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量子处理器中量子比特数字误差的半经典分析导论

Introduction to Semi-Classical Analysis for Digital Errors of Qubit in Quantum Processor.

作者信息

Hirota Osamu

机构信息

Quantum ICT Research Institute, Tamagawa University, Tokyo 194-8610, Japan.

Reserch and Development Initiative, Chuo University, Tokyo 112-8551, Japan.

出版信息

Entropy (Basel). 2021 Nov 26;23(12):1577. doi: 10.3390/e23121577.

DOI:10.3390/e23121577
PMID:34945882
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8700742/
Abstract

In recent years, remarkable progress has been achieved in the development of quantum computers. For further development, it is important to clarify properties of errors by quantum noise and environment noise. However, when the system scale of quantum processors is expanded, it has been pointed out that a new type of quantum error, such as nonlinear error, appears. It is not clear how to handle such new effects in information theory. First of all, one should make the characteristics of the error probability of qubits clear as communication channel error models in information theory. The purpose of this paper is to survey the progress for modeling the quantum noise effects that information theorists are likely to face in the future, to cope with such nontrivial errors mentioned above. This paper explains a channel error model to represent strange properties of error probability due to new quantum noise. By this model, specific examples on the features of error probability caused by, for example, quantum recurrence effects, collective relaxation, and external force, are given. As a result, it is possible to understand the meaning of strange features of error probability that do not exist in classical information theory without going through complex physical phenomena.

摘要

近年来,量子计算机的发展取得了显著进展。为了进一步发展,明确量子噪声和环境噪声引起的误差特性非常重要。然而,当量子处理器的系统规模扩大时,有人指出会出现一种新型的量子误差,比如非线性误差。在信息论中,尚不清楚如何处理这种新效应。首先,应将量子比特的误差概率特性明确为信息论中的通信信道误差模型。本文的目的是综述信息理论学家未来可能面临的对量子噪声效应进行建模的进展,以应对上述这类非平凡误差。本文解释了一种信道误差模型,以表征由新的量子噪声导致的误差概率的奇特特性。通过该模型,给出了例如量子递归效应、集体弛豫和外力等引起的误差概率特征的具体示例。结果,无需经历复杂的物理现象,就有可能理解经典信息论中不存在的误差概率奇特特征的含义。

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