Unified evolutionary optimization for high-fidelity spin qubit operations
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arXiv
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| Autori principali: | , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
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| author | Katiraee-Far, Sam R. Matsumoto, Yuta Undseth, Brennan De Smet, Maxim Gualtieri, Valentina Meinersen, Christian Ventura de Fuentes, Irene Fernandez Capannelli, Kenji Rimbach-Russ, Maximilian Scappucci, Giordano Vandersypen, Lieven M. K. Greplova, Eliska |
| author_facet | Katiraee-Far, Sam R. Matsumoto, Yuta Undseth, Brennan De Smet, Maxim Gualtieri, Valentina Meinersen, Christian Ventura de Fuentes, Irene Fernandez Capannelli, Kenji Rimbach-Russ, Maximilian Scappucci, Giordano Vandersypen, Lieven M. K. Greplova, Eliska |
| contents | Developing optimal strategies to calibrate quantum processors for high-fidelity operation is one of the outstanding challenges in quantum computing today. Here, we demonstrate multiple examples of high-fidelity operations achieved using a unified global optimization-driven automated calibration routine on a six dot semiconductor quantum processor. Within the same algorithmic framework we optimize readout, shuttling and single-qubit quantum gates by tailoring task-specific cost functions and tuning parameters based on the underlying physics of each operation. Our approach reaches systematically $99\%$ readout fidelity, $>99\%$ shuttling fidelity over an effective distance of 10$μ$m, and $>99.5\%$ single-qubit gate fidelity on timescales similar or shorter compared to those of expert human operators. The flexibility of our gradient-free closed loop algorithmic procedure allows for seamless application across diverse qubit functionalities while providing a systematic framework to tune-up semiconductor quantum devices and enabling interpretability of the identified optimal operation points. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_12256 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Unified evolutionary optimization for high-fidelity spin qubit operations Katiraee-Far, Sam R. Matsumoto, Yuta Undseth, Brennan De Smet, Maxim Gualtieri, Valentina Meinersen, Christian Ventura de Fuentes, Irene Fernandez Capannelli, Kenji Rimbach-Russ, Maximilian Scappucci, Giordano Vandersypen, Lieven M. K. Greplova, Eliska Quantum Physics Mesoscale and Nanoscale Physics Developing optimal strategies to calibrate quantum processors for high-fidelity operation is one of the outstanding challenges in quantum computing today. Here, we demonstrate multiple examples of high-fidelity operations achieved using a unified global optimization-driven automated calibration routine on a six dot semiconductor quantum processor. Within the same algorithmic framework we optimize readout, shuttling and single-qubit quantum gates by tailoring task-specific cost functions and tuning parameters based on the underlying physics of each operation. Our approach reaches systematically $99\%$ readout fidelity, $>99\%$ shuttling fidelity over an effective distance of 10$μ$m, and $>99.5\%$ single-qubit gate fidelity on timescales similar or shorter compared to those of expert human operators. The flexibility of our gradient-free closed loop algorithmic procedure allows for seamless application across diverse qubit functionalities while providing a systematic framework to tune-up semiconductor quantum devices and enabling interpretability of the identified optimal operation points. |
| title | Unified evolutionary optimization for high-fidelity spin qubit operations |
| topic | Quantum Physics Mesoscale and Nanoscale Physics |
| url | https://arxiv.org/abs/2503.12256 |