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Jin-Peng Liu
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2020 – today
- 2024
- [j6]Jin-Peng Liu, Lin Lin:
Dense outputs from quantum simulations. J. Comput. Phys. 514: 113213 (2024) - 2023
- [i13]Dong An, Jin-Peng Liu, Lin Lin:
Linear combination of Hamiltonian simulation for non-unitary dynamics with optimal state preparation cost. CoRR abs/2303.01029 (2023) - [i12]Junyu Liu, Minzhao Liu, Jin-Peng Liu, Ziyu Ye, Yuri Alexeev, Jens Eisert, Liang Jiang:
Towards provably efficient quantum algorithms for large-scale machine-learning models. CoRR abs/2303.03428 (2023) - [i11]Jin-Peng Liu, Lin Lin:
Dense outputs from quantum simulations. CoRR abs/2307.14441 (2023) - 2022
- [j5]Andrew M. Childs, Jiaqi Leng, Tongyang Li, Jin-Peng Liu, Chenyi Zhang:
Quantum simulation of real-space dynamics. Quantum 6: 860 (2022) - [c1]Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang:
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants. NeurIPS 2022 - [i10]Andrew M. Childs, Jiaqi Leng, Tongyang Li, Jin-Peng Liu, Chenyi Zhang:
Quantum simulation of real-space dynamics. CoRR abs/2203.17006 (2022) - [i9]Dong An, Di Fang, Stephen Jordan, Jin-Peng Liu, Guang Hao Low, Jiasu Wang:
Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation. CoRR abs/2205.01141 (2022) - [i8]Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang:
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants. CoRR abs/2210.06539 (2022) - [i7]Dong An, Jin-Peng Liu, Daochen Wang, Qi Zhao:
A theory of quantum differential equation solvers: limitations and fast-forwarding. CoRR abs/2211.05246 (2022) - [i6]Marco Bornstein, Jin-Peng Liu, Jingling Li, Furong Huang:
Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent. CoRR abs/2211.09908 (2022) - 2021
- [j4]Jin-Peng Liu, Herman Øie Kolden, Hari K. Krovi, Nuno F. Loureiro, Konstantina Trivisa, Andrew M. Childs:
Efficient quantum algorithm for dissipative nonlinear differential equations. Proc. Natl. Acad. Sci. USA 118(35): e2026805118 (2021) - [j3]Dong An, Noah Linden, Jin-Peng Liu, Ashley Montanaro, Changpeng Shao, Jiasu Wang:
Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance. Quantum 5: 481 (2021) - [j2]Andrew M. Childs, Jin-Peng Liu, Aaron Ostrander:
High-precision quantum algorithms for partial differential equations. Quantum 5: 574 (2021) - 2020
- [j1]Cong Sun, Jin-Peng Liu:
New stepsizes for the gradient method. Optim. Lett. 14(7): 1943-1955 (2020) - [i5]Andrew M. Childs, Jin-Peng Liu, Aaron Ostrander:
High-precision quantum algorithms for partial differential equations. CoRR abs/2002.07868 (2020) - [i4]Changpeng Shao, Jin-Peng Liu:
Quantum algorithms for the polynomial eigenvalue problems. CoRR abs/2010.15027 (2020) - [i3]Jin-Peng Liu, Herman Øie Kolden, Hari K. Krovi, Nuno F. Loureiro, Konstantina Trivisa, Andrew M. Childs:
Efficient quantum algorithm for dissipative nonlinear differential equations. CoRR abs/2011.03185 (2020) - [i2]Dong An, Noah Linden, Jin-Peng Liu, Ashley Montanaro, Changpeng Shao, Jiasu Wang:
Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance. CoRR abs/2012.06283 (2020)
2010 – 2019
- 2019
- [i1]Andrew M. Childs, Jin-Peng Liu:
Quantum spectral methods for differential equations. CoRR abs/1901.00961 (2019)
Coauthor Index
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