EFFICIENT SYNTHESIS OF PROBABILISTIC QUANTUM CIRCUITS WITH FALLBACK
    5.
    发明公开
    EFFICIENT SYNTHESIS OF PROBABILISTIC QUANTUM CIRCUITS WITH FALLBACK 有权
    具有倒退的概率量子电路的有效综合

    公开(公告)号:EP3192018A1

    公开(公告)日:2017-07-19

    申请号:EP15771828.9

    申请日:2015-09-11

    IPC分类号: G06N99/00 B82Y10/00

    摘要: A Probabilistic Quantum Circuit with Fallback (PQFs) is composed as a series of circuit stages that are selected to implement a target unitary. A final stage is conditioned on unsuccessful results of all the preceding stages as indicated by measurement of one or more ancillary qubits. This final stage executes a fallback circuit that enforces deterministic execution of the target unitary at a relatively high cost (mitigated by very low probability of the fallback). Specific instances of general PQF synthesis method and are disclosed with reference to the specific Clifford+T, Clifford+V and Clifford+π/12 bases. The resulting circuits have expected cost in logb(1/ε(log(log(1/ε)))+const wherein b is specific to each basis. The three specific instances of the synthesis have polynomial compilation time guarantees.

    摘要翻译: 具有后备的概率量子电路(PQF)由一系列电路级组成,这些级被选择用于实现目标单位。 如通过测量一个或多个辅助量子位所指示的,最后阶段以所有前面阶段的不成功结果为条件。 这个最后阶段执行一个回退电路,以相对高的成本强制执行目标幺正的确定性执行(通过非常低的回退概率来缓解)。 参考具体的Clifford + T,Clifford + V和Clifford +碱基公开了一般PQF合成方法的具体实例。 所得到的电路具有预期的成本,其中b是针对每个基准而特定的。 合成的三个特定实例具有多项式编译时间保证。

    QUANTUM DEEP LEARNING
    8.
    发明公开
    QUANTUM DEEP LEARNING 审中-公开
    量子深度学习

    公开(公告)号:EP3227837A1

    公开(公告)日:2017-10-11

    申请号:EP15813186.2

    申请日:2015-11-28

    IPC分类号: G06N99/00

    摘要: Boltzmann machines are trained using an objective function that is evaluated by sampling quantum states that approximate a Gibbs state. Classical processing is used to produce the objective function, and the approximate Gibbs state is based on weights and biases that are refined using the sample results. In some examples, amplitude estimation is used. A combined classical/quantum computer produces suitable weights and biases for classification of shapes and other applications.

    摘要翻译: 玻尔兹曼机器使用目标函数进行训练,该目标函数通过对量度状态进行采样来近似于吉布斯状态。 经典处理用于生成目标函数,而近似吉布斯状态基于使用样本结果进行优化的权重和偏差。 在一些示例中,使用幅度估计。 组合的经典/量子计算机为形状和其他应用的分类产生合适的权重和偏差。

    METHOD FOR EFFICIENT IMPLEMENTATION OF DIAGONAL OPERATORS OVER CLIFFORD+T BASIS
    10.
    发明公开
    METHOD FOR EFFICIENT IMPLEMENTATION OF DIAGONAL OPERATORS OVER CLIFFORD+T BASIS 审中-公开
    基于CLIFFORD T基的有效实现对角算子的方法

    公开(公告)号:EP3221822A1

    公开(公告)日:2017-09-27

    申请号:EP15801658.4

    申请日:2015-11-20

    IPC分类号: G06N99/00

    CPC分类号: G06N99/002 G06F17/505

    摘要: Quantum circuits and circuit designs are based on factorizations of diagonal unitaries using a phase context. The cost/complexity of phase sparse/phase dense approximations is compared, and a suitable implementation is selected. For phase sparse implementations in the Clifford+
    T basis, required entangling circuits are defined based on a number of occurrences of a phase in the phase context in a factor of the diagonal unitary.

    摘要翻译: 量子电路和电路设计基于使用相位上下文的对角单位的因式分解。 比较相稀疏/相密近似的成本/复杂性,并选择合适的实现。 对于Clifford + T基础中的相位稀疏实现,所需的纠缠电路是根据相位上下文中对角线单位因子中出现的相位数量来定义的。