Physics-informed tracking of qubit fluctuations
Fuente:
arXiv
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| Autori principali: | , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866911956548452352 |
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| author | Berritta, Fabrizio Krzywda, Jan A. Benestad, Jacob van der Heijden, Joost Fedele, Federico Fallahi, Saeed Gardner, Geoffrey C. Manfra, Michael J. van Nieuwenburg, Evert Danon, Jeroen Chatterjee, Anasua Kuemmeth, Ferdinand |
| author_facet | Berritta, Fabrizio Krzywda, Jan A. Benestad, Jacob van der Heijden, Joost Fedele, Federico Fallahi, Saeed Gardner, Geoffrey C. Manfra, Michael J. van Nieuwenburg, Evert Danon, Jeroen Chatterjee, Anasua Kuemmeth, Ferdinand |
| contents | Environmental fluctuations degrade the performance of solid-state qubits but can in principle be mitigated by real-time Hamiltonian estimation down to time scales set by the estimation efficiency. We implement a physics-informed and an adaptive Bayesian estimation strategy and apply them in real time to a semiconductor spin qubit. The physics-informed strategy propagates a probability distribution inside the quantum controller according to the Fokker-Planck equation, appropriate for describing the effects of nuclear spin diffusion in gallium-arsenide. Evaluating and narrowing the anticipated distribution by a predetermined qubit probe sequence enables improved dynamical tracking of the uncontrolled magnetic field gradient within the singlet-triplet qubit. The adaptive strategy replaces the probe sequence by a small number of qubit probe cycles, with each probe time conditioned on the previous measurement outcomes, thereby further increasing the estimation efficiency. The combined real-time estimation strategy efficiently tracks low-frequency nuclear spin fluctuations in solid-state qubits, and can be applied to other qubit platforms by tailoring the appropriate update equation to capture their distinct noise sources. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_09212 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Physics-informed tracking of qubit fluctuations Berritta, Fabrizio Krzywda, Jan A. Benestad, Jacob van der Heijden, Joost Fedele, Federico Fallahi, Saeed Gardner, Geoffrey C. Manfra, Michael J. van Nieuwenburg, Evert Danon, Jeroen Chatterjee, Anasua Kuemmeth, Ferdinand Mesoscale and Nanoscale Physics Quantum Physics Environmental fluctuations degrade the performance of solid-state qubits but can in principle be mitigated by real-time Hamiltonian estimation down to time scales set by the estimation efficiency. We implement a physics-informed and an adaptive Bayesian estimation strategy and apply them in real time to a semiconductor spin qubit. The physics-informed strategy propagates a probability distribution inside the quantum controller according to the Fokker-Planck equation, appropriate for describing the effects of nuclear spin diffusion in gallium-arsenide. Evaluating and narrowing the anticipated distribution by a predetermined qubit probe sequence enables improved dynamical tracking of the uncontrolled magnetic field gradient within the singlet-triplet qubit. The adaptive strategy replaces the probe sequence by a small number of qubit probe cycles, with each probe time conditioned on the previous measurement outcomes, thereby further increasing the estimation efficiency. The combined real-time estimation strategy efficiently tracks low-frequency nuclear spin fluctuations in solid-state qubits, and can be applied to other qubit platforms by tailoring the appropriate update equation to capture their distinct noise sources. |
| title | Physics-informed tracking of qubit fluctuations |
| topic | Mesoscale and Nanoscale Physics Quantum Physics |
| url | https://arxiv.org/abs/2404.09212 |