IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v119y2009i10p3453-3470.html
   My bibliography  Save this article

White noise driven SPDEs with reflection: Existence, uniqueness and large deviation principles

Author

Listed:
  • Xu, Tiange
  • Zhang, Tusheng

Abstract

In the first part of this paper, we prove the uniqueness of the solutions of SPDEs with reflection, which was left open in the paper [C. Donati-Martin, E. Pardoux, White noise driven SPDEs with reflection, Probab. Theory Related Fields 95 (1993) 1-24]. We also obtain the existence of the solution for more general coefficients depending on the past with a much shorter proof. In the second part of the paper, we establish a large deviation principle for SPDEs with reflection. The weak convergence approach is proven to be very efficient on this occasion.

Suggested Citation

  • Xu, Tiange & Zhang, Tusheng, 2009. "White noise driven SPDEs with reflection: Existence, uniqueness and large deviation principles," Stochastic Processes and their Applications, Elsevier, vol. 119(10), pages 3453-3470, October.
    • Handle: RePEc:eee:spapps:v:119:y:2009:i:10:p:3453-3470
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4149(09)00110-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ben Hambly & Jasdeep Kalsi & James Newbury, 2018. "Limit order books, diffusion approximations and reflected SPDEs: from microscopic to macroscopic models," Papers 1808.07107, arXiv.org, revised Jun 2019.
    2. Salins, M., 2021. "Systems of small-noise stochastic reaction–diffusion equations satisfy a large deviations principle that is uniform over all initial data," Stochastic Processes and their Applications, Elsevier, vol. 142(C), pages 159-194.
    3. Matoussi, Anis & Sabbagh, Wissal & Zhang, Tusheng, 2017. "Backward doubly SDEs and semilinear stochastic PDEs in a convex domain," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2781-2815.
    4. Zhang, Tusheng, 2012. "Large deviations for invariant measures of SPDEs with two reflecting walls," Stochastic Processes and their Applications, Elsevier, vol. 122(10), pages 3425-3444.
    5. Zhang, Tusheng, 2011. "Systems of stochastic partial differential equations with reflection: Existence and uniqueness," Stochastic Processes and their Applications, Elsevier, vol. 121(6), pages 1356-1372, June.
    6. Li, Ruinan & Li, Yumeng, 2020. "Talagrand’s quadratic transportation cost inequalities for reflected SPDEs driven by space–time white noise," Statistics & Probability Letters, Elsevier, vol. 161(C).
    7. Juan Yang & Tusheng Zhang, 2014. "Existence and Uniqueness of Invariant Measures for SPDEs with Two Reflecting Walls," Journal of Theoretical Probability, Springer, vol. 27(3), pages 863-877, September.
    8. Yang, Xue & Zhang, Jing, 2019. "The obstacle problem for quasilinear stochastic PDEs with degenerate operator," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3055-3079.
    9. Yang, Xue & Zhang, Qi & Zhang, Tusheng, 2020. "Reflected backward stochastic partial differential equations in a convex domain," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 6038-6063.
    10. Yang, Xue, 2019. "Reflected backward stochastic partial differential equations with jumps in a convex domain," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 126-136.
    11. Jasdeep Kalsi, 2020. "Existence of Invariant Measures for Reflected Stochastic Partial Differential Equations," Journal of Theoretical Probability, Springer, vol. 33(3), pages 1755-1767, September.
    12. Hambly, Ben & Kalsi, Jasdeep, 2020. "Stefan problems for reflected SPDEs driven by space–time white noise," Stochastic Processes and their Applications, Elsevier, vol. 130(2), pages 924-961.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:spapps:v:119:y:2009:i:10:p:3453-3470. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.