Probabilistic error cancellation with sparse Pauli-Lindblad models on noisy quantum processors

DIPC Seminars

Speaker

Kristan Temme
IBM Quantum, United States of America

When

2023/05/23
12:30

Place

Donostia International Physics Center

Host

Tobias Grass

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Noise in pre-fault-tolerant quantum computers can result in biased estimates of physical observables. Accurate biasfree 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.