Optimized continuous dynamical decoupling via differential geometry and machine learning

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Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorQuaTI-Quantum Technology & Information-
Autor(es): dc.creatorMorazotti, Nicolas André Da Costa-
Autor(es): dc.creatorDa Silva, Adonai Hilário-
Autor(es): dc.creatorAudi, Gabriel-
Autor(es): dc.creatorFanchini, Felipe Fernandes-
Autor(es): dc.creatorNapolitano, Reginaldo De Jesus-
Data de aceite: dc.date.accessioned2025-08-21T17:48:21Z-
Data de disponibilização: dc.date.available2025-08-21T17:48:21Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-10-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1103/PhysRevA.110.042601-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/299454-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/299454-
Descrição: dc.descriptionWe introduce a strategy to develop optimally designed fields for continuous dynamical decoupling. Using our methodology, we obtain the optimal continuous field configuration to maximize the fidelity of a general one-qubit quantum gate. To achieve this, considering dephasing-noise perturbations, we employ an auxiliary qubit instead of the boson bath to implement a purification scheme, which results in unitary dynamics. Employing the sub-Riemannian geometry framework for the two-qubit unitary group, we derive and numerically solve the geodesic equations, obtaining the optimal time-dependent control Hamiltonian. Also, due to the extended time required to find solutions to the geodesic equations, we train a neural network on a subset of geodesic solutions, enabling us to promptly generate the time-dependent control Hamiltonian for any desired gate, which is crucial in circuit optimization.-
Descrição: dc.descriptionSao Carlos Institute of Physics University of Sao Paulo, P.O. Box 369, SP-
Descrição: dc.descriptionSao Paulo State University (UNESP) School of Sciences, SP-
Descrição: dc.descriptionQuaTI-Quantum Technology & Information, SP-
Descrição: dc.descriptionSao Paulo State University (UNESP) School of Sciences, SP-
Idioma: dc.languageen-
Relação: dc.relationPhysical Review A-
???dc.source???: dc.sourceScopus-
Título: dc.titleOptimized continuous dynamical decoupling via differential geometry and machine learning-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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