研究领域

量子模拟算法，量子科学计算，量子机器学习

刘锦鹏的主要研究领域为量子模拟算法，量子科学计算，量子机器学习等。他开创性地发展了一系列量子算法用于求解微分方程、

采样与优化问题，并解决了量子计算领域15年的公开猜想：提出首个多项式时间求解非线性微分方程的量子算法。

他在PNAS、Nat. Commun.、PRL、CMP、JCP、Quantum 等期刊和 NeurIPS、QIP、TQC等会议发表论文多篇，并受到 Quanta、

SIAM News、MATH+ 等科技媒体报道。刘锦鹏现为量子信息领域顶刊Quantum的编委，是中国高校现有的3名编委之一。

教育背景

2013-2017 学士 北京航空航天大学-中科院华罗庚班

2017-2022 博士 马里兰大学

科研经历

2024 至今 助理教授，清华大学丘成桐数学科学中心

2023-2024 博士后研究员，麻省理工学院

2022-2023 西蒙斯量子博士后，加州大学伯克利分校

荣誉与奖励

2024年 世界华人数学家大会ICCM毕业论文奖（博士论文金奖）

2023-2024年 NSF Robust Quantum Simulation Seed Grant（Co-PI）

2023年 James C. Alexander Prize

2023年 MIT CTP Postdoctoral Scholarship

2022年 Simons Quantum Postdoctoral Fellowship

2022年 Stanford Q-FARM Bloch Fellowship

2021年 NSF QISE-NET Triplet Award

代表性论文

(Google Scholar https://scholar.google.com/citations?user=4dExDoAAAAAJ&hl=en)

[1] Provably Efficient Adiabatic Learning for Quantum-Classical Dynamics (with C.Peng, G-W.Chern, and D.Luo) arXiv:2408.00276

[2] Explicit block encodings of boundary value problems for many-body elliptic operators (with T.Kharazi, A.M.Alkadri, K.K.Mandadapu, and K.B.Whaley) arXiv:2407.18347

[3] Dense outputs from quantum simulations (with L.Lin) Journal of Computational Physics 113213 (2024)

[4] Towards provably efficient quantum algorithms for large-scale machine-learning

models (with J.Liu, M.Liu, Z.Ye, Y.Alexeev, J.Eisert, and L.Jiang) Nature Communications 15, 434 (2024).

[5] Linear combination of Hamiltonian simulation for non-unitary dynamics with optimal state preparation cost (with D.An and L.Lin) Physical Review Letters 131, 150603 (2023)

[6] A theory of quantum differential equation solvers: limitations and fast-forwarding (with D.An, D.Wang, and Q.Zhao) arXiv:2211.05246

[7] Quantum algorithms for sampling log-concave distributions and estimating normalizing constants (with A.M.Childs, T.Li, C.Wang, and R.Zhang) Advances in Neural Information Processing Systems 35, 23205–23217 (NeurIPS 2022)

[8] Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation (with D.An, D.Fang, S.Jordan, G.Low, and J.Wang) Communications in Mathematical Physics 404, 963-1020 (2023)

[9] Quantum simulation of real-space dynamics (A.M.Childs, J.Leng, T.Li,, C.Zhang) Quantum 6, 860 (2022)

[10] Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance (with D.An, N.Linden, A.Montanaro, C.Shao, and J.Wang) Quantum 5, 481 (2021)

[11] Efficient quantum algorithm for dissipative nonlinear differential equations (with H. Ø.Holden, H.K.Krovi, N.F.Loureiro, K.Trivisa, and A.M.Childs) Proceedings of the National Academy of Sciences 118, 35 (2021)

[12] Solving generalized eigenvalue problems by ordinary differential equations on a quantum computer (with C.Shao) Proceedings of the Royal Society A 478, 20210797 (2022)

[13] High-precision quantum algorithms for partial differential equations (with A.M.Childs and A.Ostrander) Quantum 5, 574 (2021)

[14] Quantum spectral methods for differential equations (with A.M.Childs) Communications in Mathematical Physics 375, 1427-1457 (2020)

[15] New stepsizes for the gradient method (with C.Sun) Optimization Letters 14, 1943-1955 (2020)