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Phase Estimation Algorithm for Quantum States Classification with NISQ Devices

机译:NISQ设备量子状态分类的相位估计算法

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Methods of processing quantum data become more important as quantum computing devices improve their quality towards fault tolerant universal quantum computers. These methods include discrimination and filtering of quantum states given as an input to the device that may find numerous applications in quantum information technologies. In the present paper, we address a scheme of a classification of input states, which is nondestructive and deterministic for certain inputs, while probabilistic, in general case. This can be achieved by incorporating phase estimation algorithm into the hybrid quantum-classical computation scheme, where quantum block is trained classically. We perform proof-of-principle implementation of this idea using superconducting quantum processor of IBM Quantum Experience. Another aspect we are interested in is a mitigation of errors occurring due to the quantum device imperfections. We apply a series of heuristic tricks at the stage of classical postprocessing in order to improve raw experimental data and to recognize patterns in them. These ideas may find applications in other realization of hybrid quantum-classical computations with noisy quantum machines.
机译:随着量子计算设备提高其朝向容错通用量子计算机的质量,处理量子数据的方法变得更加重要。这些方法包括作为对Quantum信息技术中可能发现许多应用的设备给出的量子状态的辨别和过滤。在本文中,我们解决了输入状态分类的方案,这对于某些投入而言,对于某些投入而言,概率,通常情况。这可以通过将相位估计算法结合到混合量子 - 经典计算方案中,其中量子块经典训练。我们使用IBM量子体验的超导量子处理器执行本想法的原理证明。我们感兴趣的另一个方面是减轻由于量子器件缺陷因素而发生的错误。我们在经典后处理阶段应用一系列启发式技巧,以改善原始实验数据并识别它们的模式。这些想法可能会在其他具有嘈杂量子机器的混合量子古典计算的其他实现中找到应用。

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