A Full Quantum Eigensolver for Quantum Chemistry Simulations

TL;DR

The paper introduces a full quantum eigensolver (FQE) algorithm that calculates molecular ground energies entirely on a quantum computer, offering faster convergence and suitability for near-term quantum hardware.

Contribution

It presents a novel quantum eigensolver that eliminates classical optimization, enabling all calculations to be performed quantumly with improved efficiency and accuracy.

Findings

FQE removes the classical optimizer used in VQE.

It achieves logarithmic complexity in system size and precision.

FQE can be implemented on near-term quantum computers.

Abstract

Quantum simulation of quantum chemistry is one of the most compelling applications of quantum computing. It is of particular importance in areas ranging from materials science, biochemistry and condensed matter physics. Here, we propose a full quantum eigensolver (FQE) algorithm to calculate the molecular ground energies and electronic structures using quantum gradient descent. Compared to existing classical-quantum hybrid methods such as variational quantum eigensolver (VQE), our method removes the classical optimizer and performs all the calculations on a quantum computer with faster convergence. The gradient descent iteration depth has a favorable complexity that is logarithmically dependent on the system size and inverse of the precision. Moreover, the FQE can be further simplified by exploiting perturbation theory for the calculations of intermediate matrix elements, and obtain results with a precision that satisfies the requirement of chemistry application. The full quantum eigensolver can be implemented on a near-term quantum computer. With the rapid development of quantum computing hardware, FQE provides an efficient and powerful tool to solve quantum chemistry problems.