Sampling conditioned hypoelliptic diffusions

作者: Martin Hairer , Andrew M. Stuart , Jochen Voss

DOI: 10.1214/10-AAP708

关键词: Physical modelStochastic partial differential equationInvariant (mathematics)Hypoelliptic operatorMathematicsMechanical systemMathematical analysis

摘要: A series of recent articles introduced a method to construct stochastic partial differential equations (SPDEs) which are invariant with respect the distribution given conditioned diffusion. These works restricted case elliptic diffusions where drift has gradient structure and resulting SPDE is second-order parabolic type. The present article extends this methodology allow construction SPDEs class hypoelliptic diffusion processes, subject bridge conditioning, leading fourth-order type. This allows treatment more realistic physical models, for example, one can use study transitions between meta-stable states in mechanical systems friction noise. In situation restriction being also be lifted.

参考文章(16)
J. Zabczyk, Symmetric solutions of semilinear stochastic equations Springer, Berlin, Heidelberg. pp. 237- 256 ,(1989) , 10.1007/BFB0083952
Hans Triebel, Theory of Function Spaces III ,(2008)
Giuseppe Da Prato, Jerzy Zabczyk, Stochastic Equations in Infinite Dimensions ,(1992)
Martin Hairer, Andrew Stuart, Jochen Voß, Sampling conditioned diffusions Cambridge University Press. ,(2009) , 10.1017/CBO9781139107020.009
Hans Triebel, Theory of function spaces ,(1983)
Martin Hairer, An Introduction to Stochastic PDEs arXiv: Probability. ,(2009)
M. Hairer, A. M. Stuart, J. Voss, P. Wiberg, Analysis of SPDEs arising in path sampling. Part I: The Gaussian case Communications in Mathematical Sciences. ,vol. 3, pp. 587- 603 ,(2005) , 10.4310/CMS.2005.V3.N4.A8
Andrew M. Stuart, Jochen Voss, Petter Wilberg, Conditional Path Sampling of SDEs and the Langevin MCMC Method Communications in Mathematical Sciences. ,vol. 2, pp. 685- 697 ,(2004) , 10.4310/CMS.2004.V2.N4.A7