Theory versus practice in annealing-based quantum computing
Theory versus practice in annealing-based quantum computing
复制标题
DOI：
10.1016/j.tcs.2020.01.024
复制
发表时间：
2020-05-06
影响因子：
1.1
通讯作者：
McGeoch, Catherine C.
中科院分区：
文献类型：
--
作者：
McGeoch, Catherine C.
本文介绍了基于退火的量子计算（也称为绝热量子计算（AQC）和量子退火（QA））的基本概念，并调查了有关这种新颖计算范式的已知信息。对 D-Wave Systems 构建的物理量子退火处理器进行的广泛实证研究揭示了许多有趣的特征和特性。然而，由于计算性能研究的抽象方法和经验方法之间长期存在差异，这项工作的大部分内容可能被认为与复杂性理论感兴趣的问题无关。出于同样的原因，量子计算中的一些理论结果可能被认为与实践经验无关。为了解决这种沟通差距，本文提出了位于纸笔抽象和物理设备之间的实例化规模的计算和算法模型。这些尺度的中间点模型可以提供通用语言，使两端的研究人员能够交流和分享他们的结果。本文还给出了几个常见术语的例子，这些术语在这个高度多学科领域的不同领域具有不同的技术含义，这可能会给跨学科的有效沟通造成障碍。 (C) 2020 Elsevier B.V. 保留所有权利。
This paper introduces basic concepts of annealing-based quantum computing, also known as adiabatic quantum computing (AQC) and quantum annealing (QA), and surveys what is known about this novel computing paradigm. Extensive empirical research on physical quantum annealing processers built by D-Wave Systems has exposed many interesting features and properties. However, because of longstanding differences between abstract and empirical approaches to the study of computational performance, much of this work may not be considered relevant to questions of interest to complexity theory; by the same token, several theoretical results in quantum computing may be considered irrelevant to practical experience.To address this communication gap, this paper proposes models of computation and of algorithms that lie on a scale of instantiation between pencil-and-paper abstraction and physical device. Models at intermediate points on these scales can provide a common language, allowing researchers from both ends to communicate and share their results. The paper also gives several examples of common terms that have different technical meanings in different regions of this highly multidisciplinary field, which can create barriers to effective communication across disciplines. (C) 2020 Elsevier B.V. All rights reserved.