期刊文献+
共找到3篇文章
< 1 >
每页显示 20 50 100
Nuclear magnetic resonance for quantum computing: Techniques and recent achievements 被引量:1
1
作者 辛涛 王碧雪 +5 位作者 李可仁 孔祥宇 魏世杰 王涛 阮东 龙桂鲁 《Chinese Physics B》 SCIE EI CAS CSCD 2018年第2期154-165,共12页
Rapid developments in quantum information processing have been made, and remarkable achievements have been obtained in recent years, both in theory and experiments. Coherent control of nuclear spin dynamics is a power... Rapid developments in quantum information processing have been made, and remarkable achievements have been obtained in recent years, both in theory and experiments. Coherent control of nuclear spin dynamics is a powerful tool for the experimental implementation of quantum schemes in liquid and solid nuclear magnetic resonance (NMR) system, especially in liquid-state NMR. Compared with other quantum information processing systems, the NMR platform has the advantages such as the long coherence time, the precise manipulation, and well-developed quantum control techniques, which make it possible to accurately control a quantum system with up to 12-qubits. Extensive applications of liquid-state NMR spectroscopy in quantum information processing such as quantum communication, quantum computing, and quantum simulation have been thoroughly studied over half a century. This article introduces the general principles of NMR quantum information processing, and reviews the new-developed techniques. The review will also include the recent achievements of the experimental realization of quantum algorithms for machine learning, quantum simulations for high energy physics, and topological order in NMR. We also discuss the limitation and prospect of liquid-state NMR spectroscopy and the solid-state NMR systems as quantum computing in the article. 展开更多
关键词 nuclear magnetic resonance quantum control techniques machine learning topological quantumcomputing
原文传递
Quantum hyperentanglement and its applications in quantum information processing 被引量:13
2
作者 Fu-Guo Deng Bao-Cang Ren Xi-Han Li 《Science Bulletin》 SCIE EI CAS CSCD 2017年第1期46-68,共23页
Hyperentanglement is a promising resource in quantum information processing with its high capacity character, defined as the entanglement in multiple degrees of freedom(DOFs) of a quantum system, such as polarization,... Hyperentanglement is a promising resource in quantum information processing with its high capacity character, defined as the entanglement in multiple degrees of freedom(DOFs) of a quantum system, such as polarization, spatial-mode, orbit-angular-momentum, time-bin and frequency DOFs of photons.Recently, hyperentanglement attracts much attention as all the multiple DOFs can be used to carry information in quantum information processing fully. In this review, we present an overview of the progress achieved so far in the field of hyperentanglement in photon systems and some of its important applications in quantum information processing, including hyperentanglement generation, complete hyperentangled-Bell-state analysis, hyperentanglement concentration, and hyperentanglement purification for high-capacity long-distance quantum communication. Also, a scheme for hyper-controlled-not gate is introduced for hyperparallel photonic quantum computation, which can perform two controlled-not gate operations on both the polarization and spatial-mode DOFs and depress the resources consumed and the photonic dissipation. 展开更多
关键词 Quantum hyperentanglement High-capacity quantum communication Concentration and purification Hyperparallel photonic quantumcomputation Quantum information processing
原文传递
Quantum-inspired bacterial foraging algorithm for parameter adjustment in green cognitive radio 被引量:5
3
作者 Hongyuan Gao Chenwan Li 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2015年第5期897-907,共11页
Parameter adjustment that maximizes the energy efficiency of cognitive radio networks is studied in this paper where it can be investigated as a complex discrete optimization problem. Then a quantum-inspired bacterial... Parameter adjustment that maximizes the energy efficiency of cognitive radio networks is studied in this paper where it can be investigated as a complex discrete optimization problem. Then a quantum-inspired bacterial foraging algorithm(QBFA)is proposed. Quantum computing has perfect characteristics so as to avoid local convergence and speed up the optimization of QBFA. A proof of convergence is also given for this algorithm.The superiority of QBFA is verified by simulations on three test functions. A novel parameter adjustment method based on QBFA is proposed for resource allocation of green cognitive radio. The proposed method can provide a globally optimal solution for parameter adjustment in green cognitive radio networks. Simulation results show the proposed method can reduce energy consumption effectively while satisfying different quality of service(Qo S)requirements. 展开更多
关键词 green cognitive radio parameter adjustment quantumcomputing bacterial foraging algorithm
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部