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 冉仕举         副研究员

	所属学科	理论物理、量子计算、人工智能
	研究方向	张量网络理论与算法、强关联数值计算、量子多体模拟、机器学习解决量子物理问题、基于机器学习的量子编程、量子机器学习、多线性代数
	招生方向	理论物理、量子机器学习
	联系方式	sjran@cnu.edu.cn

 

 

　　主要研究量子多体物理、张量网络理论与方法、量子信息与量子计算、经典及量子机器学习等方向；发表学术论文30余篇，在Springer的 “Lecture Notes in Physics” 系列出版专著《Tensor Network Contractions》；多次在国际学术会议作邀请报告，担任Frontiers in Physics客座编辑，组织张量网络相关专刊；组织全国性量子机器学习会议；担任机器学习国际会议委员会成员；曾获西班牙博士后项目Fellowship of Fundacio Catalunya - La Pedrera · Ignacio Cirac Program Chair；曾任欧盟学术委员会项目评审；曾于慕尼黑大学、美因茨大学、马普量子光学所等进行学术访问。

 

 

　　2006年-2010年，北京师范大学物理学系，本科；

　　2010年-2015年，中国科学院大学物理科学学院，硕博；

　　2014年7月，德国慕尼黑大学，访问博士生；

　　2015年-2018年，西班牙光子必赢626net入口所（ICFO），博士后研究员；

　　2016年，获Fundacio-Catalunya独立博士后研究员fellowship；

　　2017年9月，德国马克思-普朗克研究所，访问学者；

　　2018年6月，德国美因茨大学，访问学者；

　　2018年7月-11月，中国科学院大学，访问学者；

　　2018年-今，bwin必赢国际-首页，副研究员

　　 

　　 

　　学术专著：

　　[1] Shi-Ju Ran*, Emanuele Tirrito, Cheng Peng, Xi Chen, Gang Su, and Maciej Lewenstein.  Tensor Network Contractions.  Lecture Notes in Physics, Springer, Cham (2020). ISSN: 0075-8450. DOI: http://doi.org/10.1007/978-3-030-34489-4

　　[2] 冉仕举，《张量网络基础教程》，首都师范大学出版社（即将出版）

　　 

　　已发表论文：

[1]  Ying Lu, Yue-Min Li, Peng-Fei Zhou, and Shi-Ju Ran*, Preparation of Many-body Ground States by Time Evolution with Variational Microscopic Magnetic Fields and Incomplete Interactions, Phys. Rev. A 104, 052413 (2021).

[2]  Kunkun Wang, Lei Xiao, Wei Yi*, Shi-Ju Ran*, and Peng Xue*, Experimental realization of a quantum image classifier via tensor-network-based machine learning, Photon. Res. 9, 2332-2340 (2021).

[3]  Peng-Fei Zhou, Rui Hong, and Shi-Ju Ran*, Automatically differentiable quantum circuit for many-qubit state preparation, Phys. Rev. A 101, 032310 (1 October 2021).

[4]  Xinran Ma, Z. C. Tu, and Shi-Ju Ran*, Deep Learning Quantum States for Hamiltonian Estimation, Chin. Phys. Lett. (Express Letter), 38 (11), 110301 (11 October 2021).

[5]  Rui Hong, Peng-Fei Zhou, Bin Xi, Jie Hu, An-Chun Ji, and Shi-Ju Ran*, Predicting quantum potentials by deep neural network and metropolis sampling, SciPost Phys. Core 4, 022 (13 September 2021).

[6]  Yuhan Liu, Wen-Jun Li, Xiao Zhang, Maciej Lewenstein, Gang Su*, and Shi-Ju Ran*, Entanglement-Based Feature Extraction by Tensor Network Machine Learning, Front. Appl. Math. Stat. 7, 716044 (06 August 2021).

[7]  Yuan Yang, Zheng-Zhi Sun, Shi-Ju Ran*, and Gang Su*, Visualizing quantum phases and identifying quantum phase transitions by nonlinear dimensional reduction, Phys. Rev. B 103, 075106 (2 February 2021).

[8]  Yuan Yang, Zhengchuan Wang*, Shi-Ju Ran*, and Gang Su*, Phase identification in many-body systems by virtual configuration binarization, Phys. Rev. E 103, 013313 (22 January 2021).

[9]  Shi-Ju Ran*, Zheng-Zhi Sun, Shao-Ming Fei, Gang Su, Maciej Lewenstein. Quantum Compressed Sensing with Unsupervised Tensor Network Machine Learning. Phys. Rev. Research 2, 033293 (24 August 2020).

[10] Zheng-Zhi Sun, Shi-Ju Ran*, and Gang Su*, Tangent-Space Gradient Optimization of Tensor Network for Machine Learning. Phys. Rev. E 102, 012152 (30 July 2020).

[11] Shi-Ju Ran, Efficient Encoding of Matrix Product States into Quantum Circuits of One- and Two-Qubit Gates. Phys. Rev. A 101, 032310 (9 March, 2020).

[12] Zheng-Zhi Sun, Cheng Peng, Ding Liu, Shi-Ju Ran*, and Gang Su*. Generative Tensor Network Classification Model for Supervised Machine Learning. Phys. Rev. B 101, 075135 (25 February 2020).

[13] Yuan Yang, Shi-Ju Ran*, Xi Chen, Zhengzhi Sun, Shou-Shu Gong, Zhengchuan Wang*, Gang Su*. Reentrance of Topological Phase in Spin-1 Frustrated Heisenberg Chain. Phys. Rev. B 101, 045133, (29 January 2020).

[14] Shi-Ju Ran*, Bin Xi, Cheng Peng, Gang Su, and Maciej Lewenstein. Efficient quantum simulation for thermodynamics of infinite-size many-body systems in arbitrary dimensions. Physical Review B 99:205132, May 2019.

[15] Ding Liu, Shi-Ju Ran*, Peter Wittek*, Cheng Peng, Rual Blázquez Garca, Gang Su, and Maciej Lewenstein. Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure. New Journal of Physics, 21:073059, (30 July 2019).

[16] Xi Chen, Shi-Ju Ran*, Shuo Yang, Maciej Lewenstein, Gang Su*. Noise-tolerant Signature of Z_N Topological Orders in Quantum Many-body States. Physical Review B 99:195101, (1 May 2019).

[17] Shi-Ju Ran*, Cheng Peng, Gang Su, and Maciej Lewenstein. Controlling phase diagram of finite spin-1/2 chains by tuning boundary interactions. Physical Review B 98:085111, Aug. 2018.

[18] Shi-Ju Ran, Wei Li, Shou-Shu Gong, Andreas Weichselbaum, Jan von Delft, and Gang Su*. Emergent spin-1 trimerized valence bond crystal in the spin-1/2 Heisenberg model on the star lattice. Physical Review B, 97:075146, Feb. 2018.

[19] Cheng Peng, Shi-Ju Ran*, Maciej Lewenstein, and Gang Su*. Identifying Criticality in Higher Dimensions by Time Matrix Product State, The European Physical Journal B, 91:258, Oct. 2018.

[20] Xi Chen, Shi-Ju Ran, Tao Liu, Cheng Peng, Yi-Zhen Huang, and Gang Su. Finite-temperature phase diagram and algebraic paramagnetic liquid in the spin-1/2 kagomé Heisenberg antiferromagnet. Science Bulletin, 63:1545–1550, Dec. 2018.

[21] Shi-Ju Ran*, Angelo Piga, Cheng Peng, Gang Su, and Maciej Lewenstein. Few-body systems capture many-body physics: Tensor network approach. Physical Review B, 96:155120, Oct. 2017.

[22] Shi-Ju Ran, Cheng Peng, Wei Li, Maciej Lewenstein, and Gang Su*. Criticality in two-dimensional quantum systems: Tensor network approach. Physical Review B, 95:155114, Apr. 2017.

[23] J. Jünemann, A. Piga, Shi-Ju Ran, M. Lewenstein, M. Rizzi, and A. Bermudez*. Exploring Interacting Topological Insulators with Ultracold Atoms: the Synthetic Creutz-Hubbard Model. Physical Review X, 7:031057, Sep. 2017.

[24] Cheng Peng, Shi-Ju Ran, Tao Liu, Xi Chen, and Gang Su*. Fermionic algebraic quantum spin liquid in an octa-kagome frustrated antiferromagnet. Physical Review B, 95:075140, Feb. 2017.

[25] Emanuele Tirrito, Shi-Ju Ran, Andrew J Ferris, Ian P McCulloch, and Maciej Lewenstein*. Efficient perturbation theory to improve the density matrix renormalization group. Physical Review B, 95:064110, Feb. 2017.

[26] Shi-Ju Ran. Ab-initio optimization principle for the ground states of translationally invariant strongly correlated quantum lattice models. Physical Review E, 93:053310, May. 2016.

[27] Meng Wang, Shi-Ju Ran, Tao Liu, Yang Zhao, Qing-Rong Zheng, and Gang Su*. Phase diagram and exotic spin-spin correlations of anisotropic Ising model on the Sierpiński gasket. The European Physical Journal B, 89:1-10, Feb. 2016.

[28] Tao Liu, Shi-Ju Ran, Wei Li, Xin Yan, Yang Zhao, and Gang Su*. Featureless quantum spin liquid, 1/3-magnetization plateau state, and exotic thermodynamic properties of the spin-1/2 frustrated Heisenberg antiferromagnet on an infinite Husimi lattice. Physical Review B, 89:054426, Feb. 2014.

[29] Shi-Ju Ran, Bin Xi, Tao Liu, and Gang Su*. Theory of network contractor dynamics for exploring thermodynamic properties of two-dimensional quantum lattice models. Physical Review B, 88:064407, Aug. 2013.

[30] Yang Zhao, Wei Li, Bin Xi, Zhe Zhang, Xin Yan, Shi-Ju Ran, Tao Liu, and Gang Su*. Kosterlitz-Thouless phase transition and re-entrance in an anisotropic three-state Potts model on the generalized kagome lattice. Physical Review E, 87:032151, Mar. 2013.

[31] Yang Zhao, Wei Li, Bin Xi, Shi-Ju Ran, Yuan-Yuan Zhu, Bing-Wu Wang, Song Gao, and Gang Su*. Honeycomb Heisenberg spin ladder: Unusual ground state and thermodynamic properties. Europhysics Letters, 104:57009, Dec. 2013.

[32] Shi-Ju Ran, Wei Li, Bin Xi, Zhe Zhang, and Gang Su*. Optimized decimation of tensor networks with super-orthogonalization for two-dimensional quantum lattice models. Physical Review B, 86:134429, Oct. 2012.

[33] Xin Yan, Wei Li, Yang Zhao, Shi-Ju Ran, and Gang Su*. Phase diagrams, distinct conformal anomalies, and thermodynamics of spin-1 bond-alternating Heisenberg antiferromagnetic chain in magnetic fields. Physical Review B, 85:134425, Apr. 2012.

[34] Wei Li, Shi-Ju Ran, Shou-Shu Gong, Yang Zhao, Bin Xi, Fei Ye, and Gang Su*. Linearized tensor renormalization group algorithm for the calculation of thermodynamic properties of quantum lattice models. Physical Review Letters, 106:127202, Mar. 2011.

[35] Wei Li, Shou-Shu Gong, Yang Zhao, Shi-Ju Ran, Song Gao, and Gang Su*. Phase transitions and thermodynamics of the two-dimensional Ising model on a distorted kagome lattice. Physical Review B, 82:134434, Oct. 2010.

 

　　待发表论文（审稿中）：

[1]  Ye-Ming Meng, Jing Zhang, Peng Zhang, Chao Gao*, and Shi-Ju Ran*, Residual Matrix Product State for Machine Learning, arXiv:2012.11841.

[2]  Shi-Ju Ran, Bayesian Tensor Network with Polynomial Complexity for Probabilistic Machine Learning. arXiv:1912.12923.

 

　　学术会议（未完全统计）：

[1]  Wen-Jun Li, Zheng-Zhi Sun, Ya-Ru Wang, Shi-Ju Ran*, and Gang Su*, Matrix product state for quantum-inspired feature extraction and compressed sensing, Accepted by Second Workshop on Quantum Tensor Networks in Machine Learning, 35th Conference on Neural Information Processing Systems (NeurIPS 2021).

[2]  Zheng-Zhi Sun, Shi-Ju Ran*, and Gang Su*, Tangent-space gradient optimization: an efficient update scheme for tensor network machine learning and beyond, First Workshop on Quantum Tensor Networks in Machine Learning, 34th Conference on Neural Information Processing Systems (NeurIPS 2020).

[3]  Ding Liu , Zheng-Zhi Sun , Cheng Peng , Gang Su, and Shi-Ju Ran*, Generative Tensor Network Classification for Supervised Learning, International Workshop on Tensor Network Representations in Machine Learning, the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020).