Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Statistics
  • Help & Advice
University of Warwick

The Library

  • Login

Consistent families of Brownian motions and stochastic flows of kernels

Tools
- Tools
+ Tools

Howitt, Chris and Warren, Jon. (2009) Consistent families of Brownian motions and stochastic flows of kernels. The Annals of Probability, Vol.37 (No.4). pp. 1237-1272. ISSN 0091-1798

[img]
Preview
PDF
WRAP_warren_euclid.aop.1248182138.pdf - Published Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader

Download (342Kb)
Official URL: http://dx.doi.org/10.1214/08-AOP431

Abstract

Consider the following mechanism for the random evolution of a distribution of mass on the integer lattice Z. At unit rate, independently for each site, the mass at the site is split into two parts by choosing a random proportion distributed according to some specified probability measure on [0, 1] and dividing the mass in that proportion. One part then moves to each of the two adjacent sites. This paper considers a continuous analogue of this evolution, which may be described by means of a stochastic flow of kernels, the theory of which was developed by Le Jan and Raimond. One of their results is that such a flow is characterized by specifying its N point motions, which form a consistent family of Brownian motions. This means for each dimension N we have a diffusion in RN, whose N coordinates are all Brownian motions. Any M coordinates taken from the N-dimensional process are distributed as the M-dimensional process in the family. Moreover, in this setting, the only interactions between coordinates are local: when coordinates differ in value they evolve independently of each other. In this paper we explain how such multidimensional diffusions may be constructed and characterized via martingale problems.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Brownian motion processes, Kernel functions, Stochastic processes, Diffusion processes
Journal or Publication Title: The Annals of Probability
Publisher: Institute of Mathematical Statistics
ISSN: 0091-1798
Date: 2009
Volume: Vol.37
Number: No.4
Page Range: pp. 1237-1272
Identification Number: 10.1214/08-AOP431
Status: Peer Reviewed
Access rights to Published version: Restricted or Subscription Access
References: [1] AMIR, M. (1991). Sticky Brownian motion as the strong limit of a sequence of random walks. Stochastic Process. Appl. 39 221–237. MR1136247 [2] BORODIN, A. N. and SALMINEN, P. (2002). Handbook of Brownian Motion—Facts and Formulae, 2nd ed. Birkhäuser, Basel. MR1912205 [3] FALKOVICH, G., GAW¸EDZKI, K. and VERGASSOLA, M. (2001). Particles and fields in fluid turbulence. Rev. Modern Phys. 73 913–975. MR1878800 [4] GAW¸EDZKI, K. and HORVAI, P. (2004). Sticky behavior of fluid particles in the compressible Kraichnan model. J. Statist. Phys. 116 1247–1300. MR2096036 [5] HARRISON, J. M. and LEMOINE, A. J. (1981). Sticky Brownian motion as the limit of storage processes. J. Appl. Probab. 18 216–226. MR598937 [6] HOWITT, C. J. andWARREN, J. (2008). Dynamics for the Brownian web and the erosion flow. Stochastic Process. Appl. To appear. [7] IKEDA, N. andWATANABE, S. (1973). The local structure of a class of diffusions and related problems. In Proceedings of the Second Japan–USSR Symposium on Probability Theory (Kyoto, 1972). Lecture Notes in Math. 330 124–169. Springer, Berlin. MR0451425 [8] JACOD, J. and SHIRYAEV, A. N. (2003). Limit Theorems for Stochastic Processes, 2nd ed. Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences] 288. Springer, Berlin. MR1943877 [9] LE JAN, Y. and LEMAIRE, S. (2004). Products of Beta matrices and sticky flows. Probab. Theory Related Fields 130 109–134. MR2092875 [10] LE JAN, Y. and RAIMOND, O. (2004). Flows, coalescence and noise. Ann. Probab. 32 1247– 1315. MR2060298 [11] LE JAN, Y. and RAIMOND, O. (2004). Sticky flows on the circle and their noises. Probab. Theory Related Fields 129 63–82. MR2052863 [12] PROTTER, P. E. (2005). Stochastic Integration and Differential Equations. Stochastic Modelling and Applied Probability 21. Springer, Berlin. MR2273672 [13] REVUZ, D. and YOR, M. (1999). Continuous Martingales and Brownian Motion, 3rd ed. Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences] 293. Springer, Berlin. MR1725357 [14] STROOCK, D. W. and VARADHAN, S. R. S. (1979). Multidimensional Diffusion Processes. Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences] 233. Springer, Berlin. MR532498 [15] SUN, R. and SWART, J. M. (2008). The Brownian net. Ann. Probab. 36 1153–1208. [16] TSIRELSON, B. (2004). Nonclassical stochastic flows and continuous products. Probab. Surv. 1 173–298 (electronic). MR2068474 [17] WARREN, J. (1997). Branching processes, the Ray–Knight theorem, and sticky Brownian motion. In Séminaire de Probabilités, XXXI. Lecture Notes in Math. 1655 1–15. Springer, Berlin. MR1478711
URI: http://wrap.warwick.ac.uk/id/eprint/37376

Data sourced from Thomson Reuters' Web of Knowledge

Request changes to a record

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...
twitter

Email us: publications@warwick.ac.uk
Contact Details
About Us