Computing Electronic Correlation Energies using Linear Depth Quantum Circuits

TL;DR

This paper introduces a NISQ-compatible quantum algorithm that uses shallow, linear-depth circuits to estimate electronic correlation energies in molecules, enabling studies of larger molecules on near-term quantum devices.

Contribution

The authors propose a variational quantum algorithm with shallow circuits that efficiently estimates correlation energies, suitable for noisy intermediate-scale quantum devices.

Findings

Successfully tested on small molecules with classical and quantum simulations.

Reproduces equilibrium energies and captures correlation effects at longer bond distances.

Shows potential for studying larger molecules as quantum hardware improves.

Abstract

Efficient computation of molecular energies is an exciting application of quantum computing for quantum chemistry, but current noisy intermediate-scale quantum (NISQ) devices can only execute shallow circuits, limiting existing variational quantum algorithms, which require deep entangling quantum circuit ansatzes to capture correlations, to small molecules. Here we demonstrate a variational NISQ-friendly algorithm that generates a set of mean-field Hartree-Fock (HF) ansatzes using multiple shallow circuits with depth linear in the number of qubits to estimate electronic correlation energies via perturbation theory up to the second order. We tested the algorithm on several small molecules, both with classical simulations including noise models and on cloud quantum processors, showing that it not only reproduces the equilibrium molecular energies but it also captures the perturbative electronic correlation effects at longer bond distances. As fidelities of quantum processors continue to improve our algorithm will enable the study of larger molecules compared to other approaches requiring higher-order polynomial circuit depth.