Mitigating errors in noisy quantum computers

Ryan LaRose, Tudor Giurgică-Tiron, Yousef Hindy +4 more

Abhinav Kandala

Vincent Russo, Andrea Mari, Nathan Shammah +2 more

We apply quantum error mitigation techniques to a variety of benchmark problems and quantum computers to evaluate the performance of quantum error mitigation in practice. To do so, we define an empirically motivated, resource-normalized metric of the improvement of error mitigation which we call the improvement factor, and calculate this metric for each experiment we perform. The experiments we perform consist of zero-noise extrapolation and probabilistic error cancellation applied to two benchmark problems run on IBM, IonQ, and Rigetti quantum computers, as well as noisy quantum computer simulators. Our results show that error mitigation is on average more beneficial than no error mitigation — even when normalized by the additional resources used — but also emphasize that the performance of quantum error mitigation depends on the underlying computer.

J. Borge, Unai Aseguinolaza, Nahual Sobrino +2 more

Ryan LaRose, Andrea Mari, Sarah Kaiser +16 more

We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error mitigation techniques can reduce the impact of noise on near-term quantum computers with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Mitiq is an extensible toolkit of different error mitigation methods, including zero-noise extrapolation, probabilistic error cancellation, and Clifford data regression. The library is designed to be compatible with generic backends and interfaces with different quantum software frameworks. We describe Mitiq using code snippets to demonstrate usage and discuss features and contribution guidelines. We present several examples demonstrating error mitigation on IBM and Rigetti superconducting quantum processors as well as on noisy simulators.

Constantia Alexandrou, Lena Funcke, Tobias Hartung +6 more

Readout errors are among the most dominant errors on current noisy intermediate-scale quantum devices. Recently, an efficient and scaleable method for mitigating such errors has been developed, based on classical bit-flip correction. In this talk, we compare the performance of this method for IBM's and Rigetti's quantum devices, demonstrating how the method improves the noisy measurements of observables obtained on the quantum hardware. Moreover, we examine the variance amplification to the data after applying of our mitigation procedure, which is common to all mitigation strategies. We derive a new expression for the variance of the mitigated Pauli operators in terms of the corrected expectation values and the noisy variances.Our hardware results show good agreement with the theoretical prediction, and we demonstrate that the increase of the variance due to the mitigation procedure is only moderate.