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A Random Walk on Rectangles Algorithm

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Abstract

In this article, we introduce an algorithm that simulates efficiently the first exit time and position from a rectangle (or a parallelepiped) for a Brownian motion that starts at any point inside. This method provides an exact way to simulate the first exit time and position from any polygonal domain and then to solve some Dirichlet problems, whatever the dimension. This method can be used as a replacement or complement of the method of the random walk on spheres and can be easily adapted to deal with Neumann boundary conditions or Brownian motion with a constant drift.

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References

  • J. V. Beck, K. D. Cole, A. Haji-Sheikh, and B. Litkouhi, Heat conduction using Green's functions, Series in Computational and Physical Processes in Mechanics and Thermal Sciences, Hemisphere Publishing Corp.:London, 1992.

  • L. Breiman, Probability, Addison-Wesley, 1981.

  • F. Campillo and A. Lejay, “A Monte Carlo method without grid for a fractured porous domain model,” Monte Carlo Methods and Applications vol. 8(2) pp. 129–148, 2002.

    MathSciNet  MATH  Google Scholar 

  • J. M. DeLaurentis and L. A. Romero, “A Monte Carlo method for Poisson's equation,” Journal of Computational Physics vol. 90(1) pp. 123–140, 1990.

    Article  MathSciNet  MATH  Google Scholar 

  • L. Devroye, Non-Uniform Random Variate Generation, Springer-Verlag, 1986.

  • M. S. P. Eastham, Theory of ordinary differential equations, Van Nostrand Reinhold Company, 1970.

  • N. Golyanda, “Convergence rate for spherical processes with shifted centres,” Monte Carlo Methods and Applications vol. 10(3–4), pp. 287–296, 2004. Conference proceeding of IV IMACS Seminar on Monte Carlo Methods.

    MathSciNet  Google Scholar 

  • C.-O. Hwang, M. Mascagni, and J. A. Given, “A Feynman-Kac path-integral implementation for Poisson's equation using an \(h\)-conditioned Green's function,” Mathematics and Computers in Simulation vol. 62(3–6) pp. 347–355, 2003. 3rd IMACS Seminar on Monte Carlo Methods-MCM 2001 (Salzburg).

    Article  MathSciNet  MATH  Google Scholar 

  • V. Linetsky, “On the transition densities for reflected diffusions,” Advances in Applied Probability vol. 37(2) pp. 435–460, 2005.

    Article  MATH  MathSciNet  Google Scholar 

  • S. Maire, Réduction de variance pour l'intégration numérique et pour le calcul critique en transport neutronique, PhD thesis, Université de Toulon et de Var (France), 2001.

  • G. N. Mil'shtejn and N. F. Rybkina, “An algorithm for random walks over small ellipsoids for solving the general Dirichlet problem,” Computational Mathematics and Mathematical Physics vol. 33(5) pp. 631–647, 1993.

    MathSciNet  Google Scholar 

  • G. N. Milstein and M. V. Tretyakov, “Simulation of a space-time bounded diffusion,” Annals of Applied Probability vol. 9(3) pp. 732–779, 1999.

    Article  MathSciNet  MATH  Google Scholar 

  • M. E. Muller, “Some continuous Monte Carlo methods for the Dirichlet problem,” Annals of Mathematical Statistics vol. 27 pp. 569–589, 1956.

    MATH  MathSciNet  Google Scholar 

  • B. Nœtinger and T. Estébenet, “Up scaling of fractured media using continuous-time random walks methods,” Transport in Porous Media vol. 39(3) pp. 315–337, 2000.

    Article  Google Scholar 

  • W. H. Press, S. A Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C (2nd ed.), Cambridge University Press, 1992.

  • K. Sabelfeld, I. Shalimova, and A. I. Levykin, “Discrete random walk on large spherical grids generated by spherical means for PDEs,” Monte Carlo Methods and Applications vol. 10(3–4) pp. 559–574, 2004. Conference proceeding of IV IMACS Seminar on Monte Carlo Methods.

    MathSciNet  MATH  Google Scholar 

  • K. K. Sabelfeld and D. Talay, “Integral formulation of the boundary value problems and the method of random walk on spheres,” Monte Carlo Methods and Applications vol. 1(1) pp. 1–34, 1995.

    Article  MathSciNet  MATH  Google Scholar 

  • N. A. Simonov and M. Mascagni, “Random walk algorithm for estimating effective properties of digitized porous media,” Monte Carlo Methods and Applications vol. 10(3–4) pp. 599–608, 2004. Conference proceeding of IV IMACS Seminar on Monte Carlo Methods.

    Article  MathSciNet  MATH  Google Scholar 

  • S. Torquato and C. Kim, “Effective conductivity, dielectric constant, and diffusion coefficient of digitized composite media via first-passage-time equations,” Journal of Applied Physics vol. 85(3) pp. 1560–1571, 1999.

    Article  Google Scholar 

  • D. Veestraeten, “The conditional probability density function for a reflected Brownian motion,” Computational Economics vol. 24(2) pp. 185–207, 2005.

    Article  Google Scholar 

  • E. Zauderer, Partial differential equations of applied mathematics. Pure and Applied Mathematics, John Wiley & Sons Inc.: New York, 1983.

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Correspondence to Madalina Deaconu.

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60C05, 65N

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Deaconu, M., Lejay, A. A Random Walk on Rectangles Algorithm. Methodol Comput Appl Probab 8, 135–151 (2006). https://doi.org/10.1007/s11009-006-7292-3

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  • DOI: https://doi.org/10.1007/s11009-006-7292-3

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