Abstract
In this paper we review some recent results on stochastic analytical and numerical approaches to parabolic and elliptic partial differential equations involving a divergence form operator with a discontinuous coefficient and a compatibility transmission condition.
In the one-dimensional case existence and uniqueness results for such PDEs can be obtained by stochastic methods. The probabilistic interpretation of the solutions allows one to develop and analyze a low complexity Monte Carlo numerical resolution method. In addition, it allows to get accurate pointwise estimates for the derivatives of the solutions from which sharp convergence rate estimates are deduced for the stochastic numerical method.
A stochastic approach is also developed for the linearized Poisson–Boltzmann equation in Molecular Dynamics. As in the one-dimensional case, the probabilistic interpretation of the solution involves the solution of a SDE including a non standard local time term related to the discontinuity interface. We present an extended Feynman–Kac formula for the Poisson–Boltzmann equation. This formula justifies various probabilistic numerical methods to approximate the free energy of a molecule and bases error analyzes.
We finally present probabilistic interpretations of the non-linearized Poisson–Boltzmann equation in terms of backward stochastic differential equations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bass, R.F.: Diffusions and Elliptic Operators. Springer, New York (1998)
Bass, R.F., Chen, Z.Q.: Stochastic differential equations for Dirichlet processes. Probab. Theory Relat. Fields 121(3), 422–446 (2001)
Bernardin, F., Bossy, M., Martinez, M., Talay, D.: On mean discounted numbers of passage times in small balls of Itô processes observed at discrete times. Electron. Commun. Probab. 14, 302–316 (2009)
Bossy, M., Champagnat, N., Maire, S., Talay, D.: Probabilistic interpretation and random walk on spheres algorithms for the Poisson-Boltzmann equation in molecular dynamics. ESAIM:M2AN Math. Model. Numer. Anal. 44(5), 997–1048 (2010)
Champagnat, N., Perrin, N., Talay, D.: (in preparation)
Chen, L., Holst, M.J., Xu, J.: The finite element approximation of the nonlinear Poisson-Boltzmann equation. SIAM J. Numer. Anal. 45(6), 2298–2320 (2007)
Étoré, P.: On random walk simulation of one-dimensional diffusion processes with discontinuous coefficients. Electron. J. Probab. 11(9), 249–275 (2006)
Étoré, P., Lejay, A.: A Donsker theorem to simulate one-dimensional processes with measurable coefficients. ESAIM Probab. Stat. 11(9), 301–326 (2007)
Friedman, A.: Stochastic Differential Equations and Applications. Dover, Mineola (2006)
Fukushima, M., Oshima, Y., Takeda, M.: Dirichlet forms and symmetric Markov processes. In: de Gruyter Studies in Mathematics, vol. 19. (Walter) de Gruyter, Berlin (2011)
Graham, C., Talay, D.: Stochastic simulation and Monte Carlo methods, mathematical foundations of stochastic simulation. In: Stochastic Modelling and Applied Probability, vol. 68. Springer, Heildeberg (2013)
Ladyzenskaya, O.A., Solonnikov, V.A., Uralćeva, N.N.: Linear and quasi-linear equations of parabolic type. In: Translations of Mathematical Monographs, vol. 23. American Mathematical Society, Providence (1967)
Le Gall, J.-F.: One-dimensional stochastic differential equations involving the local times of the unknown process. In: Proceedings stochastic analysis and applications (Swansea, 1983). Lecture Notes in Mathematics, vol. 1095, pp. 51–82. Springer, Berlin (1984)
Lejay, A., Martinez, M.: A scheme for simulating one-dimensional diffusions with discontinuous coefficients. Ann. Appl. Probab. 16(1), 107–139 (2006)
Martinez, M., Talay, D.: One-dimensional parabolic diffraction equations: pointwise estimates and discretization of related stochastic differential equations with weighted local times. Electron. J. Probab. 17(27), 1–30 (2012)
Mascagni, M., Simonov, N.A.: Monte Carlo method for calculating the electrostatic energy of a molecule. In: Computational science—ICCS 2003, Part I. Lecture Notes in Computur Science, vol. 2657, pp. 63–72. Springer, Berlin (2003)
Niklitschek-Soto, S., Talay, D.: (in preparation)
Pardoux, É.: Backward stochastic differential equations and viscosity solutions of systems of semilinear parabolic and elliptic PDEs of second order. In: Decreusefond, L., Gjerde, J., Øksendal, B., Üstünel, A.S. (eds.) Stochastic Analysis and Related Topics: The Geilo Workshop, (1996). Birkhäuser, Boston (1998)
Pauwels, E.J.: Smooth first-passage densities for one-dimensional diffusions. J. Appl. Probab. 24(2), 370–377 (1987)
Peskir, G.: A change-of-variable formula with local time on curves. J. Theoret. Probab. 18(3), 499–535 (2005)
Revuz, D., Yor, M.: Continuous Martingales and Brownian Motion. Springer, Berlin (1999)
Rozkosz, A.: Weak convergence of diffusions corresponding to divergence form operators. Stoch. Stoch. Rep. 57(1–2), 129–157 (1996)
Stroock, D.W.: Diffusion semi-groups corresponding to uniformly elliptic divergence form operators (I): Aronson’s estimate for elliptic operators in divergence form. In: Séminaire de probabilités XXII. Lecture Notes in Mathematics, vol. 1321, pp. 316–347. Springer, Berlin (1988)
Talay, D.: Probabilistic numerical methods for partial differential equations: elements of analysis. In: Talay, D., Tubaro, L. (eds.) Probabilistic Models for Nonlinear Partial Differential Equations and Numerical Applications. Lecture Notes in Mathematics, vol. 1627, pp. 148–196. Springer, Berlin (1996)
Yan, L.: The Euler scheme with irregular coefficients. Ann. Probab. 30(3), 1172–1194 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Talay, D. (2014). On Probabilistic Analytical and Numerical Approaches for Divergence Form Operators with Discontinuous Coefficients. In: Parés, C., Vázquez, C., Coquel, F. (eds) Advances in Numerical Simulation in Physics and Engineering. SEMA SIMAI Springer Series, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-319-02839-2_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-02839-2_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02838-5
Online ISBN: 978-3-319-02839-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)