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11.发明申请QUANTUM PROCESSOR BASED SYSTEMS AND METHODS THAT MINIMIZE AN OBJECTIVE FUNCTION 审中-公开基于量子处理器的系统和最小化目标函数的方法公开(公告)号：US20160042294A1
公开(公告)日：2016-02-11
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
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.
Abstract translation: 基于量子处理器的技术例如通过将量子处理器作为从具有高概率的概率分布提供低能量样本的样本发生器来操作来最小化目标函数。 概率分布的形状是根据相应的目标函数值为样本分配相对概率，直到样本收敛到目标函数的最小值为止。 可以解决具有与量子处理器不匹配的变量之间的多个变量和/或连接性的问题。 与量子处理器的交互可以通过数字计算机。 数字计算机存储分层堆栈的软件模块，以便于通过各种级别的编程环境从机器语言级别到最终使用应用级别与量子处理器进行交互。
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公开(公告)号：US20220092152A1
公开(公告)日：2022-03-24
申请号：US17533384
申请日：2021-11-23
Applicant: D-WAVE SYSTEMS INC.
Inventor： Firas Hamze , James King , Evgeny Andriyash , Catherine McGeoch , Jack Raymond , Jason Rolfe , William G. Macready , Aaron Lott , Murray C. Thom
Abstract: The systems, devices, articles, and methods generally relate to sampling from an available probability distribution. The samples may be used to create a desirable probability distribution, for instance for use in computing values used in computational techniques including: Importance Sampling and Markov chain Monte Carlo systems. An analog processor may operate as a sample generator, for example by: programming the analog processor with a configuration of the number of programmable parameters for the analog processor, which corresponds to a probability distribution over qubits of the analog processor, evolving the analog processor, and reading out states for the qubits. The states for the qubits in the plurality of qubits correspond to a sample from the probability distribution. Operation of the sampling device may be summarized as including updating a set of samples to include the sample from the probability distribution, and returning the set of 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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公开(公告)号：US20150161524A1
公开(公告)日：2015-06-11
申请号：US14561086
申请日：2014-12-04
Applicant: D-Wave Systems Inc.
Inventor： Firas Hamze
Abstract: The techniques and structures described herein generally relate to sampling from an available probability distribution to create a desirable probability distribution. This resultant distribution can be used for computing values used in computational techniques including: Importance Sampling and Markov chain Monte Carlo systems.
Abstract translation: 本文描述的技术和结构通常涉及从可用概率分布中的采样以创建期望的概率分布。 该结果分布可用于计算技术中使用的计算值，包括：重要性抽样和马尔可夫链蒙特卡洛系统。
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