Assessment of error variation in high-fidelity two-qubit gates in silicon
Achieving high-fidelity entangling operations between qubits consistently is essential for the performance of multi-qubit systems and is a crucial factor in achieving fault-tolerant quantum processors. Solid-state platforms are particularly exposed to errors due to materials-induced variability betw...
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creator | Tanttu, Tuomo Wee Han Lim Huang, Jonathan Y Nard Dumoulin Stuyck Gilbert, Will Su, Rocky Y Feng, MengKe Cifuentes, Jesus D Seedhouse, Amanda E Seritan, Stefan K Ostrove, Corey I Rudinger, Kenneth M Leon, Ross C C Huang, Wister Escott, Christopher C Itoh, Kohei M Abrosimov, Nikolay V Pohl, Hans-Joachim Thewalt, Michael L W Hudson, Fay E Blume-Kohout, Robin Bartlett, Stephen D Morello, Andrea Laucht, Arne Yang, Chih Hwan Saraiva, Andre Dzurak, Andrew S |
description | Achieving high-fidelity entangling operations between qubits consistently is essential for the performance of multi-qubit systems and is a crucial factor in achieving fault-tolerant quantum processors. Solid-state platforms are particularly exposed to errors due to materials-induced variability between qubits, which leads to performance inconsistencies. Here we study the errors in a spin qubit processor, tying them to their physical origins. We leverage this knowledge to demonstrate consistent and repeatable operation with above 99% fidelity of two-qubit gates in the technologically important silicon metal-oxide-semiconductor (SiMOS) quantum dot platform. We undertake a detailed study of these operations by analysing the physical errors and fidelities in multiple devices through numerous trials and extended periods to ensure that we capture the variation and the most common error types. Physical error sources include the slow nuclear and electrical noise on single qubits and contextual noise. The identification of the noise sources can be used to maintain performance within tolerance as well as inform future device fabrication. Furthermore, we investigate the impact of qubit design, feedback systems, and robust gates on implementing scalable, high-fidelity control strategies. These results are achieved by using three different characterization methods, we measure entangling gate fidelities ranging from 96.8% to 99.8%. Our analysis tools identify the causes of qubit degradation and offer ways understand their physical mechanisms. These results highlight both the capabilities and challenges for the scaling up of silicon spin-based qubits into full-scale quantum processors. |
doi_str_mv | 10.48550/arxiv.2303.04090 |
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Solid-state platforms are particularly exposed to errors due to materials-induced variability between qubits, which leads to performance inconsistencies. Here we study the errors in a spin qubit processor, tying them to their physical origins. We leverage this knowledge to demonstrate consistent and repeatable operation with above 99% fidelity of two-qubit gates in the technologically important silicon metal-oxide-semiconductor (SiMOS) quantum dot platform. We undertake a detailed study of these operations by analysing the physical errors and fidelities in multiple devices through numerous trials and extended periods to ensure that we capture the variation and the most common error types. Physical error sources include the slow nuclear and electrical noise on single qubits and contextual noise. The identification of the noise sources can be used to maintain performance within tolerance as well as inform future device fabrication. Furthermore, we investigate the impact of qubit design, feedback systems, and robust gates on implementing scalable, high-fidelity control strategies. These results are achieved by using three different characterization methods, we measure entangling gate fidelities ranging from 96.8% to 99.8%. Our analysis tools identify the causes of qubit degradation and offer ways understand their physical mechanisms. These results highlight both the capabilities and challenges for the scaling up of silicon spin-based qubits into full-scale quantum processors.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.2303.04090</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Accuracy ; Error analysis ; Error correction ; Error correction & detection ; Fault tolerance ; Metal oxide semiconductors ; Physics - Mesoscale and Nanoscale Physics ; Physics - Quantum Physics ; Processors ; Quantum computing ; Quantum dots ; Qubits (quantum computing) ; Silicon ; Stability analysis</subject><ispartof>arXiv.org, 2024-03</ispartof><rights>2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,784,885,27925</link.rule.ids><backlink>$$Uhttps://doi.org/10.1038/s41567-024-02614-w$$DView published paper (Access to full text may be restricted)$$Hfree_for_read</backlink><backlink>$$Uhttps://doi.org/10.48550/arXiv.2303.04090$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Tanttu, Tuomo</creatorcontrib><creatorcontrib>Wee Han Lim</creatorcontrib><creatorcontrib>Huang, Jonathan Y</creatorcontrib><creatorcontrib>Nard Dumoulin Stuyck</creatorcontrib><creatorcontrib>Gilbert, Will</creatorcontrib><creatorcontrib>Su, Rocky Y</creatorcontrib><creatorcontrib>Feng, MengKe</creatorcontrib><creatorcontrib>Cifuentes, Jesus D</creatorcontrib><creatorcontrib>Seedhouse, Amanda E</creatorcontrib><creatorcontrib>Seritan, Stefan K</creatorcontrib><creatorcontrib>Ostrove, Corey I</creatorcontrib><creatorcontrib>Rudinger, Kenneth M</creatorcontrib><creatorcontrib>Leon, Ross C C</creatorcontrib><creatorcontrib>Huang, Wister</creatorcontrib><creatorcontrib>Escott, Christopher C</creatorcontrib><creatorcontrib>Itoh, Kohei M</creatorcontrib><creatorcontrib>Abrosimov, Nikolay V</creatorcontrib><creatorcontrib>Pohl, Hans-Joachim</creatorcontrib><creatorcontrib>Thewalt, Michael L W</creatorcontrib><creatorcontrib>Hudson, Fay E</creatorcontrib><creatorcontrib>Blume-Kohout, Robin</creatorcontrib><creatorcontrib>Bartlett, Stephen D</creatorcontrib><creatorcontrib>Morello, Andrea</creatorcontrib><creatorcontrib>Laucht, Arne</creatorcontrib><creatorcontrib>Yang, Chih Hwan</creatorcontrib><creatorcontrib>Saraiva, Andre</creatorcontrib><creatorcontrib>Dzurak, Andrew S</creatorcontrib><title>Assessment of error variation in high-fidelity two-qubit gates in silicon</title><title>arXiv.org</title><description>Achieving high-fidelity entangling operations between qubits consistently is essential for the performance of multi-qubit systems and is a crucial factor in achieving fault-tolerant quantum processors. Solid-state platforms are particularly exposed to errors due to materials-induced variability between qubits, which leads to performance inconsistencies. Here we study the errors in a spin qubit processor, tying them to their physical origins. We leverage this knowledge to demonstrate consistent and repeatable operation with above 99% fidelity of two-qubit gates in the technologically important silicon metal-oxide-semiconductor (SiMOS) quantum dot platform. We undertake a detailed study of these operations by analysing the physical errors and fidelities in multiple devices through numerous trials and extended periods to ensure that we capture the variation and the most common error types. Physical error sources include the slow nuclear and electrical noise on single qubits and contextual noise. The identification of the noise sources can be used to maintain performance within tolerance as well as inform future device fabrication. Furthermore, we investigate the impact of qubit design, feedback systems, and robust gates on implementing scalable, high-fidelity control strategies. These results are achieved by using three different characterization methods, we measure entangling gate fidelities ranging from 96.8% to 99.8%. Our analysis tools identify the causes of qubit degradation and offer ways understand their physical mechanisms. 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subjects | Accuracy Error analysis Error correction Error correction & detection Fault tolerance Metal oxide semiconductors Physics - Mesoscale and Nanoscale Physics Physics - Quantum Physics Processors Quantum computing Quantum dots Qubits (quantum computing) Silicon Stability analysis |
title | Assessment of error variation in high-fidelity two-qubit gates in silicon |
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