G-Brownian Motion as Rough Paths and Differential Equations Driven by G-Brownian Motion

被引:2
|
作者
Geng, Xi [1 ,2 ]
Qian, Zhongmin [3 ]
Yang, Danyu [1 ,2 ]
机构
[1] Univ Oxford, Math Inst, Oxford OX2 6GG, England
[2] Univ Oxford, Oxford Man Inst, Oxford OX2 6ED, England
[3] Univ Oxford Exeter Coll, Oxford OX1 3DP, England
来源
关键词
Euler-Maruyama approximation; G-Brownian motion; G-expectation; Geometric rough paths; Nonlinear diffusion processes; Nonlinear heat flow; Rough differential equations; STOCHASTIC CALCULUS;
D O I
10.1007/978-3-319-11970-0_6
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The present article is devoted to the study of sample paths of G-Brownian motion and stochastic differential equations (SDEs) driven by G-Brownian motion from the viewpoint of rough path theory. As the starting point, by using techniques in rough path theory, we show that quasi-surely, sample paths of G-Brownian motion can be enhanced to the second level in a canonical way so that they become geometric rough paths of roughness 2 < p < 3. This result enables us to introduce the notion of rough differential equations (RDEs) driven by G-Brownian motion in the pathwise sense under the general framework of rough paths. Next we establish the fundamental relation between SDEs and RDEs driven by G-Brownian motion. As an application, we introduce the notion of SDEs on a differentiable manifold driven by G-Brownian motion and construct solutions from the RDE point of view by using pathwise localization technique. This is the starting point of developing G-Brownian motion on a Riemannian manifold, based on the idea of Eells-Elworthy-Malliavin. The last part of this article is devoted to such construction for a wide and interesting class of G-functions whose invariant group is the orthogonal group. In particular, we establish the generating nonlinear heat equation for such G-Brownian motion on a Riemannian manifold. We also develop the Euler-Maruyama approximation for SDEs driven by G-Brownian motion of independent interest.
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页码:125 / 193
页数:69
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