond the capacity of near-term quantum devices. In this work, we integrate the divide-and-conquer (DC) approaches into the variational quantum eigensolver (VQE) for large-scale quantum computational chemistry simulations. Two popular divide-and-conquer schemes, including many-body expansion~(MBE) fragmentation theory and density matrix embedding theory~(DMET), are employed to divide complicated problems into many small parts that are easy to implement on near-term quantum computers. Pilot applications of these methods to systems consisting of tens of atoms are performed with adaptive VQE algorithms. This work should encourage further studies of using the philosophy of DC to solve electronic structure problems on quantum computers.