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arXiv 1303.5329math-phmath.MPmath.PR
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全空间纳维-斯托克斯方程的正倒向随机微分系统

Forward-Backward Stochastic Differential Systems Associated to Navier-Stokes Equations in the Whole Space

Freddy Delbaen, Jinniao Qiu, Shanjian Tang

摘要:

在场空间中建立了全空间不可压纳维-斯托克斯方程的正倒向耦合随机微分系统。它被证明有一个唯一的局部解,并进一步如果雷诺数是小的或前向随机微分方程的维数等于2,它可以被证明有一个唯一的整体解决方案。这些结果与概率参数暗示已知的存在性和唯一性结果的纳维-斯托克斯方程,从而提供概率公式,后者。本文还讨论了Burgers型偏微分方程的相关结果和极大值原理。此外,通过截断上述FBSDS的时间间隔,由一类新的FBSDS及其相关的偏微分方程导出了纳维-斯托克斯方程的近似解;我们的概率公式也被桥接到Constantin和Iyer(Commun. 61:330- 345,2008)和Zhang(Probab.理论关系第148章:一个人305- 332,2010);最后,证明了纳维-斯托克斯方程的解是受控正倒向随机微分方程的临界点.

英文摘要:

A coupled forward-backward stochastic differential system (FBSDS) is formulated in spaces of fields for the incompressible Navier-Stokes equation in the whole space. It is shown to have a unique local solution, and further if either the Reynolds number is small or the dimension of the forward stochastic differential equation is equal to two, it can be shown to have a unique global solution. These results are shown with probabilistic arguments to imply the known existence and uniqueness results for the Navier-Stokes equation, and thus provide probabilistic formulas to the latter. Related results and the maximum principle are also addressed for partial differential equations (PDEs) of Burgers' type. Moreover, from truncating the time interval of the above FBSDS, approximate solution is derived for the Navier-Stokes equation by a new class of FBSDSs and their associated PDEs; our probabilistic formula is also bridged to the probabilistic Lagrangian representations for the velocity field, given by Constantin and Iyer (Commun. Pure Appl. Math. 61: 330--345, 2008) and Zhang (Probab. Theory Relat. Fields 148: 305--332, 2010) ; finally, the solution of the Navier-Stokes equation is shown to be a critical point of controlled forward-backward stochastic differential equations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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