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不公平量子基态采样的优势。

Advantages of Unfair Quantum Ground-State Sampling.

作者信息

Zhang Brian Hu, Wagenbreth Gene, Martin-Mayor Victor, Hen Itay

机构信息

Stanford University, Stanford, California, 94305, USA.

Cray, Seattle, WA 98164, USA.

出版信息

Sci Rep. 2017 Apr 21;7(1):1044. doi: 10.1038/s41598-017-01096-6.

Abstract

The debate around the potential superiority of quantum annealers over their classical counterparts has been ongoing since the inception of the field. Recent technological breakthroughs, which have led to the manufacture of experimental prototypes of quantum annealing optimizers with sizes approaching the practical regime, have reignited this discussion. However, the demonstration of quantum annealing speedups remains to this day an elusive albeit coveted goal. We examine the power of quantum annealers to provide a different type of quantum enhancement of practical relevance, namely, their ability to serve as useful samplers from the ground-state manifolds of combinatorial optimization problems. We study, both numerically by simulating stoquastic and non-stoquastic quantum annealing processes, and experimentally, using a prototypical quantum annealing processor, the ability of quantum annealers to sample the ground-states of spin glasses differently than thermal samplers. We demonstrate that (i) quantum annealers sample the ground-state manifolds of spin glasses very differently than thermal optimizers (ii) the nature of the quantum fluctuations driving the annealing process has a decisive effect on the final distribution, and (iii) the experimental quantum annealer samples ground-state manifolds significantly differently than thermal and ideal quantum annealers. We illustrate how quantum annealers may serve as powerful tools when complementing standard sampling algorithms.

摘要

自该领域创立以来,围绕量子退火器相对于经典退火器潜在优势的争论就一直存在。最近的技术突破使得制造出尺寸接近实际应用的量子退火优化器实验原型,这再次引发了这场讨论。然而,量子退火加速的证明至今仍是一个难以实现却令人向往的目标。我们研究量子退火器提供一种具有实际相关性的不同类型量子增强的能力,即它们作为组合优化问题基态流形有用采样器的能力。我们通过模拟随机和非随机量子退火过程进行数值研究,并使用原型量子退火处理器进行实验研究,探究量子退火器与热采样器相比对自旋玻璃基态进行采样的能力。我们证明:(i)量子退火器对自旋玻璃基态流形的采样与热优化器非常不同;(ii)驱动退火过程的量子涨落性质对最终分布有决定性影响;(iii)实验量子退火器对基态流形的采样与热退火器和理想量子退火器有显著不同。我们说明了量子退火器在补充标准采样算法时如何可以成为强大工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bf5/5430793/d58d93ca145c/41598_2017_1096_Fig1_HTML.jpg

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