WHO WE ARE

Spin Quantum Computing Laboratory was established in September 2017 and sponsored by the Department of Physics at Southern University of Science and Technology (SUSTech, 南方科技大学), Shenzhen Institute for Quantum Science and Engineering (SIQSE, 深圳市量子科学与工程研究院), and Peng Cheng Laboratory (鹏城实验室). We conduct research on spin-based quantum technologies and the applications in quantum computing, with the experimental platforms including nuclear magnetic resonance (NMR) and optically detected magnetic resonance (ODMR).

Although the team is young (all five faculty members were born after 1985), but it is very creative and productive. The team has published over 100 papers in quantum computing, including over 20 papers in Nature Physics, Physical Review Letters, Physical Review X, and npj Quantum Information. The team hosts grants for Thousand Talents Plan for Young Professional (青年千人计划), two General Programs (面上项目) and two Youth Programs (青年项目) of National Natural Science Foundation of China.

In our laboratory, there are many activities in daily life. Group eating, group singing, and group mountain-climbing are just the basic, and we are exploring more (escape room on the way!). If you wish to enjoy the quantum life to be a postdoc, graduate student or research assistant, welcome to join this harmonic family!

MEMBERS

Dawei Lu

Dawei Lu

Associate Professor

Research Interests:
1. Quantum information processing in nuclear and electron spin magnetic resonance systems.
2. Development of spin control techniques to achieve high-fidelity coherent control.
3. Benchmarks in large-scale systems.
4. Quantum simulation towards large-scale quantum systems.
5. Experimental realization of adiabatic quantum computing model.
6. Quantum state tomography and process tomography.

Email: [email protected]

Curriculum Vitae

Jun Li

Jun Li

Associate Professor

Research Interests:
1. Quantum system control,
2. quantum computation,
3. quantum thermalization,
4. spin dynamics,
5. nuclear magnetic resonance experiments

Email: [email protected]

Tao Xin

Tao Xin

Assistant Professor

Research Interests:
1. Spin-based quantum computing, algorithm, and simulation,
2. Efficient quantum state tomography and quantum entanglement detection,
3. R & D for Benchtop NMR

Email: [email protected]

Xinfang Nie

Xinfang Nie

Post-Doctoral Fellow

Yu Tian

Yu Tian

Ph.D. Student

Amandeep Singh

Amandeep Singh

Post-Doctoral Fellow

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Xiaodong Yang


Post-Doctoral Fellow

Xinyue Long

Xinyue Long

Ph.D. Student

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Hanyu Chen


Ph.D. Student

alumni

Ze Zhang


Ph.D. Student

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Xiangyu Wang


Graduate Student

Zidong Lin

Zidong Lin

Graduate Student

Chao Wei

Chao Wei

Graduate Student

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Bowen Shao


Graduate Student

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Liangyu Che


Ph.D. Student

Chudan Qiu

Chudan Qiu

Graduate Student

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Yunrui Ge


Graduate Student

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Hongfeng Liu


Graduate Student

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YuLei Huang


Graduate Student

Alumni

Ming Shi

Shimin Zhang

Research Assistant

Xiuzhu Zhao

Xiuzhu Zhao

Research Assistant

RESEARCH

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Quantum Control

We shall develop the general quantum control methods, and seek their practical applications to various quantum information processing experimental platforms.
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NMR

Among the various physical quantum computing platforms, nuclear magnetic resonance (NMR) has long decoherence time and the unrivalled degree control technology.
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Quantum Simulation

In our laboratory, we focus on the quantum simulation of several areas: the condensed matter physics, topological matter, high-energy physics and quantum chemistry et al.
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Spin Control in NV System

We pay attention to robust control in NV system, such like optimal control theory, geometric quantum control and control with dynamic decoupling.

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Benchtop NMR for quantum education

NMR platform has gained numerous applications in quantum algorithms, quantum simulations and quantum control techniques.

NEWS


Experimental Quantum Principal Component Analysis via Parametrized Quantum Circuits

The Institute of Quantum Science and Engineering and the Department of Physics at the Southern University of Science and Technology have recently made important progress in the research of quantum machine learning. Tao Xin, Jun Li, Dawei Lu and Ying Dong have implemented a quantum principal component analysis algorithm based on parameterized quantum circuits on a four qubits spin system based on the nuclear magnetic resonance (NMR) quantum computing platform. The article were published in the famous journal Physical Review Letters as “Experimental Quantum Principal Component Analysis Via Parameterized Quantum Circuits”.
Principal component analysis (PCA) is a common and time-consuming unsupervised learning algorithm in machine learning. This method uses orthogonal transformation to transform the observed data represented by linearly dependent variables into a few data represented by linearly independent variables. The linearly independent variables are called principal components. In 2014, Lloyd, Mohseni and Rebentros proposed the quantum principal component analysis algorithm (QPCA) and published it in the Nature Physics, which can accelerate the classical principal component analysis algorithm exponentially. However, the realization of this algorithm requires a large amount of experiment resources, resulting in the lack of experiment to proof for the proposed quantum principal component analysis.
Parameterized quantum circuits (PQC) usually consists of fixed gates (such as controlled NOTs) and adjustable gates (such as qubit rotations). PQC formalizes the target problem into a parametric optimization problem and uses a hybrid system of quantum and classical hardware to find approximate solutions. For example, the variable component eigen-solver (VQE) has been used to search for the ground state Hamiltonian of molecules. Therefore, the research team proposed a new quantum principal component algorithm based on parameterized quantum circuits, which can reduce the demands of a large number of experiment resources, so that the quantum principal component analysis can be implemented experimentally.
They applied the algorithm to face recognition, iteratively optimizing the PQC by using a classic-quantum hybrid control method, in which the objective function and gradient were measured on a quantum processor, parameters were stored and updated by classical computer. The quantum principal component analysis (QPCA) algorithm is implemented in a four qubits NMR quantum simulator.
This is the first time to implement the quantum principal component analysis (QPCA) algorithm by parameterized quantum circuits, which provides a new way for the theoretical and experimental application research of QPCA.
In this study, Tao Xin, an assistant researcher from the Quantum Research Institute, was the first author, Liangyu Che, a Ph.D. student from the Department of Physics, was the co-first author, and Jun Li, an associate researcher, and Dawei Lu, an associate professor from the Department of Physics, was the co-corresponding author. The research was also supported by the Ministry of Science and Technology, the National Natural Science Foundation of China, the Science and Technology Department of Guangdong Province, the Science and Technology Innovation Commission of Shenzhen Municipality, and Southern University of Science and Technology.

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Our group held a party on July 25, 2020

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A wonderful day in Huizhou on November 29, 2020

PUBLICATIONS

Preprints

(*: equal contributions; †: corresponding author)

  1. X. F. Nie*, X. R. Zhu*, C. Xi, X. Y. Long, Z. D. Lin, Y. Tian, C. D. Qiu, X. D. Yang, Y. Dong, J. Li†, T. Xin†, and D.W. Lu†, Experimental Realization of a Quantum Refrigerator Driven by Indefinite Causal Orders, arXiv:2011.12580 (2020).
  2. Y. C. Li*, T. Xin*, C. D. Qiu, K. R. Li, G. Q. Liu, J. Li, Y. D. Wan†, and D.W. Lu†, Dynamical-Invariantbased Holonomic Quantum Gates: Theory and Experiment, arXiv:2003.09848 (2020).
  3. X. F. Nie, Z. Zhang, X. Z. Zhao, X. Tao†, D.W. Lu†, and J. Li†, Detecting scrambling via statistical correlations between randomized measurements on an NMR quantum simulator, arXiv:1903.12237 (2019).

Refereed Papers

(*: equal contributions; †: corresponding author)

  1. T. Xin*, Y. S. Li*, Y. A. Fan, X. R. Zhu, Y. J. Zhang, X. F. Nie, J. Li†, Q. H. Liu†, and D.W. Lu†, Quantum Phases of Three-Dimensional Chiral Topological Insulators on a Spin Quantum Simulator, Phys. Rev. Lett. 125, 090502 (2020). arXiv
  2. X. F. Nie*, B. B. Wei*, X. Chen, Z. Zhang, X. Z. Zhao, C. D. Qiu, Y. Tian, Y. L. Ji, X. Tao†, D.W. Lu†, and J. Li†, Experimental Observation of Equilibrium and Dynamical Quantum Phase Transitions via Out-of-Time-Ordered Correlators, Phys. Rev. Lett. 124, 250601 (2020). arXiv
  3. H. Y. Wang, S. J. Wei, C. Zheng, X. Y. Kong, J. W. Wen, X. F. Nie, J. Li, D.W. Lu, and T. Xin†, Experimental simulation of the four-dimensional Yang-Baxter equation on a spin quantum simulator, Phys. Rev. A. 102, 012610 (2020).
  4. Y. M. Song*, Y. Tian*, Z. Y. Hu, F. F. Zhou, T. T. Xing, D.W. Lu, B. Chen†, Y. Wang, N. Y. Xu†, and J. F. Du†, Pulse-width-induced polarization enhancement of optically-pumped N-V electron spin in diamond, Photonics Research 8, 1289 (2020). arXiv
  5. T. Xin, X. F. Nie, X. Y. Kong, D.W. Lu†, and J. Li†, Quantum state tomography via a variational hybrid quantum-classical method, Phys. Rev. Applied 13, 024013 (2020). arXiv
  6. T. Xin, S. J. Wei, J. L. Cui, J. X. Xiao, I. Arrazola, L. Lamata, X. Y. Kong, D.W. Lu†, E. Solano, and G. L. Long†, Quantum algorithm for solving linear differential equations: Theory and experiment, Phys. Rev. A 101, 032307 (2020). arXiv
  7. T. Xin, S. R. Lu, N. P. Cao, G. Anikeeva, D.W. Lu, J. Li†, G. L. Long, and B. Zeng†, Local-measurementbased quantum state tomography via neural networks, accepted by npj Quantum Information (2019). arXiv.
  8. Y. Wang, W. T. Ji, Z. H. Chai, Y. H. Guo, M. Q. Wang, X. Y. Ye, P. Yu, L. Zhang, X. Qin, P. F. Wang, F. Z. Shi, X. Rong, D.W. Lu†, X. J. Liuy, and J. F. Du†, Experimental observation of dynamical bulk-surface correspondence for topological phases, accepted by Phys. Rev. A (2019). arXiv
  9. K. R. Li, Y. N. Li, M. X. Han, S. R. Lu, J. Zhou, D. Ruan, G. L. Long, Y. D. Wan†, D.W. Lu†, B. Zeng†, and R. Laflamme, Quantum Spacetime on a Quantum Simulator, Communications Physics 2, 122 (2019). arXiv
  10. J. Li†, Z. H. Luo, T. Xin, H. Y. Wang, D. Kribs, D. W. Lu†, B. Zeng†, and R. Laflamme, Experimental Im- plementation of Efficient Quantum Pseudorandomness on a 12-spin System, Phys. Rev. Lett. 123, 030502 (2019). arXiv
  11. W. Q. Zheng, H. Y. Wang, T. Xin, X. F. Nie†, D. W. Lu†, and J. Li†, Optimal Bounds on State Transfer Under Quantum Channels with Application to Spin System Engineering, Phys. Rev. A 100, 022313 (2019). arXiv
  12. Z. H. Luo, Y. Z. You, J. Li, C. M. Jian, D. W. Lu†, C. K. Xu, B. Zeng†, and R. Laflamme, Observing Fermion Pair Instability of the Sachdev-Ye-Kitaev Model on a Quantum Spin Simulator, npj Quantum Informa-
    tion
    5
    , 7 (2019). arXiv.
  13. K. R. Li∗, M. X. Han∗, D. X. Qu, Z. C. Huang, G. L. Long, Y. D. Wan†, D.W.Lu†, B. Zeng, and R. Laflamme, Measuring Holographic Entanglement Entropy on a Quantum Simulator, npj Quantum Information 5, 30 (2019). arXiv.
  14. G. R. Feng, F. Cho, H. Katiyar, J. Li, D. W. Lu, J. Baugh†, and R. Laflamme†, Closed-Loop Quantum Opti- mal Control in a Solid-State Two-Qubit System, Phys. Rev. A 98, 052341 (2018). arXiv.
  15. S. R. Lu∗, S. L. Huang∗, K. R. Li, J. Li†, J. X. Chen, D.W.Lu†, Z. F. Ji, Y. Shen, D. L. Zhou, and B. Zeng, A Separability-Entanglement Classifier via Machine Learning, Phys. Rev. A 98, 012315 (2018). arXiv.
  16. D. W. Lu†, Speeding up the “quantum” mountain climb, Front. Phys. 13, 130313 (2018).
  17. T. Xin, S. L. Huang, S. R. Lu, K. R. Li, Z. H. Luo, Z. Q. Yin, J. Li†, D.W.Lu†, G. L. Long†, B. Zeng, NM- RCloudQ: A Quantum Cloud Experience on a Nuclear Magnetic Resonance Quantum Computer, Sci. Bull. 63, 17 (2018). arXiv.

  1. D. W. Lu∗†, K. R. Li∗, J. Li∗, H. Katiyar, A. J. Park, G. R. Feng, T. Xin, H. Li, G. L. Long, A. Brodutch, J. Baugh, B. Zeng†, and R. Laflamme, Enhancing quantum control by bootstrapping a quantum processor of 12 qubits, npj Quantum Information 3, 45 (2017). arXiv.
  2. J. Li†, S. L. Huang†, Z. H. Luo, K. R. Li, D. W. Lu, and B. Zeng†, Optimal design of measurement settings for quantum-state-tomography experiments, Phys. Rev. A 96, 032307 (2017). arXiv.
  3. K. R. Li, Y. D. Wan, L. Y. Hung, T. Lan, G. L. Long, D. W. Lu†, B. Zeng, and R. Laflamme, Experimen- tal Identification of Non-Abelian Topological Orders on a Quantum Simulator, Phys. Rev. Lett. 118, 080502 (2017). arXiv
  4. K. R. Li, G. F. Long, H. Katiyar, T. Xin, G. R. Feng, D. W. Lu†, and R. Laflamme, Experimentally superpos- ing two pure states with partial prior knowledge, Phys. Rev. A 95, 022334 (2017). arXiv
  5. H. Katiyar†, A. Brodutch†, D. W. Lu†, and R. Laflamme†, Experimental violation of the LeggettĺCGarg in- equality in a three-level system, New J. Phys. 19, 023033 (2017). arXiv
  6. T. Xin∗, D. W. Lu∗, J. Klassen∗, N. K. Yu†, Z. F. Ji, J. X. Chen, X. Ma, G. L. Long, B. Zeng†, and R. Laflamme, Quantum state tomography via reduced density matrices, Phys. Rev. Lett. 118, 020401 (2017). arXiv
  7. G. R. Feng, B. Buonacorsi, J. J. Wallman, F. H. Cho, D. Park, T. Xin, D. W. Lu, J. Baugh, and R. Laflamme, Estimating the coherence of noise in quantum control of a solid-state qubit, Phys. Rev. Lett. 117, 260501 (2016). arXiv
  8. X. Rong, D. W. Lu, X. Kong, J. P. Geng, Y. Wang, F. Z. Shi, C. K. Duan, and J. F. Du†, Harnessing the pow- er of quantum systems based on spin magnetic resonance: from ensembles to single particles, invited review article, Advances in Physics: X 2, 125 (2016).
  9. H. Y. Wang, W. Q. Zheng, N. K. Yu, K. R. Li, D.W.Lu, T. Xin, C. Li, Z. F. Ji, D. Kribs, B. Zeng†, X. H. Peng†, and J. F. Du, Quantum state and process tomography via adaptive measurements, Sci. China Phys. Mech. Astron. 59, 100313 (2016). arXiv
  10. J. Li, D. W. Lu, Z. H. Luo, R. Laflamme, X. H. Peng†, and J. F. Du†, Approximation of reachable set for co- herently controlled open quantum systems: application to quantum state engineering, Phys. Rev. A 94, 012312 (2016). arXiv
  11. D. W. Lu∗, T. Xin∗, N. K. Yu∗, Z. F. Ji, J. X. Chen, G. L. Long, J. Baugh, X. H. Peng, B. Zeng†, and R. Laflamme, Tomography is necessary for universal entanglement detection with single-copy observables, Phys. Rev. Lett. 116, 230501 (2016). arXiv
  12. A. J. Park†, E. McKay, D. W. Lu†, and R. Laflamme, Simulation of anyonic statistics and its topological path independence using a 7-qubit quantum simulator, New J. Phys. 18, 043043 (2016). arXiv
  13. D. W. Lu†, J. Biamonte, J. Li, H. Li, T. Johnson, V. Bergholm, M. Faccin, Z. Zimbora ́s, R. Laflamme, J. Baugh, and S. Lloyd, Chiral quantum walks, Phys. Rev. A 93, 042302 (2016). arXiv
  14. X. Ma, T. Jackson, H. Zhou, J. X. Chen, D. W. Lu, M. D. Mazurek, K. A. G. Fisher, X. H. Peng, D. Kribs, K. J. Resch, Z. F. Ji, B. Zeng†, and R. Laflamme, Pure-state tomography with the expectation value of Pauli operators, Phys. Rev. A 93, 032140 (2016). arXiv
  15. D. W. Lu, H. Li, D. Trottier, J. Li, A. Brodutch, A. P. Krismanich, A. Ghavami, G. I. Dmitrienko, G. Long, J. Baugh, and R. Laflamme†, Experimental estimation of average fidelity of a Clifford gate on a 7-qubit quan- tum processor, Phys. Rev. Lett. 114, 140505 (2015). arXiv
  16. Z. K. Li, H. Zhou, C. Y. Ju, H. W. Chen, W. Q. Zheng, D.W.Lu, X. Rong, C. K. Duan, X. H. Peng†, and J. F. Du†, Experimental realization of a compressed quantum simulation of a 32-spin Ising chain, Phys. Rev. Lett. 112, 220501 (2014).
  17. D. W. Lu, A. Brodutch†, J. Li, H. Li, and R. Laflamme†, Experimental realization of post-selected weak mea- surements on an NMR quantum processor, New J. Phys. 16, 053015 (2014). arXiv
  18. D.W.Lu, B. R. Xu, N. Y. Xu, Z. K. Li, H. W. Chen, X. H. Peng, R. X. Xu, and J. F. Du†, Quantumchem- istry simulation on quantum computers: theories and experiments, Phys. Chem. Chem. Phys. Perspective 14, 9411 (2012).
  19. D.W.Lu, N. Y. Xu, B. R. Xu, Z. K. Li, H. W. Chen, X. H. Peng, R. X. Xu, and J. F. Du†, Experimentals- tudy of quantum simulation for quantum chemistry with a nuclear magnetic resonance simulator, Phil. Trans. R. Soc. A 370, 4734 (2012).
  20. N. Y. Xu, J. Zhu, D. W. Lu, X. Y. Zhou, X. H. Peng†, and J. F. Du†, Quantum factorization of 143 on a dipolar-coupling NMR system, Phys. Rev. Lett. 108, 130501 (2012). arXiv
  1. Z. K. Li∗, M. H. Yung∗, H. W. Chen, D. W. Lu, J. D. Whitfield, X. H. Peng, A. Aspuru-Guzik, and J. F. Du†, Solving quantum ground-state problems with nuclear magnetic resonance, Sci. Rep. 1, 88 (2011). arXiv
  2. D. W. Lu, N. Y. Xu, R. X. Xu, H. W. Chen, J. B. Gong, X. H. Peng, and J. F. Du†, Simulation of chemical isomerization reaction dynamics on a NMR quantum simulator, Phys. Rev. Lett. 107, 020501 (2011). arXiv
  3. H. W. Chen, D. W. Lu, B. Chong, G. Qin, X. Y. Zhou, X. H. Peng†, and J. F. Du†, Experimental demonstra- tion of probabilistic quantum cloning, Phys. Rev. Lett. 106, 180404 (2011). arXiv
  4. D. W. Lu, J. Zhu, P. Zhou, X. H. Peng, Y. H. Yu, S. M. Zhang, Q. Chen, and J. F. Du†, Experimental imple- mentation of a quantum random-walk search algorithm using strongly dipolar coupled spins, Phys. Rev. A 81, 022308 (2010).
  5. J. F. Du†, N. Y. Xu, X. H. Peng, P. F. Wang, S. F. Wu, and D. W. Lu, NMR implementation of a molecular hydrogen quantum simulation with adiabatic state preparation, Phys. Rev. Lett. 104, 030502 (2010). arXiv
  6. C. L. Ren, D. W. Lu, X. H. Peng, M. J. Shi, and J. F. Du†, Experimentally simulating the violation of Bell-type inequalities for generalized GHZ states, Phys. Lett. A 373, 46, 4222-4226 (2009).

Book Chapters

  1. D. W. Lu, A. Brodutch, J. Park, H. Katiyar, T. Jochym-O’Connor, and R. Laflamme, NMR quantum infor- mation processing, Electron Spin Resonance (ESR) Based Quantum Computing (Springer Publishing, 2016). arXiv; order the book
  2. J. F. Du, C. Lei, G. Qin, D. W. Lu, and X. H. Peng, Search via quantum walk, Search Algorithms and Ap- plications (InTech Publishing, 2011). PDF; order the book

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NEWS & CONTACT

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Address

广东省深圳市南山区学苑大道1088号,南方科技大学,创园10栋103室

Room 103, Innovation Park, 1088 Xueyuan Blvd, Shenzhen, Guangdong 518055, China 

Phone

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