Long-range correlated errors can severely impact the performance of noisy intermediate-scale quantum (NISQ) computing devices and proposed schemes for fault-tolerant quantum computation. Characterizing these errors is important for improving the performance of the device (via calibration and error correction), and to ensure correct interpretation of the result. We propose a compressed sensing method for detecting two-qubit correlated dephasing errors, assuming only that the correlations are sparse (i.e., at most s pairs of qubits have correlated errors, where s << n(n-1)/2, and n is the total number of qubits). In particular, our method can detect long-range correlations between any two qubits in the system (i.e., the correlations are not restricted to be geometrically local). Our method is highly scalable: it requires only s log(n) measurement settings and efficient classical postprocessing based on convex optimization. Our method also has nice theoretical properties, such as provable recovery guarantees, and resistance to state-preparation-and-measurement (SPAM) errors. The key ingredient in our method is a new type of compressed sensing measurement, which works by preparing entangled GHZ states on random subsets of qubits and measuring their decay rates with high precision.
These results are based on joint work with Mohammad Hafezi and Yi-Kai Liu.
For zoom link, contact Diana Morgan (morgandj@anl.gov)
