Measurement Error Mitigation for Variational Quantum Algorithms

TL;DR

This paper explores measurement error mitigation techniques for Variational Quantum Algorithms, demonstrating improved cost function estimates and characterizing measurement errors on devices with up to 20 qubits, advancing near-term quantum computing.

Contribution

It applies recent measurement error mitigation methods to VQAs and experimentally characterizes measurement errors related to device connectivity on larger quantum devices.

Findings

Improved expectation value estimates using error mitigation.

Characterization of measurement errors based on device connectivity.

Demonstrated effectiveness on devices with up to 20 qubits.

Abstract

Variational Quantum Algorithms (VQAs) are a promising application for near-term quantum processors, however the quality of their results is greatly limited by noise. For this reason, various error mitigation techniques have emerged to deal with noise that can be applied to these algorithms. Recent work introduced a technique for mitigating expectation values against correlated measurement errors that can be applied to measurements of 10s of qubits. We apply these techniques to VQAs and demonstrate its effectiveness in improving estimates to the cost function. Moreover, we use the data resulting from this technique to experimentally characterize measurement errors in terms of the device connectivity on devices of up to 20 qubits. These results should be useful for better understanding the near-term potential of VQAs as well as understanding the correlations in measurement errors on large, near-term devices.