Jianbo Cui

News

12.18/2024, new preprint: Improving Numerical Error Bounds Near Sharp Interface Limit for Stochastic Reaction-Diffusion Equations

04.16/2024, new preprint: Asymptotic-preserving approximations for stochastic incompressible viscous fluids and SPDEs on graph

03.16/2024, our work on quantifying the effect of random dispersion for logarithmic Schrodinger equation has been accepted by SIAM/ASA Journal on Uncertainty Quantification.

01.31/2024, new preprint: A supervised learning scheme for computing Hamilton-Jacobi equation via density coupling

03.28/2023, the work on Stochastic Wasserstein Hamiltonian Flows has been accepted for publication in the Journal of Dynamics and Differential Equations.

03.10/2023, new preprint: Energy regularized models for logarithmic SPDEs and their numerical approximations

02.21/2023, the work on Optimal control for stochastic nonlinear Schrodinger equation on graph has been accepted for publication in the SIAM Journal on Control and Optimization.

01.19/2023, the work on Stochastic logarithmic Schrodinger equations: energy regularized approach has been accepted for publication in the SIAM Journal on Mathematical Analysis.

12.02/2022, the work on Wasserstein Hamiltonian flow with common noise on graph has been accepted by SIAM Journal on Applied Mathematics.

09.13/2022,new preprint: Optimal control for stochastic nonlinear Schrodinger equation on graph

08.30/2022,new preprint: Semi-implicit energy-preserving numerical schemes for stochastic wave equation via SAV approach

08.25/2022, the work on Wellposedness and regularity estimate for stochastic Cahn--Hilliard equation with unbounded noise diffusion has been accepted by SPDEs: Analysis and Computations.

07.09/2022, new preprint: Weak error estimates of fully-discrete schemes for the stochastic Cahn-Hilliard equation

04.19/2022, the work on the continuation multiple shooting method for Wasserstein geodesic equation has been accepted by SIAM J. Sci. Comput.

04.05/2022, new preprint: Wasserstein Hamiltonian flow with common noise on graph

04/2022, the work on the density function of numerical approximation of Langevin equation has been accepted by Math. Comp.

03/2022, one paper has been accepted by IMA J. Numer. Anal.

01/2022, one paper has been accepted by Math. Comp.

05/2021, I accepted the invitation to serve as a topic editor of Fractal and Fractional.

10/2020, I accepted the invitation to serve as a commentator of Mathematical Reviews (No. 152664).

Recent Talks

12/2024, Stochastic analysis, inverse problems and related issues, Tianyuan Mathematics Research Center, Yunnan

11/2024, Seminar talk at Tianyuan Mathematical Center in Central China, Wuhan University, Wuhan

11/2024, Seminars on Numerical Algorithms, Analyses, and Application, Xiamen University, Xiamen

11/2024, 13th National Conference on Probability and Statistics, Xiamen

10/2024, Computational Mathematics Series, Southeast University, Nanjing

10/2024, CSIAM 2024 Organizing Committee, EASIAM minisymposium "Advances in data-driven modeling & scientific computation", Nanjing

10/2024, Workshop Advances in Numerics for S(P)DEs, Chalmers University of Technology & University of Gothenburg, Sweden

08/2024, First Conference on Analysis and Simulation of Uncertain Systems, Harbin Institute of Technology, Harbin

07/2024, Youth Workshop on Numerical Methods for Stochastic Differential Equations, National Tianyuan Mathematics Northeast Center, Jilin University, Jilin

07/2024, Workshop on Structure-preserving numerical methods and their applications, 20-24 July 2024, Hong Kong

07/2024, "MS:Recent Advances in Scientific Computing and Learning" in the International Conference on Scientific Computation and Differential Equations 2024, Singapore

06/2024, Seminar talk at the Hong Kong University of Science and Technology, Hong Kong

06/2024, Seminar talk at Center for Applied Mathematics, Tianjing University, Tianjing

04/2024, Modern Methods for Differential Equations of Quantum Mechanics, the Banff International Research Station for Mathematical Innovation and Discovery (BIRS), Canada

12/2023, Workshop on Graph Theory, Optimization and Scientific Computing, The Hong Kong Polytechnic University

12/2023, The One World Stochastic Numerics and Inverse Problems seminar (online)

12/2023, Ninth Youth Symposium on Scientific and Engineering Computing, Chinese Academy of Sciences, Beijing, China

11/2023, 2023 Workshop on stochastic computations, Southern University of Science and Technology, Shenzhen, China

11/2023, Workshop on Stochastic Dynamical Systems and Machine Learning, Xiamen University and Tianyuan Mathematical Center in Southeast China, Xiamen, China

10/2023, 2023 Workshop on Theory, Algorithms and Related Issues in Dynamical Systems, Nanjing University, Nanjing, China

08/2023, The First Workshop on Analysis and Computing at MSU-BIT University, Shenzhen MSU-BIT University, Shenzhen, China

06/2023, 2023 Youth Workshop on Theory and Algorithms of Stochastic Dynamical Systems, National University of Defense Technology, Changsha, China

04/2023, 2023 Frontiers Symposium on Numerical Computation of Stochastic Differential Equations, Tiangong University, Tianjing, China

03/2023, Seminar on computation mathematics, Southeast University, Jiangsu, China (online)

09/2022, 2022 Frontier Seminar on Numerical Methods, Sichuan University, Sichuan, China (online)

08/2022, Lecture on "optimal transport on graph and its application", Chinese Academy of Sciences, Beijing, China (online)

04/2021, Seminar on Stochastic Partial Differential Equations Perserving Structure Algorithms for Youth Scholars, Chinese Academy of Sciences, Beijing, China (online)

02/2021, 2021 Georgia Scientific Computing Symposium (GSCS), University of Georgia, Atlanta, USA (online)

12/2020, Central South University, School of Mathematics and Statistics, Changsha, China (online)

02/2020, 2020 Georgia Scientific Computing Symposium (GSCS), Emory University, Atlanta, USA

02/2020, Applied and Computational Mathematics Seminar, Georgia Institute of Technology, Atlanta, USA

11/2018, Forum on Numerical Analysis for SDEs and SPDEs, Chinese Academy of Sciences, Beijing, China

10/2018, International Conference on Stochastic Partial Differential Equations, University of Alberta, Edmonton, Canada

09/2018, The 1st Peking University Top Doctoral Seminar on Computing and Applied Mathematics and the 4th Beijing Computational Mathematics Graduate Forum, Peking University, Beijing, China

09/2018, Numerical Analysis of Stochastic Partial Differential Equations, University of Gothenburg, Gothenburg, Sweden

06/2018, Seminar on Hot Topics in Stochastic Computing, Tianyuan Mathematical Center in Northeast China, Changchun, China

06/2018, The 40th Stochastic Processes and Their Applications Conference, Gothenburg, Sweden

11/2017, Forum on Numerical Analysis for SDEs and SPDEs, AMSS, CAS, Beijing, China

10/2017, Efficient Numerical Methods for Stochastic Hamiltonian Partial Differential Equations, Central South University, Changsha, China

09/2017, SciCADE 2017, International Conference on Scientific Computation and Differential Equations, University of Bath, Bath

05/2017, Workshop on Dynamical System and Its Applications, Dalian University of Technology, Dalian, China

01/2017, 10th International Conference on Computational Physics, University of Macau, Macau, China

11/2016, 20th IMACS World Congress, Xiamen University, Xiamen, China

Research

My current research interests include numerical analysis, stochastic ODEs and PDEs, optimal transport, optimal control, structure-preserving algorithms, Hamiltonian systems, dynamical systems, ergodic theory, etc.

Publications

1. Cui, J. Explicit Approximation for Stochastic Nonlinear Schrodinger Equation J. Differential Equations 419 (2025), 1-39.

2. Cui, J.; Sun, L. Quantifying the effect of random dispersion for logarithmic Schrodinger equation SIAM/ASA J. Uncertain. Quantif. 12 (2024), no. 2, 579-613.

3. Cui, J.; Hong, J.; Ji, L.; Sun, L. Strong convergence rate of an exponentially integrable scheme for stochastic nonlinear wave equation Communications on Analysis and Computation, 2 (2024), no. 3, 215-245.

4. Cui, J.; Sun, L. Stochastic logarithmic Schrodinger equations: energy regularized approach SIAM J. Math. Anal. 55 (2023), no. 4, 3044-3080.

5. Cui, J.; Liu, S.; Zhou, H. Optimal control for stochastic nonlinear Schrodinger equation on graph SIAM J. Control Optim. 61 (2023), no. 4, 2021-2042.

6. Cui, J.; Liu, S.; Zhou, H. Stochastic Wasserstein Hamiltonian Flows J. Dyn. Diff. Equat. (2023), https://doi.org/10.1007/s10884-023-10264-4

7. Cui, J.; Hong, J. Wellposedness and regularity estimate for stochastic Cahn--Hilliard equation with unbounded noise diffusion Stoch. Partial Differ. Equ. Anal. Comput. 11 (2023), no. 4, 1635-1671

8. Cui, J.; Liu, S.; Zhou, H. Wasserstein Hamiltonian flow with common noise on graph SIAM J. Appl. Math. 83 (2023), no. 2, 484-509

9. Chen, C. ; Cui, J.; Hong, J.; Sheng, D. Accelerated Exponential Euler Scheme for Stochastic Heat Equation: Convergence rate of Densities. IMA J. Numer. Anal. 43 (2023), no. 2, 1181-1220.

10. Cui, J.; Dieci, L.; Zhou, H. A continuation multiple shooting method for Wasserstein geodesic equation SIAM J. Sci. Comput. 44 (2022), no. 5, A2918-A2943. GitHub

11. Cui, J.; Hong, J.; Sheng, D. Density function of numerical solution of splitting AVF scheme for stochastic Langevin equation. . Math. Comp. 91 (2022), no. 337, 2283-2333.

12. Cui, J.; Dieci, L.; Zhou, H. Time Discretizations of Wasserstein-Hamiltonian Flows. Math. Comp. 91 (2022), no. 335, 1019-1075.

13. Cui, J.; Hong, J.; Sun, L. Strong convergence of full discretization for stochastic Cahn-Hilliard equation driven by additive noise. SIAM J. Numer. Anal. 59 (2021), no. 6, 2866-2899.

14. Cui, J.; Liu S.; Zhou, H. What is a stochastic Hamiltonian process on finite graph? An optimal transport answer. J. Differential Equations 305 (2021), 428-457.

15. Cui, J.; Hong, J.; Sun, L. Weak convergence and invariant measure of a full discretization for parabolic SPDEs with non-globally Lipschitz coefficients. Stochastic Process. Appl. 134 (2021), 55-93.

16. Cui, J.; Hong, J. Absolute continuity and numerical approximation of stochastic Cahn-Hilliard equation with unbounded noise diffusion. J. Differential Equations 269 (2020), no. 11, 10143-0180.

17. Cohen, D.; Cui, J.; Hong, J.; Sun, L. Exponential integrators for stochastic Maxwell's equations driven by Ito noise. J. Comput. Phys. 410 (2020), 109382, 21 pp.

18. Cui, J.; Hong, J.; Sun, L. On global existence and blow-up for damped stochastic nonlinear Schrodinger equation. Discrete Contin. Dyn. Syst. Ser. B 24 (2019), no. 12, 6837-6854.

19. Brehier, C. E.; Cui, J.; Hong, J. Strong convergence rates of semidiscrete splitting approximations for the stochastic Allen-Cahn equation. IMA J. Numer. Anal. 39 (2019), no. 4, 2096-2134.

20. Cui, J.; Hong, J. Strong and weak convergence rates of a spatial approximation for stochastic partial differential equation with one-sided Lipschitz coefficient. SIAM J. Numer. Anal. 57 (2019), no. 4, 1815-1841.

21. Cui, J.; Hong, J.; Liu, Z.; Zhou, W. Strong convergence rate of splitting schemes for stochastic nonlinear Schrodinger equations. J. Differential Equations 266 (2019), no. 9, 5625-5663.

22. Cui, J.; Hong, J. Analysis of a splitting scheme for damped stochastic nonlinear Schrodinger equation with multiplicative noise. SIAM J. Numer. Anal. 56 (2018), no. 4, 2045-2069.

23. Niu, X.; Cui, J.; Hong, J.; Liu, Z. Explicit pseudo-symplectic methods for stochastic Hamiltonian systems. BIT 58 (2018), no. 1, 163-178.

24. Cui, J.; Hong, J.; Liu, Z. Strong convergence rate of finite difference approximations for stochastic cubic Schrodinger equations. J. Differential Equations 263 (2017), no. 7, 3687-3713.

25. Cui, J.; Hong, J.; Liu, Z.; Zhou, W. Stochastic symplectic and multi-symplectic methods for nonlinear Schrodinger equation with white noise dispersion. J. Comput. Phys. 342 (2017), 267-285.

26. Cui, J.; Liu, Z.; Miao, L.; Wang, X. Holder continuity for parabolic Anderson equation with non-Gaussian noise. J. Math. Anal. Appl. 441 (2016), no. 2, 684-691.

Preprints:

1. Cui, J.; Wang, F.-Y. Improving Numerical Error Bounds Near Sharp Interface Limit for Stochastic Reaction-Diffusion Equations arXiv:2412.12604

2. Cui, J.; Sheng, D. Asymptotic-preserving approximations for stochastic incompressible viscous fluids and SPDEs on graph arXiv:2404.09168

3. Cui, J.; Liu, S.; Zhou, H. A supervised learning scheme for computing Hamilton-Jacobi equation via density coupling arXiv:2401.1595

4. Cui, J.; Sun, L. Weak approximation for stochastic reaction-diffusion equation near sharp interface limit arXiv:2307.08241

5. Cui, J. Regularization effect of noise on fully discrete approximation for stochastic reaction-diffusion equation near sharp interface limit arXiv:2307.08246

6. Cui, J.; Hou, D.; Qiao, Z. Energy regularized models for logarithmic SPDEs and their numerical approximations arXiv:2303.05003

7. Cui, J.; Hong, J.; Sun, L. Semi-implicit energy-preserving numerical schemes for stochastic wave equation via SAV approach arXiv2208.13394

8. Brehier, C. E.; Cui, J.; Wang, X. Weak error estimates of fully-discrete schemes for the stochastic Cahn-Hilliard equation arXiv:2207.09266

9. Cui, J.; Hong, J.; Sun, L. Structure-preserving splitting methods for stochastic logarithmic Schrodinger equation via regularized energy approximation arXiv:2111.04402