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Quantum simulation and quantum computation of noisy-intermediate scale
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作者 Kai Xu Heng Fan 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第10期1-7,共7页
In the past years, great progresses have been made on quantum computation and quantum simulation. Increasing the number of qubits in the quantum processors is expected to be one of the main motivations in the next yea... In the past years, great progresses have been made on quantum computation and quantum simulation. Increasing the number of qubits in the quantum processors is expected to be one of the main motivations in the next years, while noises in manipulation of quantum states may still be inevitable even the precision will improve. For research in this direction, it is necessary to review the available results about noisy multiqubit quantum computation and quantum simulation. The review focuses on multiqubit state generations, quantum computational advantage, and simulating physics of quantum many-body systems. Perspectives of near term noisy intermediate-quantum processors will be discussed. 展开更多
关键词 quantum computation quantum simulation many-body physics quantum supremacy noisy intermediate-scale quantum technologies
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面向含噪中规模量子处理器的量子机器学习 被引量:1
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作者 石金晶 肖子萌 +2 位作者 王雯萱 张师超 李学龙 《计算机学报》 北大核心 2025年第3期602-631,共30页
量子计算与人工智能结合,在增强模型表达能力、加速和优化机器学习等方面可能产生颠覆性影响,有望突破人工智能领域所面临的可解释性差、最优解难等问题,量子人工智能已成为国内外重点关注的学科前沿。量子机器学习是量子人工智能领域... 量子计算与人工智能结合,在增强模型表达能力、加速和优化机器学习等方面可能产生颠覆性影响,有望突破人工智能领域所面临的可解释性差、最优解难等问题,量子人工智能已成为国内外重点关注的学科前沿。量子机器学习是量子人工智能领域的重要研究内容,它将量子计算基础理论与机器学习原理相结合,以实现具有量子加速的机器学习任务。随着量子计算软硬件的快速发展,含噪中规模量子(NISQ)处理器的学习优势被证明,国内外学者相继提出一系列量子机器学习方法,以挖掘量子计算助力人工智能技术发展的创新应用。然而,当前的量子机器学习仍局限于对算法的优化,缺乏系统层面的理论架构,仍有许多科学问题亟待解决。本文首先从量子机器学习系统表征角度出发,建立量子机器学习系统的层次模型,概括和总结了面向各类任务的量子机器学习方案,分析了量子机器学习在提高经典算法速度等方面可能体现的“量子优势”。接着根据量子机器学习系统的层次结构,从原理层、计算层、应用层这三个方面对现有量子机器学习方法进行了总结与梳理,系统性地分析和讨论了其中的关键问题与解决方案。最后,结合当前阶段量子人工智能的发展特点,重点分析了量子机器学习领域面临的科学问题与挑战,并对未来该领域的发展趋势进行了深入分析与展望。 展开更多
关键词 量子计算 量子人工智能 量子机器学习 量子算法 含噪中规模量子处理器
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An overview of quantum error mitigation formulas 被引量:2
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作者 Dayue Qin Xiaosi Xu Ying Li 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第9期1-12,共12页
Minimizing the effect of noise is essential for quantum computers.The conventional method to protect qubits against noise is through quantum error correction.However,for current quantum hardware in the so-called noisy... Minimizing the effect of noise is essential for quantum computers.The conventional method to protect qubits against noise is through quantum error correction.However,for current quantum hardware in the so-called noisy intermediate-scale quantum(NISQ)era,noise presents in these systems and is too high for error correction to be beneficial.Quantum error mitigation is a set of alternative methods for minimizing errors,including error extrapolation,probabilistic error cancella-tion,measurement error mitigation,subspace expansion,symmetry verification,virtual distillation,etc.The requirement for these methods is usually less demanding than error correction.Quantum error mitigation is a promising way of reduc-ing errors on NISQ quantum computers.This paper gives a comprehensive introduction to quantum error mitigation.The state-of-art error mitigation methods are covered and formulated in a general form,which provides a basis for comparing,combining and optimizing different methods in future work. 展开更多
关键词 quantum error mitigation quantum computing quantum error correction noisy intermediate-scale quantum
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Exact quantum algorithm for unit commitment optimization based on partially connected quantum neural networks
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作者 Jian Liu Xu Zhou +1 位作者 Zhuojun Zhou Le Luo 《Chinese Physics B》 2025年第10期303-312,共10页
The quantum hybrid algorithm has recently become a very promising and speedy method for solving larger-scale optimization problems in the noisy intermediate-scale quantum(NISQ)era.The unit commitment(UC)problem is a f... The quantum hybrid algorithm has recently become a very promising and speedy method for solving larger-scale optimization problems in the noisy intermediate-scale quantum(NISQ)era.The unit commitment(UC)problem is a fundamental problem in the field of power systems that aims to satisfy the power balance constraint with minimal cost.In this paper,we focus on the implementation of the UC solution using exact quantum algorithms based on the quantum neural network(QNN).This method is tested with a ten-unit system under the power balance constraint.In order to improve computing precision and reduce network complexity,we propose a knowledge-based partially connected quantum neural network(PCQNN).The results show that exact solutions can be obtained by the improved algorithm and that the depth of the quantum circuit can be reduced simultaneously. 展开更多
关键词 quantum computing quantum algorithm unit commitment quantum neural network noisy intermediate-scale quantum era
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Noise-resistant quantum state compression readout
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作者 Chen Ding Xiao-Yue Xu +3 位作者 Yun-Fei Niu Shuo Zhang Wan-Su Bao He-Liang Huang 《Science China(Physics,Mechanics & Astronomy)》 SCIE EI CAS CSCD 2023年第3期58-65,共8页
Qubit measurement is generally the most error-prone operation that degrades the performance of near-term quantum devices,and the exponential decay of readout fidelity severely impedes the development of large-scale qu... Qubit measurement is generally the most error-prone operation that degrades the performance of near-term quantum devices,and the exponential decay of readout fidelity severely impedes the development of large-scale quantum information processing.Given these disadvantages, we present a quantum state readout method, named compression readout, that naturally avoids large multi-qubit measurement errors by compressing the quantum state into a single qubit for measurement. Our method generally outperforms direct measurements in terms of accuracy, and the advantage grows with the system size. Moreover, because only one-qubit measurements are performed, our method requires solely a fine readout calibration on one qubit and is free of correlated measurement error, which drastically diminishes the demand for device calibration. These advantages suggest that our method can immediately boost the readout performance of near-term quantum devices and will greatly benefit the development of large-scale quantum computing. 展开更多
关键词 quantum compression readout qubit measurement error mitigation quantum computing noisy intermediate-scale quantum
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