清华大学交叉信息研究院

邓东灵

副教授

Email:
办公地址: MMW-S311
研究方向: 量子人工智能,量子信息与计算,拓扑相物质,量子非平衡态系统



 

Education

2010-2015,   Ph.D. in Physics, University of Michigan

2007-2010,   M. Sc. in Theoretical Physics, Chern Institute of Mathematics, Nankai University

2003-2007,   B. S. in Physics and Mathematics, Nankai University

 

Employment

2024-               Tenured Associate Professor, IIIS, Tsinghua University

2018-2024       Assistant Professor, IIIS, Tsinghua University

2015-2018       Joint Quantum Institute Postdoctoral Fellow, University of Maryland

 

Research Interests

  •      >   Quantum Machine Learning & Artificial Intelligence
  •      >   Quantum Information, Computation, and Simulation
  •      >   Topological Phases of Matter, AMO Physics
  •      >   Quantum Nonequilibrium Systems, Many-body Localization

 

Selected Publications (Google scholar profile)

  • [34] S. Xu et al., Non-Abelian braiding of Fibonacci anyons with a superconducting processor, Nature Physics, 20, 1469 (2024).[Cover of the issue]
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  • [33] H. R. Wang et al., Embedding quantum many-body scars into decoherence-free subspaces, Phys. Rev. Lett. 132, 150401 (2024)
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  • [31] S.-Y. Zhang, D. Yuan, T. Iadecola*, S. Xu*, and D.-L. Deng*, Extracting quantum many-body scarred eigenstates with matrix product states, Phys. Rev. Lett. 131, 020402 (2023).
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  • [30] X. X. Pan et al., Deep quantum neural networks on a superconducting processor, Nature Communications, 14, 4006 (2023).
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  • [29] W. Ren et al., Experimental quantum adversarial learning with programmable superconducting qubits, Nature Computational Science, 2, 711 (2022). [Cover of the issue]
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  • [28] Z.D. Liu, L. W. Yu, L.-M. Duan* and D.-L. Deng*, Presence and Absence of Barren Plateaus in Tensor-Network Based Machine Learning, Phys. Rev. Lett., 129, 270501 (2022).
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  • [27] X. Zhang et al., Digital quantum simulation of Floquet symmetry-protected topological phases, Nature, 607, 468 (2022).
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  • [26] H. Zhang et al., Experimental demonstration of adversarial examples in learning topological phases, Nature Communications, 13, 4993 (2022).
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  • [25] W. Y. Gong, and D.-L. Deng*, Universal Adversarial Examples and Perturbations for Quantum Classifiers, National Science Review, 9, nwab130 (2021).
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  • [24]   W.-G. Zhang, X.-L. Ouyang, X.-Z. Huang, X. Wang, H. L. Zhang, Y. F. Yu, X.-Y. Chang, Y. Q. Liu, D.-L. Deng*, and L.-M. Duan*, Observation of non-Hermitian topology with non-unitary dynamics of solid-state spins, Phys. Rev. Lett., 127, 090501 (2021).
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  • [23]   L. Yu and D.-L. Deng*, Unsupervised Learning of Non-Hermitian Topological Phases, Phys.  Rev. Lett. 126, 240402 (2021).
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  • [22]   D. Yuan, H.-R. Wang, Z. Wang*, and D.-L. Deng*, Solving the Liouvillian Gap with Artificial Neural Networks, Phys.  Rev. Lett., 126, 160401 (2021). 
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  • [21]   Y.-H. Zhang, P.-L. Zheng, Y. Zhang*, and D.-L. Deng*, Topological Quantum Compiling with Reinforcement Learning, Phys. Rev. Lett., 125, 170501 (2020). 
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  • [20]   S.-R. Lu, L.-M. Duan*, and D.-L. Deng*, Quantum adversarial machine learning, Phys. Rev. Research, 2, 033212 (2020).
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  • [19]   Y.-B. Yang, T. Qin, D.-L. Deng, L.-M. Duan, and Y. Xu*, Topological Amorphous Metals, Phys. Rev. Lett., 123, 076401 (2019). [Highlighted as Editor's Suggestion].
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  • [18]   W.-Q. Lian, S.-T. Wang, S.-R. Lu, Y.-Y. Huang, F. Wang, X.-X. Yuan, W.-G. Zhang, X.-L. Ouyang, X. Wang, X.-Z. Huang, L. He, X.-Y. Chang, D.-L. Deng*, and L.-M. Duan*, Machine Learning Topological Phases with a Solid-state Quantum Simulator, Phys. Rev. Lett., 122, 210503 (2019).
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  • [17]   S. Das Sarma, D.-L. Deng, and L. -M. Duan, Machine learning meets quantum physics, Physics Today 72, 48 (2019).
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  • [16]   L. Hu, S.-H. Wu, W. Z. Cai, Y. W. Ma, X. H. Mu, Y. Xu, H. Y. Wang, Y. P. Song, D.-L. Deng*, C. L. Zou*, and L. Y. Sun*, Quantum generative adversarial learning in a superconducting quantum circuit, Sci. Adv., 5, eaav2761 (2019). [Media coverage: New Scientist]
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  • [15]   F.-L. Liu, J. R. Garrison, D.-L. Deng, Z.-X. Gong, and A. V. Gorshkov, Asymmetric Particle Transport and Light-Cone Dynamics Induced by Anyonic Statistics, Phys. Rev. Lett., 121, 250404 (2018). [Highlighted as Editor's Suggestion].
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  • [14]   Y.-T. Hsu, X. Li, D.-L. Deng, and S. Das Sarma, Machine Learning Many-body Localization: Search for the Elusive Nonergodic Metal, Phys. Rev. Lett., 121, 245701 (2018).
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  • [13]   D.-L. Deng, Machine Learning Detection of Bell Nonlocality in Quantum Many-Body Systems, Phys. Rev. Lett., 120, 240402 (2018).
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  • [12]   D.-L. Deng, X. P. Li,  and S. Das Sarma, Quantum Entanglement in Neural Network States, Phys. Rev. X, 7, 021021 (2017). [Media coverage: JQI news, Deep Tech, Futurism, etc.]
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  • [11]   D.-L. Deng, X. P. Li,  and S. Das Sarma, Exact Machine Learning Topological States, Phys. Rev. B (Rapid Communications), 96, 195145 (2017).
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  • [10]   D.-L. Deng, S. Ganeshan, X.-P. Li, R. Modak, S. Mukerjee, and J. H. Pixley, Many-body localization in incommensurate models with a mobility edge, Annalen der Physik, 1600399 (2017). [invited topical review article for Annalen der Physik (Annals of Physics, Berlin)]
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  • [9]     D.-L. Deng, J. H. Pixley, X.-P. Li, and Sankar Das Sarma, Exponential Orthogonality Catastrophe in Single-particle and Many-body Localized Systems, Phys. Rev. B (Rapid Comm.), 92, 220201 (2015).
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  • [8]     D.-L. Deng, S.-T. Wang, L.-M. Duan, Direct Probe of Topological Order for Cold Atoms, Phys. Rev. A (Rapid Communications), 90, 041601 (2014).
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  • [7]     S.-T. Wang, D.-L. Deng, and L.-M. Duan, Probe of Three-Dimensional Chiral Topological Insulators in an Optical Lattice, Phys. Rev. Lett., 113, 033002 (2014).  [Highlighted as Editor's Suggestion].
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  • [6]     D.-L. Deng, S.-T. Wang, C. Shen, and L.-M. Duan, Hopf insulators and their topologically protected surface states, Phys. Rev. B (Rapid Communications), 88, 201105(R) (2013).
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  • [5]     C. Zu, D.-L. Deng, P.-Y. Hou, X.-Y. Chang, F. Wang, and L.-M. Duan, Experimental Distillation of Quantum Nonlocality, Phys. Rev. Lett., 111, 050405 (2013).
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  • [4]     D.-L. Deng, and L.-M. Duan, Fault-tolerant quantum random-number generator certified by Majorana fermions, Phys. Rev. A, 88, 012323 (2013).
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  • [3]     X. Zhang, M. Um, J.-H. Zhang, S.-M An, Y. Wang, D.-L. Deng, C. Shen, L.-M. Duan, and Kihwan Kim, State-Independent Experimental Test of Quantum Contextuality with a Single Trapped Ion, Phys. Rev. Lett., 110, 070401 (2013).
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  • [2]     C. Zu, Y.-X. Wang, D.-L. Deng, X.-Y. Chang, K. Liu, P.-Y. Hou, H.-X. Yang,and L.-M. Duan, State-Independent Experimental Test of Quantum Contextuality in an Indivisible System, Phys. Rev. Lett., 109,150401 (2012). Highlighted by the Physics Viewpoint article: "Mind the (Quantum) Context" by M.Paris and M. Paternostro, Physics 5, 113 (2012); Highlighted as Editor's Suggestion.
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  • [1]     D.-L. Deng, C.-F. Wu, J.-L. Chen, and C. H. Oh, Fault-Tolerant Greenberger-Horne-Zeilinger Paradox Based on Non-Abelian Anyons, Phys. Rev. Lett., 105, 060402 (2010).

 

Open positions:

Students: Highly motivated and gifted students interested in quantum machine learning/artificial intelligence are welcome to join us (one Ph.D. student, and one or two undergraduates per year).

Postdocs: One or two postdoc positions are available.  The successful applicants will be expected to perform theoretical studies in one of the following directions: 1) quantum machine learning/artificial intelligence; 2) quantum information, computation, and simulation; 3) topological phases of matter; 4) Non-equilibrium quantum systems, many-body localization. The application package should include a Curriculum Vita with a publication list, a research statement, and three recommendation letters. The position is available immediately and the search is open until the position is filled.

For more information about the positions, please contact dldeng@tsinghua.edu.cn.