Variational quantum unsampling on a quantum photonic processor
Variational quantum unsampling on a quantum photonic processor
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DOI：
10.1038/s41567-019-0747-6
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发表时间：
2020-01-13
期刊：
影响因子：
19.6
通讯作者：
Englund, Dirk
中科院分区：
文献类型：
--
作者：
Carolan, Jacques;Mohseni, Masoud;Englund, Dirk
变分量子去采样协议提供了一种实现量子电路近期输出的验证和推断的方法。该协议在量子光子处理器上得到了实验验证。一个有希望的途径是在有噪声的中等规模量子机器上运行定制的量子算法，以证明近期量子优于经典系统。这些算法通常涉及从概率分布中采样，而在合理的复杂性理论假设下，这些概率分布不能有效地产生经典的结果。而不是确定由一个给定的物理系统产生的输出状态的计算功能，我们调查的生成系统的功能可以有效地学习给定的直接访问输出状态。为了解决这个问题，在这里，我们介绍了变分量子采样协议，一种非线性量子神经网络方法，用于验证和推断近期量子电路输出。在我们的方法中，人们可以变分地训练量子操作来解开未知幺正对已知输入状态的作用，本质上是学习黑盒量子动力学的逆。虽然我们的方法的原理是平台无关的，但其实现将取决于特定量子处理器的独特架构。我们在量子光子处理器上对变分量子反采样协议进行了实验验证。除了量子验证之外，我们的协议还具有广泛的应用，包括最佳量子测量和断层扫描，量子传感和成像以及验证。
The variational quantum unsampling protocol provides a way to realize verification and inference of near-term quantum circuit outputs. This protocol is then experimentally verified on a quantum photonic processor.A promising route towards the demonstration of near-term quantum advantage (or supremacy) over classical systems relies on running tailored quantum algorithms on noisy intermediate-scale quantum machines. These algorithms typically involve sampling from probability distributions that-under plausible complexity-theoretic conjectures-cannot be efficiently generated classically. Rather than determining the computational features of output states produced by a given physical system, we investigate what features of the generating system can be efficiently learnt given direct access to an output state. To tackle this question, here we introduce the variational quantum unsampling protocol, a nonlinear quantum neural network approach for verification and inference of near-term quantum circuit outputs. In our approach, one can variationally train a quantum operation to unravel the action of an unknown unitary on a known input state, essentially learning the inverse of the black-box quantum dynamics. While the principle of our approach is platform independent, its implementation will depend on the unique architecture of a specific quantum processor. We experimentally demonstrate the variational quantum unsampling protocol on a quantum photonic processor. Alongside quantum verification, our protocol has broad applications, including optimal quantum measurement and tomography, quantum sensing and imaging, and ansatz validation.