BIMSA > Jinpeng Liu
Assistant Professor Jinpeng Liu

Affiliation: YMSC, BIMSA

Group: Quantum Symmetry

Office: A15-208

Email: liujinpeng@bimsa.cn

Research Field: Quantum Computation

Webpage: https://www.jin-peng-liu.me/

Biography

Jin-Peng Liu is an assistant professor at YMSC, Tsinghua University. He was a Simons quantum postdoctoral fellow at MIT and Berkeley from 2022 to 2024. He received his Ph.D. from the University of Maryland in 2022. His research focuses on Quantum for Science and AI+QS. He has published papers in PNAS, Nat. Commun., PRL, CMP, JCP, Quantum, and NeurIPS, QIP, TQC. His research has been reported by Quanta, SIAM News, and MATH+. He has won the ICCM Best Thesis Award (Gold Prize), NSF Robust Quantum Simulation Seed Grant (CO-PI), NSF QISE-NET Triplet Award, and James C. Alexander Prize. He is serving as an editor of Quantum (JCR Q1, IF 6.4).

Research Interest

  • Quantum Simulation Algorithms
  • Quantum Scientific Computation
  • Quantum Machine Learning

Education Experience

  • 2017 - 2022      University of Maryland, College Park      Applied Mathematics and Scientific Computation      Ph.D      (Supervisor: Andrew Childs)
  • 2013 - 2017      Beihang University- Chinese Academy of Sciences      Mathematics（Hua Loo Keng Class）      B.Sc.      (Supervisor: Ya-xiang Yuan)

Work Experience

  • 2024 -      Yau Mathematical Science Center, Tsinghua University      Assistant Professor
  • 2023 - 2024      Massachusetts Institute of Technology      Postdoctoral Associate
  • 2022 - 2023      University of California, Berkeley      Simons Quantum Postdoctoral Fellow

Honors and Awards

  • 2024      ICCM Best Thesis Award (Gold Prize)
  • 2023      NSF Robust Quantum Simulation Seed Grant（Co-PI）
  • 2023      James C. Alexander Prize
  • 2021      NSF QISE-NET Triplet Award

Publication

  • [1] Zhenning Liu, Xiantao Li, Chunhao Wang, Jin-Peng Liu, Toward end-to-end quantum simulation for protein dynamics, arXiv:2411.03972 (2024)
  • [2] P Schleich, T Kharazi, X Li, JP Liu, A Aspuru-Guzik, N Wiebe, Arbitrary Boundary Conditions and Constraints in Quantum Algorithms for Differential Equations via Penalty Projections, arXiv (2025)
  • [3] F Wei, R Lu, Y Shao, J Li, JP Liu, Z Liu, BELT: Block Encoding of Linear Transformation on Density Matrices, arXiv (2025)
  • [4] R Lu, HE Li, Z Liu, JP Liu, Infinite-dimensional Extension of the Linear Combination of Hamiltonian Simulation: Theorems and Applications, arXiv (2025)
  • [5] D An, JP Liu, D Wang, Q Zhao, Quantum Differential Equation Solvers: Limitations and Fast-Forwarding: D. An, J.-P. Liu, D. Wang, Q. Zhao, Communications in Mathematical Physics, 406(8), 189 (2025)
  • [6] Y Wang, R Jiang, Y Fan, X Jia, J Eisert, J Liu, JP Liu, Towards efficient quantum algorithms for diffusion probability models, arXiv (2025)
  • [7] T Kharazi, AM Alkadri, JP Liu, KK Mandadapu, KB Whaley, Explicit block encodings of boundary value problems for many-body elliptic operators, Quantum, 9, 1764 (2025)
  • [8] C Peng, JP Liu, GW Chern, D Luo, Provably efficient adiabatic learning for quantum-classical dynamics, arXiv (2024)
  • [9] J Liu, M Liu, JP Liu, Z Ye, Y Wang, Y Alexeev, J Eisert, L Jiang, Towards provably efficient quantum algorithms for large-scale machine-learning models, Nature Communications, 15(1), 434 (2024)
  • [10] JP Liu, L Lin, Dense outputs from quantum simulations, Journal of Computational Physics, 514, 113213 (2024)
  • [11] D An, JP Liu, L Lin, Linear combination of Hamiltonian simulation for nonunitary dynamics with optimal state preparation cost, Physical Review Letters, 131(15), 150603 (2023)
  • [12] D An, D Fang, S Jordan, JP Liu, GH Low, J Wang, Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation, Communications in Mathematical Physics, 404, 963-1020 (2023)
  • [13] AM Childs, T Li, JP Liu, C Wang, R Zhang, Quantum algorithms for sampling log-concave distributions and estimating normalizing constants, Advances in Neural Information Processing Systems, 35, 23205-23217 (2022)
  • [14] C Shao, JP Liu, Solving generalized eigenvalue problems by ordinary differential equations on a quantum computer, Proceedings of the Royal Society A, 478(2262), 20210797 (2022)
  • [15] AM Childs, J Leng, T Li, JP Liu, C Zhang, Quantum simulation of real-space dynamics, Quantum, 6, 860 (2022)
  • [16] D An, N Linden, JP Liu, A Montanaro, C Shao, J Wang, Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance, Quantum, 5 (2021)
  • [17] AM Childs, JP Liu, A Ostrander, High-precision quantum algorithms for partial differential equations, Quantum, 5, 574 (2021)
  • [18] JP Liu, HØ Kolden, HK Krovi, NF Loureiro, K Trivisa, AM Childs, Efficient quantum algorithm for dissipative nonlinear differential equations, Proceedings of the National Academy of Sciences, 118(35), e2026805118 (2021)
  • [19] C Sun, JP Liu, New stepsizes for the gradient method, Optimization Letters, 14(7), 1943-1955 (2020)
  • [20] AM Childs, JP Liu, Quantum spectral methods for differential equations, Communications in Mathematical Physics, 375, 1427-1457 (2020)

 

Update Time: 2025-10-13 17:00:05