Efficient learning of quantum noise

Noise is the central obstacle to building large-scale quantum computers. Quantum systems with sufficiently  uncorrelated and weak noise could be used to solve computational problems that are intractable with current digital computers. There has been substantial progress towards engineering such systems. However, continued progress depends on the ability to characterize quantum noise reliably and efficiently with high precision. Here we introduce a protocol that comprehensively and efficiently characterizes the error rates of quantum noise and we experimentally implement it on a 14-qubit superconducting quantum architecture. The method returns an estimate of the effective noise with relative precision and can detect arbitrary correlated errors. We show how to construct a quantum noise correlation matrix allowing the easy visualization of all pairwise correlated errors, enabling the discovery of long-range two-qubit correlations in the 14 qubit device that had not previously been detected...