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arXiv 2507.17469math.PR
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非线性粗糙 Fokker–Planck 方程

Nonlinear rough Fokker-Planck equations

Technische Universität Berlin(柏林工业大学);Weierstraß-Institut(魏尔斯特拉斯研究所)

Fabio Bugini, Peter K. Friz, Wilhelm Stannat

AI总结:

针对含共同噪声的非线性随机 Fokker–Planck 方程适定性难题,本文利用粗糙路径技术消除 Coghi–Gess 结果中依赖维数的正则性假设。

摘要:

McKean–Vlasov SDE 描述其动态依赖于过程规律的系统。相应的 Fokker–Planck 方程是关于相应测度流的非线性、非局部 PDE。在存在共同噪声和条件规律依赖时,演化变为随机,并由随机 Fokker–Planck 方程支配;即测度空间中的非线性、非局部 SPDE。(此类方程构成含共同噪声的平均场博弈理论的重要组成部分。)这类 SPDE 的适定性是一个难题,迄今最佳结果归功于 Coghi–Gess(2019),但该结果带有依赖于维数的正则性假设。在本工作中,我们展示粗糙路径技术如何能够完全规避这些假设。因此,与通常看法有些相反的是,相比源于经典随机分析的方法,使用粗糙路径对系数的正则性要求显著更低。

英文摘要:

McKean-Vlasov SDEs describe systems where the dynamics depend on the law of the process. The corresponding Fokker-Planck equation is a nonlinear, nonlocal PDE for the corresponding measure flow. In the presence of common noise and conditional law dependence, the evolution becomes random and is governed by a stochastic Fokker-Planck equation; that is, a nonlinear, nonlocal SPDE in the space of measures. (Such equations constitute an important ingredient in the theory of mean-field games with common noise.) Well-posedness of such SPDEs is a difficult problem, the best result to date due to Coghi-Gess (2019), which however comes with dimension-dependent regularity assumptions. In the present work, we show how rough path techniques can circumvent these entirely. Hence, and somewhat contrarily to common belief, the use of rough paths leads to substantially less regularity demands on the coefficients than methods rooted in classical stochastic analysis methods.

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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