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公开(公告)号:US11042811B2
公开(公告)日:2021-06-22
申请号:US15725600
申请日:2017-10-05
Applicant: D-Wave Systems Inc.
Inventor: Jason Rolfe , William G. Macready , Zhengbing Bian , Fabian A. Chudak
IPC: G06N10/00 , G06N3/04 , G06K9/00 , G06N3/08 , G06F15/80 , G06N20/00 , G06K9/62 , G06N20/10 , G06N7/00
Abstract: A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the computational system can perform unsupervised learning over an input space, for example via a discrete variational auto-encoder, and attempting to maximize the log-likelihood of an observed dataset. Maximizing the log-likelihood of the observed dataset can include generating a hierarchical approximating posterior. Unsupervised learning can include generating samples of a prior distribution using the quantum processor. Generating samples using the quantum processor can include forming chains of qubits and representing discrete variables by chains.
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公开(公告)号:US10817796B2
公开(公告)日:2020-10-27
申请号:US15452438
申请日:2017-03-07
Applicant: D-Wave Systems Inc.
Inventor: William G. Macready , Firas Hamze , Fabian A. Chudak , Mani Ranjbar , Jack R. Raymond , Jason T. Rolfe
IPC: G06N10/00 , G06N7/00 , G06N20/00 , G06K9/62 , G06F111/10
Abstract: A hybrid computer comprising a quantum processor can be operated to perform a scalable comparison of high-entropy samplers. Performing a scalable comparison of high-entropy samplers can include comparing entropy and KL divergence of post-processed samplers. A hybrid computer comprising a quantum processor generates samples for machine learning. The quantum processor is trained by matching data statistics to statistics of the quantum processor. The quantum processor is tuned to match moments of the data.
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3.
公开(公告)号:US20180101784A1
公开(公告)日:2018-04-12
申请号:US15725600
申请日:2017-10-05
Applicant: D-Wave Systems Inc.
Inventor: Jason Rolfe , William G. Macready , Zhengbing Bian , Fabian A. Chudak
CPC classification number: G06N10/00 , G06F15/80 , G06K9/00986 , G06K9/6256 , G06N3/0454 , G06N3/0472 , G06N3/084 , G06N3/088 , G06N7/005 , G06N20/00
Abstract: A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the computational system can perform unsupervised learning over an input space, for example via a discrete variational auto-encoder, and attempting to maximize the log-likelihood of an observed dataset. Maximizing the log-likelihood of the observed dataset can include generating a hierarchical approximating posterior. Unsupervised learning can include generating samples of a prior distribution using the quantum processor. Generating samples using the quantum processor can include forming chains of qubits and representing discrete variables by chains.
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4.
公开(公告)号:US20230385668A1
公开(公告)日:2023-11-30
申请号:US18203880
申请日:2023-05-31
Applicant: D-WAVE SYSTEMS INC.
Inventor: Murray C. Thom , Aidan P. Roy , Fabian A. Chudak , Zhengbing Bian , William G. Macready , Robert B. Israel , Kelly T. R. Boothby , Sheir Yarkoni , Yanbo Xue , Dmytro Korenkevych
IPC: G06N10/00
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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公开(公告)号:US10599988B2
公开(公告)日:2020-03-24
申请号:US15448361
申请日:2017-03-02
Applicant: D-Wave Systems Inc.
Inventor: Murray C. Thom , Aidan P. Roy , Fabian A. Chudak , Zhengbing Bian , William G. Macready , Robert B. Israel , Kelly T.R. Boothby , Sheir Yarkoni , Yanbo Xue , Dmytro Korenkevych
IPC: 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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公开(公告)号:US20170255871A1
公开(公告)日:2017-09-07
申请号:US15452438
申请日:2017-03-07
Applicant: D-Wave Systems Inc.
Inventor: William G. Macready , Firas Hamze , Fabian A. Chudak , Mani Ranjbar , Jack R. Raymond , Jason T. Rolfe
Abstract: A hybrid computer comprising a quantum processor can be operated to perform a scalable comparison of high-entropy samplers. Performing a scalable comparison of high-entropy samplers can include comparing entropy and KL divergence of post-processed samplers. A hybrid computer comprising a quantum processor generates samples for machine learning. The quantum processor is trained by matching data statistics to statistics of the quantum processor. The quantum processor is tuned to match moments of the data.
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7.
公开(公告)号:US20170255629A1
公开(公告)日:2017-09-07
申请号:US15448361
申请日:2017-03-02
Applicant: D-Wave Systems Inc.
Inventor: Murray C. Thom , Aidan P. Roy , Fabian A. Chudak , Zhengbing Bian , William G. Macready , Robert B. Israel , Tomas J. Boothby , Sheir Yarkoni , Yanbo Xue , Dmytro Korenkevych
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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公开(公告)号:US11704586B2
公开(公告)日:2023-07-18
申请号:US17739411
申请日:2022-05-09
Applicant: D-WAVE SYSTEMS INC.
Inventor: Murray C. Thom , Aidan P. Roy , Fabian A. Chudak , Zhengbing Bian , William G. Macready , Robert B. Israel , Kelly T. R. Boothby , Sheir Yarkoni , Yanbo Xue , Dmytro Korenkevych
IPC: G06N10/00
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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公开(公告)号:US11348026B2
公开(公告)日:2022-05-31
申请号:US16778295
申请日:2020-01-31
Applicant: D-WAVE SYSTEMS INC.
Inventor: Murray C. Thom , Aidan P. Roy , Fabian A. Chudak , Zhengbing Bian , William G. Macready , Robert B. Israel , Kelly T. R. Boothby , Sheir Yarkoni , Yanbo Xue , Dmytro Korenkevych
IPC: 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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公开(公告)号:US20210019647A1
公开(公告)日:2021-01-21
申请号:US17030576
申请日:2020-09-24
Applicant: D-WAVE SYSTEMS INC.
Inventor: William G. Macready , Firas Hamze , Fabian A. Chudak , Mani Ranjbar , Jack R. Raymond , Jason T. Rolfe
Abstract: A hybrid computer comprising a quantum processor can be operated to perform a scalable comparison of high-entropy samplers. Performing a scalable comparison of high-entropy samplers can include comparing entropy and KL divergence of post-processed samplers. A hybrid computer comprising a quantum processor generates samples for machine learning. The quantum processor is trained by matching data statistics to statistics of the quantum processor. The quantum processor is tuned to match moments of the data.
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