Probabilistic error cancellation with sparse Pauli-Lindblad models on noisy quantum processors
Abstract
Noise in pre-fault-tolerant quantum computers can result in biased estimates of physical observables. Accurate bias-free estimates can be obtained using probabilistic error cancellation (PEC), which is an error-mitigation technique that effectively inverts well-characterized noise channels. Learning correlated noise channels in large quantum circuits, however, has been a major challenge and has severely hampered experimental realizations. Our work presents a practical protocol for learning and inverting a sparse noise model that is able to capture correlated noise and scales to large quantum devices. These advances allow us to demonstrate PEC on a superconducting quantum processor with crosstalk errors, thereby providing an important milestone in opening the way to quantum computing with noise-free observables at larger circuit volumes.
Cite
@article{arxiv.2201.09866,
title = {Probabilistic error cancellation with sparse Pauli-Lindblad models on noisy quantum processors},
author = {Ewout van den Berg and Zlatko K. Minev and Abhinav Kandala and Kristan Temme},
journal= {arXiv preprint arXiv:2201.09866},
year = {2023}
}