First-order convergence of Milstein schemes for McKean–Vlasov equations and interacting particle systems

In this paper, we derive fully implementable first-order time-stepping schemes for McKean–Vlasov stochastic differential equations, allowing for a drift term with super-linear growth in the state component. We propose Milstein schemes for a time-discretized interacting particle system associated with the McKean–Vlasov equation and prove strong convergence of order 1 and moment stability, taming the drift if only a one-sided Lipschitz condition holds. To derive our main results on strong convergence rates, we make use of calculus on the space of probability measures with finite second-order moments. In addition, numerical examples are presented which support our theoretical findings.

[1]  F. Antonelli,et al.  Rate of convergence of a particle method to the solution of the Mc Kean-Vlasov's equation , 2002 .

[2]  Xuerong Mao,et al.  The truncated Euler-Maruyama method for stochastic differential equations , 2015, J. Comput. Appl. Math..

[3]  François Delarue,et al.  Probabilistic Theory of Mean Field Games with Applications I: Mean Field FBSDEs, Control, and Games , 2018 .

[4]  C. Patlak Random walk with persistence and external bias , 1953 .

[5]  G. dos Reis,et al.  Simulation of McKean–Vlasov SDEs with super-linear growth , 2018, IMA Journal of Numerical Analysis.

[6]  T. Faniran Numerical Solution of Stochastic Differential Equations , 2015 .

[7]  A. Veretennikov,et al.  Existence and uniqueness theorems for solutions of McKean–Vlasov stochastic equations , 2016 .

[8]  Michael B. Giles,et al.  Adaptive Euler–Maruyama method for SDEs with nonglobally Lipschitz drift , 2020 .

[9]  Andrew M. Stuart,et al.  Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations , 2002, SIAM J. Numer. Anal..

[10]  H. McKean,et al.  A CLASS OF MARKOV PROCESSES ASSOCIATED WITH NONLINEAR PARABOLIC EQUATIONS , 1966, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Martin Bauer,et al.  Strong Solutions of Mean-Field Stochastic Differential Equations with irregular drift , 2018, 1806.11451.

[12]  S. Sabanis A note on tamed Euler approximations , 2013, 1303.5504.

[13]  J. Touboul,et al.  Mean-field description and propagation of chaos in networks of Hodgkin-Huxley and FitzHugh-Nagumo neurons , 2012, The Journal of Mathematical Neuroscience.

[14]  William Salkeld,et al.  Freidlin–Wentzell LDP in path space for McKean–Vlasov equations and the functional iterated logarithm law , 2017, The Annals of Applied Probability.

[15]  L. Segel,et al.  Initiation of slime mold aggregation viewed as an instability. , 1970, Journal of theoretical biology.

[16]  Christoph Reisinger,et al.  Well-posedness and tamed schemes for McKean-Vlasov Equations with Common Noise , 2020, The Annals of Applied Probability.

[17]  Christoph Reisinger,et al.  An adaptive Euler-Maruyama scheme for McKean SDEs with super-linear growth and application to the mean-field FitzHugh-Nagumo model , 2020, J. Comput. Appl. Math..

[18]  Mireille Bossy,et al.  A stochastic particle method for the McKean-Vlasov and the Burgers equation , 1997, Math. Comput..

[19]  A. Sznitman Topics in propagation of chaos , 1991 .

[20]  P. Kloeden,et al.  Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients , 2010, 1010.3756.

[21]  D. Crisan,et al.  A Probabilistic Approach to Classical Solutions of the Master Equation for Large Population Equilibria , 2014, Memoirs of the American Mathematical Society.

[22]  Chaman Kumar,et al.  On Milstein approximations with varying coefficients: the case of super-linear diffusion coefficients , 2016, BIT Numerical Mathematics.

[23]  Xiaojie Wang,et al.  The tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients , 2011, 1102.0662.

[24]  Neelima,et al.  On Explicit Milstein-type Scheme for Mckean-Vlasov Stochastic Differential Equations with Super-linear Drift Coefficient , 2020, Electronic Journal of Probability.

[25]  École d'été de probabilités de Saint-Flour,et al.  Ecole d'été de probabilités de Saint-Flour XIX, 1989 , 1991 .

[26]  P. Kloeden,et al.  Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients , 2009, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[27]  James Foster,et al.  An Optimal Polynomial Approximation of Brownian Motion , 2019, SIAM J. Numer. Anal..

[28]  Terry Lyons,et al.  Pathwise approximation of SDEs by coupling piecewise abelian rough paths , 2015, 1505.01298.

[29]  Lukasz Szpruch,et al.  Antithetic multilevel particle system sampling method for McKean-Vlasov SDEs , 2019, 1903.07063.