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  • Frame-Based Filter-Function Formalism for Quantum Characterization and Control

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    Chalermpusitarak442812-Accepted.pdf (27.21Mb)
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    Accepted Manuscript (AM)
    Author(s)
    Chalermpusitarak, Teerawat
    Tonekaboni, Behnam
    Wang, Yuanlong
    Norris, Leigh M
    Viola, Lorenza
    Paz-Silva, Gerardo A
    Griffith University Author(s)
    Paz Silva, Gerardo A.
    Tonekaboni Faghihnasiri, Behnam
    Wang, Yuanlong
    Year published
    2021
    Metadata
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    Abstract
    We introduce a theoretical framework for resource-efficient characterization and control of non-Markovian open quantum systems, which naturally allows for the integration of given, experimentally motivated, control capabilities and constraints. This is achieved by developing a transfer filter-function formalism based on the general notion of a frame and by appropriately tying the choice of frame to the available control. While recovering the standard frequency-based filter-function formalism as a special instance, this control-adapted generalization affords intrinsic flexibility and, crucially, it permits an efficient ...
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    We introduce a theoretical framework for resource-efficient characterization and control of non-Markovian open quantum systems, which naturally allows for the integration of given, experimentally motivated, control capabilities and constraints. This is achieved by developing a transfer filter-function formalism based on the general notion of a frame and by appropriately tying the choice of frame to the available control. While recovering the standard frequency-based filter-function formalism as a special instance, this control-adapted generalization affords intrinsic flexibility and, crucially, it permits an efficient representation of the relevant control matrix elements and dynamical integrals if an appropriate finite-size frame condition is obeyed. Our frame-based formulation overcomes important limitations of existing approaches. In particular, we show how to implement quantum noise spectroscopy in the presence of nonstationary noise sources, and how to effectively achieve control-driven model reduction for noise-optimized prediction and quantum gate design.
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    Journal Title
    PRX Quantum
    Volume
    2
    Issue
    3
    DOI
    https://doi.org/10.1103/PRXQuantum.2.030315
    Copyright Statement
    © 2021 American Physical Society. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
    Subject
    Science & Technology
    Physical Sciences
    Quantum Science & Technology
    Physics, Applied
    Physics, Multidisciplinary
    Publication URI
    http://hdl.handle.net/10072/411595
    Collection
    • Journal articles

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