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Chin. Phys. B, 2018, Vol. 27(2): 020308    DOI: 10.1088/1674-1056/27/2/020308
Special Issue: TOPICAL REVIEW — Solid-state quantum information processing
TOPICAL REVIEW—Solid-state quantum information processing Prev   Next  

Nuclear magnetic resonance for quantum computing: Techniques and recent achievements

Tao Xin(辛涛)1, Bi-Xue Wang(王碧雪)1, Ke-Ren Li(李可仁)1, Xiang-Yu Kong(孔祥宇)1, Shi-Jie Wei(魏世杰)1, Tao Wang(王涛)1, Dong Ruan(阮东)1, Gui-Lu Long(龙桂鲁)1,2,3
1. State Key Laboratory of Low-dimensional Quantum Physics and Department of Physics, Tsinghua University, Beijing 100084, China;
2. The Innovative Center of Quantum Matter, Beijing 100084, China;
3. Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China
Abstract  

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.

Keywords:  nuclear magnetic resonance      quantum control techniques      machine learning      topological quantum computing  
Received:  21 November 2017      Revised:  14 January 2018      Accepted manuscript online: 
PACS:  03.65.-w (Quantum mechanics)  
  03.67.Ac (Quantum algorithms, protocols, and simulations)  
  03.67.Lx (Quantum computation architectures and implementations)  
Fund: 

Project supported by the National Natural Science Foundation of China (Grants Nos. 11175094 and 91221205) and the National Basic Research Program of China (Grant No. 2015CB921002).

Corresponding Authors:  Gui-Lu Long     E-mail:  gllong@mail.tsinghua.edu.cn
About author:  03.65.-w; 03.67.Ac; 03.67.Lx

Cite this article: 

Tao Xin(辛涛), Bi-Xue Wang(王碧雪), Ke-Ren Li(李可仁), Xiang-Yu Kong(孔祥宇), Shi-Jie Wei(魏世杰), Tao Wang(王涛), Dong Ruan(阮东), Gui-Lu Long(龙桂鲁) Nuclear magnetic resonance for quantum computing: Techniques and recent achievements 2018 Chin. Phys. B 27 020308

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