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Machine learning as an enabler of qubit scalability

Intense efforts are underway to produce circuits that integrate a technologically relevant number of qubits. Although qubit control in most material systems is by now mature, device variability is one of the main bottlenecks in qubit scalability. How do we characterize and tune millions of qubits? Machine learning might hold the answer.

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Fig. 1: Qubit tuning and characterization.

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Correspondence to Natalia Ares.

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Ares, N. Machine learning as an enabler of qubit scalability. Nat Rev Mater 6, 870–871 (2021). https://doi.org/10.1038/s41578-021-00321-z

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