Jin-Peng Liu

According to our database, Jin-Peng Liu authored at least 19 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Infinite-dimensional Extension of the Linear Combination of Hamiltonian Simulation: Theorems and Applications.

Rundi Lu, Hao-En Li, Zhengwei Liu, Jin-Peng Liu

CoRR, February, 2025

Towards efficient quantum algorithms for diffusion probability models.

Yunfei Wang, Ruoxi Jiang, Yingda Fan, Xiaowei Jia, Jens Eisert, Junyu Liu, Jin-Peng Liu

CoRR, February, 2025

Explicit block encodings of boundary value problems for many-body elliptic operators.

Tyler Kharazi, Ahmad M. Alkadri, Jin-Peng Liu, Kranthi K. Mandadapu, K. Birgitta Whaley

Quantum, 2025

2024

Dense outputs from quantum simulations.

Jin-Peng Liu, Lin Lin

J. Comput. Phys., 2024

Toward end-to-end quantum simulation for protein dynamics.

Zhenning Liu, Xiantao Li, Chunhao Wang, Jin-Peng Liu

CoRR, 2024

2023

Dense outputs from quantum simulations.

Jin-Peng Liu, Lin Lin

CoRR, 2023

Towards provably efficient quantum algorithms for large-scale machine-learning models.

Junyu Liu, Minzhao Liu, Jin-Peng Liu, Ziyu Ye, Yuri Alexeev, Jens Eisert, Liang Jiang

CoRR, 2023

Linear combination of Hamiltonian simulation for non-unitary dynamics with optimal state preparation cost.

Dong An, Jin-Peng Liu, Lin Lin

CoRR, 2023

2022

Quantum simulation of real-space dynamics.

Andrew M. Childs, Jiaqi Leng, Tongyang Li, Jin-Peng Liu, Chenyi Zhang

Quantum, September, 2022

Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent.

Marco Bornstein, Jin-Peng Liu, Jingling Li, Furong Huang

CoRR, 2022

A theory of quantum differential equation solvers: limitations and fast-forwarding.

Dong An, Jin-Peng Liu, Daochen Wang, Qi Zhao

CoRR, 2022

Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation.

Dong An, Di Fang, Stephen Jordan, Jin-Peng Liu, Guang Hao Low, Jiasu Wang

CoRR, 2022

Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants.

Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

High-precision quantum algorithms for partial differential equations.

Andrew M. Childs, Jin-Peng Liu, Aaron Ostrander

Quantum, 2021

Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance.

Dong An, Noah Linden, Jin-Peng Liu, Ashley Montanaro, Changpeng Shao, Jiasu Wang

Quantum, 2021

Efficient quantum algorithm for dissipative nonlinear differential equations.

Jin-Peng Liu, Herman Øie Kolden, Hari K. Krovi, Nuno F. Loureiro, Konstantina Trivisa, Andrew M. Childs

Proc. Natl. Acad. Sci. USA, 2021

2020

New stepsizes for the gradient method.

Cong Sun, Jin-Peng Liu

Optim. Lett., 2020

Quantum algorithms for the polynomial eigenvalue problems.

Changpeng Shao, Jin-Peng Liu

CoRR, 2020

2019

Quantum spectral methods for differential equations.

Andrew M. Childs, Jin-Peng Liu

CoRR, 2019