Implementation of the Projective Quantum Eigensolver on a Quantum Computer

TL;DR

This paper evaluates the performance of the Projective Quantum Eigensolver (PQE) on IBM quantum hardware, demonstrating its ability to accurately compute energies for simple models and discussing error mitigation strategies.

Contribution

It presents the first experimental implementation of PQE on real quantum hardware, analyzing its accuracy, convergence, and error mitigation techniques for molecular and spin models.

Findings

Achieved 4 millihartree accuracy for H2 energy calculations.

Recovered 99% of correlation energy in the Ising model using PQE.

Identified the impact of CNOT gate errors on PQE accuracy.

Abstract

We study the performance of our previously proposed Projective Quantum Eigensolver (PQE) on IBM's quantum hardware in conjunction with error mitigation techniques. For a single qubit model of H$_2$, we find that we are able to obtain energies within 4 millihartree (2.5 kcal/mol) of the exact energy along the entire potential energy curve, with the accuracy limited by both stochastic error and inconsistent performance of the IBM devices. We find that an optimization algorithm using direct inversion of the iterative subspace can converge swiftly, even to excited states, but stochastic noise can cause large parameter updates. For the four-site transverse-field Ising model at the critical point, PQE with an appropriate application of qubit tapering can recover 99% of the correlation energy, even discarding several parameters. The large number of CNOT gates needed for the additional parameters introduces a concomitant error that, on the IBM devices, results in loss of accuracy, despite the increased expressivity of the trial state. Error extrapolation techniques and tapering or postselection are recommended to mitigate errors in PQE hardware experiments.