Quantum information processing in electrically defined Silicon triple quantum dot systems

IF 1.4 4区 物理与天体物理 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Ji-Hoon Kang, Hoon Ryu
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引用次数: 0

Abstract

Quantum bits (qubits) operations in electrically defined Silicon (Si) triple quantum dots (TQDs) are computationally investigated to elevate the potential of TQD structure as a platform for quantum information processing. Employing a realistic Si/Si-germanium heterostructure as a target model, device simulations are conducted to secure an initialized qubit state. Basic programmability is verified through implementation of individual qubit operations and 2-qubit entangling operations between neighboring QDs. Constructing a gate sequence composed of 1-qubit and 2-qubit blocks, then, we not only generate three-qubit Greenberger–Horne–Zeilinger state, but also quantify the degradation of state fidelity under the inevitable inaccuracy which are incorporated in the dominant factors of spin-qubit Hamiltonian. Presenting engineering details that are hard to be carried by simulations based on the first principle theory, this work can be served as a practical guideline for designs of scalable quantum processors with electron spin-qubits in Si QD platforms.

电定义硅三量子点系统中的量子信息处理
对电学定义的硅(Si)三量子点(TQDs)中的量子比特(qubit)操作进行了计算研究,以提升 TQD 结构作为量子信息处理平台的潜力。以现实中的硅/硅锗异质结构为目标模型,进行了器件仿真,以确保初始化量子比特状态。通过实现单个量子比特操作和相邻 QD 之间的双量子比特纠缠操作,验证了基本的可编程性。通过构建由 1 量子位和 2 量子位块组成的门序列,我们不仅生成了三量子位格林伯格-霍恩-蔡林格状态,还量化了状态保真度在不可避免的误差下的衰减情况,这些误差被纳入自旋量子位哈密顿的主导因子中。这项工作提出了基于第一原理理论的模拟难以实现的工程细节,可作为在硅 QD 平台上设计具有电子自旋量子比特的可扩展量子处理器的实用指南。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Solid-state Electronics
Solid-state Electronics 物理-工程:电子与电气
CiteScore
3.00
自引率
5.90%
发文量
212
审稿时长
3 months
期刊介绍: It is the aim of this journal to bring together in one publication outstanding papers reporting new and original work in the following areas: (1) applications of solid-state physics and technology to electronics and optoelectronics, including theory and device design; (2) optical, electrical, morphological characterization techniques and parameter extraction of devices; (3) fabrication of semiconductor devices, and also device-related materials growth, measurement and evaluation; (4) the physics and modeling of submicron and nanoscale microelectronic and optoelectronic devices, including processing, measurement, and performance evaluation; (5) applications of numerical methods to the modeling and simulation of solid-state devices and processes; and (6) nanoscale electronic and optoelectronic devices, photovoltaics, sensors, and MEMS based on semiconductor and alternative electronic materials; (7) synthesis and electrooptical properties of materials for novel devices.
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