Error mitigation with stabilized noise in superconducting quantum processors
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arXiv
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866909536912146432 |
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| author | Kim, Youngseok Govia, Luke C. G. Dane, Andrew Berg, Ewout van den Zajac, David M. Mitchell, Bradley Liu, Yinyu Balakrishnan, Karthik Keefe, George Stabile, Adam Pritchett, Emily Stehlik, Jiri Kandala, Abhinav |
| author_facet | Kim, Youngseok Govia, Luke C. G. Dane, Andrew Berg, Ewout van den Zajac, David M. Mitchell, Bradley Liu, Yinyu Balakrishnan, Karthik Keefe, George Stabile, Adam Pritchett, Emily Stehlik, Jiri Kandala, Abhinav |
| contents | 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 on 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_02467 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Error mitigation with stabilized noise in superconducting quantum processors Kim, Youngseok Govia, Luke C. G. Dane, Andrew Berg, Ewout van den Zajac, David M. Mitchell, Bradley Liu, Yinyu Balakrishnan, Karthik Keefe, George Stabile, Adam Pritchett, Emily Stehlik, Jiri Kandala, Abhinav Quantum Physics 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 on 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. |
| title | Error mitigation with stabilized noise in superconducting quantum processors |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2407.02467 |