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 I will discuss a newly introduced protocol that completely and efficiently characterizes the qubit error rates of quantum noise. The method returns an estimate of the effective noise with relative precision and detects all correlated errors. I will show how the reconstruction allows the easy visualization of these correlated errors, enabling both the discovery of long-range correlations in the device and the construction of scalable models that describe the noise in the device to arbitrary precision. These properties of the protocol make it exceptionally well suited for high-precision noise metrology in quantum information processors. Our results are the first implementation of a provably rigorous, diagnostic protocol capable of being run on state of the art devices and beyond. These results pave the way for noise metrology in next-generation quantum devices, calibration in the presence of crosstalk, bespoke quantum error-correcting codes, and customized fault-tolerance protocols that can greatly reduce the overhead in a quantum computation.