Systems and methods for analog processing of problem graphs having arbitrary size and/or connectivity

    公开(公告)号:US11704586B2

    公开(公告)日:2023-07-18

    申请号:US17739411

    申请日:2022-05-09

    CPC classification number: G06N10/00

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

    Systems and methods for analog processing of problem graphs having arbitrary size and/or connectivity

    公开(公告)号:US11348026B2

    公开(公告)日:2022-05-31

    申请号:US16778295

    申请日:2020-01-31

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

    SYSTEMS AND METHODS FOR ANALOG PROCESSING OF PROBLEM GRAPHS HAVING ARBITRARY SIZE AND/OR CONNECTIVITY

    公开(公告)号:US20200167685A1

    公开(公告)日:2020-05-28

    申请号:US16778295

    申请日:2020-01-31

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

    SYSTEMS AND METHODS FOR ANALOG PROCESSING OF PROBLEM GRAPHS HAVING ARBITRARY SIZE AND/OR CONNECTIVITY

    公开(公告)号:US20220335320A1

    公开(公告)日:2022-10-20

    申请号:US17739411

    申请日:2022-05-09

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

    Systems and methods for quantum bayesian networks

    公开(公告)号:US11386346B2

    公开(公告)日:2022-07-12

    申请号:US16357773

    申请日:2019-03-19

    Abstract: Techniques are provided for computing problems represented as directed graphical models via quantum processors with topologies and coupling physics which correspond to undirected graphs. These include techniques for generating approximations of Bayesian networks via a quantum processor capable of computing problems based on a Markov network-based representation of such problems. Approximations may be generated by moralization of Bayesian networks to Markov networks, learning of Bayesian networks' probability distributions by Markov networks' probability distributions, or otherwise, and are trained by executing the resulting Markov network on the quantum processor.

    SYSTEMS AND METHODS FOR ANALOG PROCESSING OF PROBLEM GRAPHS HAVING ARBITRARY SIZE AND/OR CONNECTIVITY

    公开(公告)号:US20230385668A1

    公开(公告)日:2023-11-30

    申请号:US18203880

    申请日:2023-05-31

    CPC classification number: G06N10/00

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

    Systems and methods for analog processing of problem graphs having arbitrary size and/or connectivity

    公开(公告)号:US10599988B2

    公开(公告)日:2020-03-24

    申请号:US15448361

    申请日:2017-03-02

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

    SYSTEMS AND METHODS FOR QUANTUM BAYESIAN NETWORKS

    公开(公告)号:US20200019879A1

    公开(公告)日:2020-01-16

    申请号:US16357773

    申请日:2019-03-19

    Abstract: Techniques are provided for computing problems represented as directed graphical models via quantum processors with topologies and coupling physics which correspond to undirected graphs. These include techniques for generating approximations of Bayesian networks via a quantum processor capable of computing problems based on a Markov network-based representation of such problems. Approximations may be generated by moralization of Bayesian networks to Markov networks, learning of Bayesian networks' probability distributions by Markov networks' probability distributions, or otherwise, and are trained by executing the resulting Markov network on the quantum processor.

    SYSTEMS AND METHODS FOR ANALOG PROCESSING OF PROBLEM GRAPHS HAVING ARBITRARY SIZE AND/OR CONNECTIVITY

    公开(公告)号:US20170255629A1

    公开(公告)日:2017-09-07

    申请号:US15448361

    申请日:2017-03-02

    CPC classification number: G06N10/00

    Abstract: Computational systems implement problem solving using hybrid digital/quantum computing approaches. A problem may be represented as a problem graph which is larger and/or has higher connectivity than a working and/or hardware graph of a quantum processor. A quantum processor may be used determine approximate solutions, which solutions are provided as initial states to one or more digital processors which may implement classical post-processing to generate improved solutions. Techniques for solving problems on extended, more-connected, and/or “virtual full yield” variations of the processor's actual working and/or hardware graphs are provided. A method of operation in a computational system comprising a quantum processor includes partitioning a problem graph into sub-problem graphs, and embedding a sub-problem graph onto the working graph of the quantum processor. The quantum processor and a non-quantum processor-based device generate partial samples. A controller causes a processing operation on the partial samples to generate complete samples.

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