Dong An

dong-an's picture
Hartree Postdoctoral Fellow (2021-2024)
dongan@umd.edu
3355 Atlantic Building

Dong An was a QuICS Hartree Postdoctoral Fellow in quantum information science from 2021 to 2024. His research interests include quantum algorithms, computational quantum mechanics, and an interdisciplinary study on quantum computing and applied mathematics, with focuses on adiabatic quantum computing, quantum simulation, and quantum algorithms for linear systems and differential equations. He received his doctorate in applied mathematics from University of California, Berkeley in 2021. After QuICS he continued on as a tenure-track Assistant Professor at Peking University.

Publications

2024

J. Aftab, An, D., and Trivisa, K., “Multi-product Hamiltonian simulation with explicit commutator scaling”, 2024.

2023

D. An, Liu, J. - P., Wang, D., and Zhao, Q., “A theory of quantum differential equation solvers: limitations and fast-forwarding”, 2023.
D. An, Childs, A. M., and Lin, L., “Quantum algorithm for linear non-unitary dynamics with near-optimal dependence on all parameters”, 2023.
P. C. S. Costa, An, D., Babbush, R., and Berry, D., “The discrete adiabatic quantum linear system solver has lower constant factors than the randomized adiabatic solver”, 2023.
D. An, Liu, J. - P., and Lin, L., “Linear combination of Hamiltonian simulation for non-unitary dynamics with optimal state preparation cost”, Phys. Rev. Lett., vol. 131, no. 150603, 2023.

2022

D. An, Fang, D., and Lin, L., “Time-dependent Hamiltonian Simulation of Highly Oscillatory Dynamics and Superconvergence for Schrödinger Equation”, Quantum, vol. 6, p. 690, 2022.
D. An, Fang, D., Jordan, S., Liu, J. - P., Low, G. Hao, and Wang, J., “Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation”, 2022.
D. An, Liu, J. - P., Wang, D., and Zhao, Q., “A theory of quantum differential equation solvers: limitations and fast-forwarding”, 2022.
P. C. S. Costa, An, D., Sanders, Y. R., Su, Y., Babbush, R., and Berry, D. W., “Optimal scaling quantum linear systems solver via discrete adiabatic theorem”, PRX Quantum, vol. 3, no. 4, p. 040303, 2022.

2021

D. An, Linden, N., Liu, J. - P., Montanaro, A., Shao, C., and Wang, J., “Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance”, Quantum 5, 481 (2021), vol. 5, p. 481, 2021.
P. C. S. Costa, An, D., Sanders, Y. R., Su, Y., Babbush, R., and Berry, D. W., “Optimal scaling quantum linear systems solver via discrete adiabatic theorem”, 2021.