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Classical boson sampling algorithms with superior performance to near-term experiments

机译:经典玻色子采样算法具有比近期实验更高的性能

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摘要

It is predicted that quantum computers will dramatically outperform their conventional counterparts. However, large-scale universal quantum computers are yet to be built. Boson sampling is a rudimentary quantum algorithm tailored to the platform of linear optics, which has sparked interest as a rapid way to demonstrate this quantum supremacy. Photon statistics are governed by intractable matrix functions, which suggests that sampling from the distribution obtained by injecting photons into a linear-optical network could be solved more quickly by a photonic experiment than by a classical computer. The apparently low resource requirements for large boson sampling experiments have raised expectations of a near-term demonstration of quantum supremacy by boson sampling. Here we present classical boson sampling algorithms and theoretical analyses of prospects for scaling boson sampling experiments, showing that near-term quantum supremacy via boson sampling is unlikely. Our classical algorithm, based on Metropolised independence sampling, allowed the boson sampling problem to be solved for 30 photons with standard computing hardware. Compared to current experiments, a demonstration of quantum supremacy over a successful implementation of these classical methods on a supercomputer would require the number of photons and experimental components to increase by orders of magnitude, while tackling exponentially scaling photon loss.
机译:可以预见,量子计算机将大大优于传统计算机。但是,尚未建立大规模的通用量子计算机。玻色子采样是针对线性光学平台量身定做的基本量子算法,已引起人们的兴趣,作为证明这种量子至上性的快速方法。光子统计受不可解的矩阵函数支配,这表明通过光子实验比通过传统计算机更快地解决从通过将光子注入线性光学网络中获得的分布进行采样的问题。大型玻色子采样实验所需的资源显然很低,因此人们期望可以通过玻色子采样在近期证明量子霸权。在这里,我们介绍经典的玻色子采样算法和对按比例缩放玻色子采样实验前景的理论分析,表明通过玻色子采样实现近期量子至上性的可能性很小。我们基于大都市独立采样的经典算法允许使用标准计算硬件解决30个光子的玻色子采样问题。与当前的实验相比,在超级计算机上成功实现这些经典方法的量子至上论证将要求光子和实验组件的数量增加一个数量级,同时以指数方式应对光子损失。

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