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Amplitude Amplification for Operator Identification and Randomized Classes

机译:用于操作员识别和随机分类的振幅放大

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Amplitude amplification (AA) is tool of choice for quantum algorithm designers to increase the success probability of query algorithms that reads its input in the form of oracle gates. Geometrically speaking, the technique can be understood as rotation in a specific two-dimensional space. We study and use a generalized form of this rotation operator to design algorithms in a geometric manner. Specifically, we apply AA to algorithms that take their input in the form of input states and in which rotations with different angles and directions are used in a unified manner. We show that AA can be used to sequentially discriminate between two unitary operators, both without error and with bounded-error, in an asymptotically optimal manner. We also show how to reduce error probability in one and two-sided bounded error algorithms more efficiently than the usual parallel repetitions technique; in particular, errors can be completely eliminated from the exact error algorithms.
机译:幅度放大(AA)是量子算法设计人员选择的工具,可以提高以oracle门形式读取其输入的查询算法的成功概率。从几何学上讲,该技术可以理解为在特定二维空间中的旋转。我们研究并使用此旋转算子的广义形式以几何方式设计算法。具体来说,我们将AA应用于以输入状态形式输入其输入并以统一的方式使用不同角度和方向的旋转的算法。我们证明了AA可以渐近最优的方式用于顺序地区分两个unit运算符,既无错误又有界错误。我们还展示了如何比通常的并行重复技术更有效地降低一面和两面有界错误算法中的错误概率;特别是,可以从精确的错误算法中完全消除错误。

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