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    Quantum processor based systems and methods that minimize an objective function
    11.
    发明授权
    Quantum processor based systems and methods that minimize an objective function 有权

    公开(公告)号：US10467543B2

    公开(公告)日：2019-11-05

    申请号：US14920235

    申请日：2015-10-22

    Applicant: D-Wave Systems Inc.

    Inventor： William G. Macready ,  Mani Ranjbar ,  Firas Hamze ,  Geordie Rose ,  Suzanne Gildert

    IPC: G06N10/00 ,  G06N5/02 ,  B82Y10/00 ,  G06N7/00 ,  G06N3/12 ,  G06N3/00

    Abstract: Quantum processor based techniques minimize an objective function for example by operating the quantum processor as a sample generator providing low-energy samples from a probability distribution with high probability. The probability distribution is shaped to assign relative probabilities to samples based on their corresponding objective function values until the samples converge on a minimum for the objective function. Problems having a number of variables and/or a connectivity between variables that does not match that of the quantum processor may be solved. Interaction with the quantum processor may be via a digital computer. The digital computer stores a hierarchical stack of software modules to facilitate interacting with the quantum processor via various levels of programming environment, from a machine language level up to an end-use applications level.

    SYSTEMS AND METHODS FOR FINDING QUANTUM BINARY OPTIMIZATION PROBLEMS
    13.
    发明申请
    SYSTEMS AND METHODS FOR FINDING QUANTUM BINARY OPTIMIZATION PROBLEMS 审中-公开
    用于发现量子二进制优化问题的系统和方法

    公开(公告)号：US20150205759A1

    公开(公告)日：2015-07-23

    申请号：US14671862

    申请日：2015-03-27

    Applicant: D-WAVE SYSTEMS INC.

    Inventor： Robert Israel ,  William G. Macready ,  Zhengbing Bian ,  Fabian Chudak ,  Mani Ranjbar

    IPC: G06F17/11

    CPC classification number: G06F17/11 ,  G06N99/002

    Abstract: Methods and systems represent constraint as an Ising model penalty function and a penalty gap associated therewith, the penalty gap separating a set of feasible solutions to the constraint from a set of infeasible solutions to the constraint; and determines the Ising model penalty function subject to the bounds on the programmable parameters imposed by the hardware limitations of the second processor, where the penalty gap exceeds a predetermined threshold greater than zero. Such may be employed to find quantum binary optimization problems and associated gap values employing a variety of techniques.

    Abstract translation: 方法和系统表示作为Ising模型惩罚函数的约束和与之相关联的惩罚差距，将一组可行解与约束的惩罚差距从一组不可行解解决定到约束; 并且确定Ising模型惩罚函数受到由第二处理器的硬件限制所强加的可编程参数的界限的影响，其中惩罚间隔超过大于零的预定阈值。 可以采用这种方法来找到采用各种技术的量子二进制优化问题和相关的间隙值。

    QUANTUM PROCESSOR BASED SYSTEMS AND METHODS THAT MINIMIZE A CONTINUOUS VARIABLE OBJECTIVE FUNCTION
    14.
    发明申请
    QUANTUM PROCESSOR BASED SYSTEMS AND METHODS THAT MINIMIZE A CONTINUOUS VARIABLE OBJECTIVE FUNCTION 有权
    基于量子处理器的系统和最小化连续可变目标函数的方法

    公开(公告)号：US20140344322A1

    公开(公告)日：2014-11-20

    申请号：US14280204

    申请日：2014-05-16

    Applicant: D-Wave Systems Inc.

    Inventor： Mani Ranjbar

    IPC: G06N99/00 ,  G06F1/02

    CPC classification number: G06N99/002 ,  B82Y10/00 ,  G06F17/11

    Abstract: Computational techniques for mapping a continuous variable objective function into a discrete variable objective function problem that facilitate determining a solution of the problem via a quantum processor are described. The modified objective function is solved by minimizing the cost of the mapping via an iterative search algorithm.

    Abstract translation: 描述了将连续变量目标函数映射到便于通过量子处理器确定问题的解的离散变量目标函数问题的计算技术。 通过迭代搜索算法最小化映射的成本来解决修改后的目标函数。

    Systems and methods for domain adaptation
    15.
    发明授权
    Systems and methods for domain adaptation 有权

    公开(公告)号：US11625612B2

    公开(公告)日：2023-04-11

    申请号：US16779035

    申请日：2020-01-31

    Applicant: D-WAVE SYSTEMS INC.

    Inventor： Arash Vahdat ,  Mani Ranjbar ,  Mehran Khodabandeh ,  William G. Macready ,  Zhengbing Bian

    IPC: G06N3/08 ,  G06N5/02 ,  G06N5/04 ,  G06N3/088 ,  G06N5/022 ,  G06N5/045

    Abstract: The domain adaptation problem is addressed by using the predictions of a trained model over both source and target domain to retain the model with the assistance of an auxiliary model and a modified objective function. Inaccuracy in the model's predictions in the target domain is treated as noise and is reduced by using a robust learning framework during retraining, enabling unsupervised training in the target domain. Applications include object detection models, where noise in retraining is reduced by explicitly representing label noise and geometry noise in the objective function and using the ancillary model to inject information about label noise.

    SYSTEMS AND METHODS FOR EMBEDDING GRAPHS USING SYSTOLIC ALGORITHMS
    16.
    发明申请
    SYSTEMS AND METHODS FOR EMBEDDING GRAPHS USING SYSTOLIC ALGORITHMS 有权

    公开(公告)号：US20220391744A1

    公开(公告)日：2022-12-08

    申请号：US17832327

    申请日：2022-06-03

    Applicant: D-WAVE SYSTEMS INC.

    Inventor： Kelly T.R. Boothby ,  Peter D. Spear ,  Mani Ranjbar

    IPC: G06N10/80 ,  G06N10/60

    Abstract: An accelerated version of a node-weighted path distance algorithm is implemented on a microprocessor coupled to a digital processor. The algorithm calculates an embedding of a source graph into a target graph (e.g., hardware graph of a quantum processor). The digital processor causes the microprocessor to send seeds to logic blocks with a corresponding node in the target graph contained in a working embedding of a node, compute a minimum distance to neighboring logic blocks from each seeded logic block, set the distance to neighboring logic blocks as the minimum distance plus the weight of the seeded logic block, increment the accumulator value by the weight of the seeded logic block, increment the accumulator value by the distance, determine the minimum distance logic block by computing the minimum accumulated value, compute distances to the minimum distance logic block; and read distances from all logic blocks into local memory.

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