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用量子计算优势与可编程光子处理器。

Quantum computational advantage with a programmable photonic processor.

机构信息

Xanadu, Toronto, ON, Canada.

National Institute of Standards and Technology, Boulder, CO, USA.

出版信息

Nature. 2022 Jun;606(7912):75-81. doi: 10.1038/s41586-022-04725-x. Epub 2022 Jun 1.

Abstract

A quantum computer attains computational advantage when outperforming the best classical computers running the best-known algorithms on well-defined tasks. No photonic machine offering programmability over all its quantum gates has demonstrated quantum computational advantage: previous machines were largely restricted to static gate sequences. Earlier photonic demonstrations were also vulnerable to spoofing, in which classical heuristics produce samples, without direct simulation, lying closer to the ideal distribution than do samples from the quantum hardware. Here we report quantum computational advantage using Borealis, a photonic processor offering dynamic programmability on all gates implemented. We carry out Gaussian boson sampling (GBS) on 216 squeezed modes entangled with three-dimensional connectivity, using a time-multiplexed and photon-number-resolving architecture. On average, it would take more than 9,000 years for the best available algorithms and supercomputers to produce, using exact methods, a single sample from the programmed distribution, whereas Borealis requires only 36 μs. This runtime advantage is over 50 million times as extreme as that reported from earlier photonic machines. Ours constitutes a very large GBS experiment, registering events with up to 219 photons and a mean photon number of 125. This work is a critical milestone on the path to a practical quantum computer, validating key technological features of photonics as a platform for this goal.

摘要

当量子计算机在执行定义明确的任务时,在运行最佳经典算法方面表现优于最佳经典计算机时,就会获得计算优势。没有光子机器可以对所有量子门进行可编程性,从而展示出量子计算优势:以前的机器在很大程度上仅限于静态门序列。以前的光子演示也容易受到欺骗,在欺骗中,经典启发式算法会产生样本,而无需直接模拟,这些样本比来自量子硬件的样本更接近理想分布。在这里,我们使用提供所有门可编程性的光子处理器 Borealis 报告了量子计算优势。我们使用时分复用和光子数分辨架构对与三维连接纠缠的 216 个压缩模式进行了高斯玻色抽样(GBS)。平均而言,使用最佳可用算法和超级计算机通过精确方法从编程分布中生成单个样本需要超过 9000 年的时间,而 Borealis 仅需要 36μs。与之前的光子机器相比,这种运行时优势超过了 5000 万倍。我们的实验是一个非常大的 GBS 实验,记录了多达 219 个光子和平均 125 个光子的事件。这项工作是实现实用量子计算机道路上的一个关键里程碑,验证了光子学作为实现这一目标的平台的关键技术特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b98f/9159949/f1673c6ad2cb/41586_2022_4725_Fig1_HTML.jpg

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