Error mitigation with stabilized noise in superconducting quantum processors

Youngseok Kim (), Luke C. G. Govia, Andrew Dane, Ewout Berg, David M. Zajac, Bradley Mitchell, Yinyu Liu, Karthik Balakrishnan, George Keefe, Adam Stabile, Emily Pritchett, Jiri Stehlik and Abhinav Kandala ()
Additional contact information
Youngseok Kim: IBM T.J. Watson Research Center
Luke C. G. Govia: IBM Almaden Research Center
Andrew Dane: IBM T.J. Watson Research Center
Ewout Berg: IBM T.J. Watson Research Center
David M. Zajac: IBM T.J. Watson Research Center
Bradley Mitchell: IBM Almaden Research Center
Yinyu Liu: IBM T.J. Watson Research Center
Karthik Balakrishnan: IBM T.J. Watson Research Center
George Keefe: IBM T.J. Watson Research Center
Adam Stabile: IBM T.J. Watson Research Center
Emily Pritchett: IBM T.J. Watson Research Center
Jiri Stehlik: IBM T.J. Watson Research Center
Abhinav Kandala: IBM T.J. Watson Research Center

Nature Communications, 2025, vol. 16, issue 1, 1-8

Abstract: Abstract Pre-fault tolerant quantum computers have already demonstrated the ability to estimate observable values accurately, at a scale beyond brute-force classical computation. This has been enabled by error mitigation techniques that often rely on a representative model of the device noise. However, learning and maintaining these models is complicated by fluctuations in the noise over unpredictable time scales, for instance, arising from resonant interactions between superconducting qubits and defect two-level systems (TLS). Such interactions affect the stability and uniformity of device performance as a whole, but also affect the noise model accuracy, leading to incorrect observable estimation. Here, we experimentally demonstrate that tuning of the qubit-TLS interactions helps reduce noise instabilities and consequently enables more reliable error-mitigation performance. These experiments provide a controlled platform for studying the performance of error mitigation in the presence of quasi-static noise. We anticipate that the capabilities introduced here will be crucial for the exploration of quantum applications on solid-state processors at non-trivial scales.

Date: 2025
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DOI: 10.1038/s41467-025-62820-9

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