Skip to main content
Log in

Stochastic partial differential equations with gradient driven by space-time fractional noises

  • Research Article
  • Published:
Frontiers of Mathematics in China Aims and scope Submit manuscript

Abstract

We establish a class of stochastic partial differential equations (SPDEs) driven by space-time fractional noises, where we suppose that the drift term contains a gradient and satisfies certain non-Lipschitz condition. We prove the strong existence and uniqueness and joint Hölder continuity of the solution to the SPDEs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Bo L, Jiang Y, Wang Y. Stochastic Cahn-Hilliard equation with fractional noise. Stoch Dyn, 2008, 8(4): 643–665

    Article  MathSciNet  Google Scholar 

  2. Dong Z, Wang F, Xu L. Irreducibility and asymptotics of stochastic burgers equation driven by α-stable processes. Potential Anal, 2020, 52(3): 371–392

    Article  MathSciNet  Google Scholar 

  3. Guasoni P. No arbitrage under transaction costs, with fractional Brownian motion and beyond. Math Finance, 2006, 16(3): 569–582

    Article  MathSciNet  Google Scholar 

  4. Gyöngy I. Existence and uniqueness results for semilinear stochastic partial differential equations. Stochastic Process Appl, 1998, 73(4): 271–299

    Article  MathSciNet  Google Scholar 

  5. Hairer M, Voss J. Approximations to the stochastic Burgers equation. J Nonlinear Sci, 2011, 12(6): 897–920

    Article  MathSciNet  Google Scholar 

  6. Hu Y. Heat equations with fractional white noise potentials. Appl Math Optim, 2001, 43: 221–243

    Article  MathSciNet  Google Scholar 

  7. Hu Y, Jiang Y, Qian Z. Stochastic partial differential equations driven by space-time fractional noises. Stoch Dyn, 2019, 18(6): 1950012 (34 pp)

    Article  MathSciNet  Google Scholar 

  8. Hu Y, Nualart D, Xu F. Central limit theorem for an additive functional of the fractional Brownian motion. Ann Probab, 2014, 42(1): 168–203

    Article  MathSciNet  Google Scholar 

  9. Jiang Y, Wei T, Zhou X. Stochastic generalized Burgers equations driven by fractional noise. J Differential Equations, 2012, 252(2): 1934–1961

    Article  MathSciNet  Google Scholar 

  10. Kou S C. Stochastic modeling in nanoscale biophysics: subdiffusion within proteins. Ann Appl Stat, 2008, 2(2): 501–535

    Article  MathSciNet  Google Scholar 

  11. Kunita H. Stochastic Flows and Stochastic Differential Equations. Cambridge: Cambridge Univ Press, 1990

    MATH  Google Scholar 

  12. Mandelbrot B, Van Ness J. Fractional Brownian motions, fractional noises and applications. SIAM Rev, 1968, 10(4): 422–437

    Article  MathSciNet  Google Scholar 

  13. Mémin J, Mishura Y, Valkeila E. Inequalities for moments of Wiener integrals with respect to a fractional Brownian motion. Statist Probab Lett, 2001, 51(2): 197–206

    Article  MathSciNet  Google Scholar 

  14. Mitoma I. An ∞-dimensional inhomogeneous Langevin equation. J Funct Anal, 1985, 61: 342–359

    Article  MathSciNet  Google Scholar 

  15. Mohammed S, Zhang T. Stochastic Burgers equation with random initial velocities: a Malliavin calculus approach. SIAM J Math Anal, 2013, 45(4): 2396–2420

    Article  MathSciNet  Google Scholar 

  16. Mytnik L, Wachtel V. Multifractal analysis of superprocesses with stable branching in dimension one. Ann Probab, 2015, 43: 2763–2809

    Article  MathSciNet  Google Scholar 

  17. Nualart D, Ouknine Y. Regularization of quasilinear heat equations by a fractional noise. Stoch Dyn, 2004, 4(2): 201–221

    Article  MathSciNet  Google Scholar 

  18. Odde D J, Tanaka E M, Hawkins S S, Buettner H M. Stochastic dynamics of the nerve growth cone and its microtubules during neurite outgrowth. Biotechnol Bioeng, 1996, 50(4): 452–461

    Article  Google Scholar 

  19. Rosen J. Joint continuity of the intersection local times of Markov processes. Ann Probab, 1987, 15: 659–675

    Article  MathSciNet  Google Scholar 

  20. Shiga T. Two contrasting properties of solutions for one-dimensional stochastic partial differential equation. Canad J Math, 1994, 46(2): 415–437

    Article  MathSciNet  Google Scholar 

  21. Wang F, Wu J, Xu L. Log-Harnack inequality for stochastic Burgers equations and applications. J Math Anal Appl, 2011, 384(1): 151–159

    Article  MathSciNet  Google Scholar 

  22. Xiong J. Super-Brownian motion as the unique strong solution to an SPDE. Ann Probab, 2013, 41: 1030–1054

    Article  MathSciNet  Google Scholar 

  23. Xiong J, Yang X. Strong existence and uniqueness to a class of nonlinear SPDEs driven by Gaussian colored noises. Statist Probab Lett, 2017, 129: 113–129

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 11571190, 11771218, 11771018, 12061004), the Natural Science Foundation of Ningxia (No. 2020AAC03230), and the Major Research Project for North Minzu University (No. ZDZX201902).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xu Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, Y., Yang, X. Stochastic partial differential equations with gradient driven by space-time fractional noises. Front. Math. China 16, 479–497 (2021). https://doi.org/10.1007/s11464-021-0875-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11464-021-0875-z

Keywords

MSC2020

Navigation