Nonlinear Fokker–Planck equations for probability measures on path space and path-distribution dependent SDEs

Xing Huang; Michael Röckner; Feng-Yu Wang

doi:10.3934/dcds.2019125

Article Contents

2019, Volume 39, Issue 6: 3017-3035. Doi: 10.3934/dcds.2019125

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Nonlinear Fokker–Planck equations for probability measures on path space and path-distribution dependent SDEs

1.
Center for Applied Mathematics, Tianjin University, Tianjin 300072, China
2.
Department of Mathematics, Bielefeld University, D-33501 Bielefeld, Germany
3.
Department of Mathematics, Swansea University, Singleton Park, SA2 8PP, United Kingdom

^* Corresponding author: Feng-Yu Wang
^* Corresponding author: Feng-Yu Wang

Received: January 2018

Revised: October 2018

Published: February 2019

Supported by NNSFC (11801406, 11771326, 11831014, 11431014, 11726627)

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Abstract

By investigating path-distribution dependent stochastic differential equations, the following type of nonlinear Fokker–Planck equations for probability measures $ (\mu_t)_{t \geq 0} $ on the path space $ {\scr {C}}: = C([-r_0, 0];\mathbb R^d), $ is analyzed:

$ \partial_t \mu(t) = L_{t, \mu_t}^*\mu_t, \ \ t\ge 0, $

where $ \mu(t) $ is the image of $ \mu_t $ under the projection $ {\scr {C}}\ni\xi\mapsto \xi(0)\in\mathbb R^d $, and

$ \begin{align*} L_{t, \mu}(\xi)&: = \frac 1 2\sum\limits_{i, j = 1}^d a_{ij}(t, \xi, \mu)\frac{\partial^2} {\partial_{\xi(0)_i} \partial_{\xi(0)_j }} \\\; &\quad +\sum\limits_{i = 1}^d b_i(t, \xi, \mu)\frac{\partial}{\partial_{\xi(0)_i}}, \ \ t\ge 0, \xi\in {\scr {C}}, \mu\in \scr P^{\scr {C}}. \end{align*} $

Under reasonable conditions on the coefficients $ a_{ij} $ and $ b_i $, the existence, uniqueness, Lipschitz continuity in Wasserstein distance, total variational norm and entropy, as well as derivative estimates are derived for the martingale solutions.

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Mathematics Subject Classification: Primary: 60J75, 47G20, 60G52.

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[1]	M. Arnaudon, A. Thalmaier and F.-Y. Wang, Harnack inequality and heat kernel estimate on manifolds with curvature unbounded below, Bull. Sci. Math., 130 (2006), 223-233. doi: 10.1016/j.bulsci.2005.10.001.
[2]	J. Bao, F.-Y. Wang and C. Yuan, Asymptotic Log-Harnack inequality and applications for stochastic systems of infinite memory, Stochastic Processes and their Applications, , 2018, arXiv: 1710.01042. doi: 10.1016/j.spa.2018.12.010.
[3]	J. Bao, F.-Y. Wang and C. Yuan, Ergodicity for Neutral Type SDEs with Infinite Length of Memory, preprint, arXiv: 1805.03431.
[4]	V. Bogachev, A. Krylov, M. Röckner and S. Shaposhnikov, Fokker-Planck-Kolmogorov Equations, Monograph, AMS, 2015. doi: 10.1090/surv/207.
[5]	O. A. Butkovsky, On ergodic properties of nonlinear Markov chains and stochastic McKean-Vlasov equations, Theo. Probab. Appl., 58 (2014), 661-674. doi: 10.1137/S0040585X97986825.
[6]	I. Csiszár and J. Körne, Information Theory: Coding Theorems for Discrete Memory-less Systems, Academic Press, New York, 1981.
[7]	K. Carrapatoso, Exponential convergence to equilibrium for the homogeneous Landau equation with hard potentials, Bull. Sci. Math., 139 (2015), 777-805. doi: 10.1016/j.bulsci.2014.12.002.
[8]	L. Desvillettes and C. Villani, On the spatially homogeneous Landau equation for hard potentials, Part Ⅰ: existence, uniqueness and smothness, Comm. Part. Diff. Equat., 25 (2000), 179-259. doi: 10.1080/03605300008821512.
[9]	L. Desvillettes and C. Villani, On the spatially homogeneous Landau equation for hard potentials, Part Ⅱ: H-Theorem and Applications, Comm. Part. Diff. Equat., 25 (2000), 261-298. doi: 10.1080/03605300008821513.
[10]	A. Eberle, A. Guillin and R. Zimmer, Quantitative Harris type theorems for diffusions and McKean-Vlasov processes, Trans. Amer. Math. Soc., 2018, arXiv: 1606.06012. doi: 10.1090/tran/7576.
[11]	N. Fournier and A. Guillin, From a Kac-like particle system to the Landau equation for hard potentials and Maxwell molecules, Ann. Sci. l'ENS, 50 (2017), 157-199. doi: 10.24033/asens.2318.
[12]	H. Guérin, Existence and regularity of a weak function-solution for some Landau equations with a stochastic approach, Stoch. Proc. Appl., 101 (2002), 303-325. doi: 10.1016/S0304-4149(02)00107-2.
[13]	M. Hairer, J. C. Mattingly and M. Scheutzow, Asymptotic coupling and a general form of Harris theorem with applications to stochastic delay equations, Probab. Theory Related Fields, 149 (2011), 223-259. doi: 10.1007/s00440-009-0250-6.
[14]	I. Ikeda and S. Watanabe, Stochastic Differential Equations and Diffusion Processes, North-Holland Publishing Co., Amsterdam, 1981.
[15]	A. N. Kolmogoroff, Über die analytischen Methoden in der Wahrscheinlichkeitsrechnung, Math. Ann., 104 (1931), 415-458. doi: 10.1007/BF01457949.
[16]	Yu. S. Mishura and A. Yu. Veretennikov, Existence and uniqueness theorems for solutions of McKean-Vlasov stochastic equations, preprint, arXiv: 1603.02212.
[17]	S.-E. A. Mohammed, Stochastic Functional Differential Equations, Pitman, Boston, 1984.
[18]	M. S. Pinsker, Information and Information Stability of Random Variables and Processes, Holden-Day, San Francisco, 1964.
[19]	M. Röckner and F.-Y. Wang, Log-harnack inequality for stochastic differential equations in Hilbert spaces and its consequences, Infin. Dim. Anal. Quat. Probab. Relat. Top., 13 (2010), 27-37. doi: 10.1142/S0219025710003936.
[20]	D. W. Stroock and S. R. S. Varadhan, Multidimensional Diffusion Processes, Springer, New York, 1979.
[21]	A.-S. Sznitman, Topics in propagation of chaos, Lecture Notes in Mathematics, 1464 (1991), 165-251. doi: 10.1007/BFb0085169.
[22]	C. Villani, Optimal Transport, Old and New, Springer-Verlg, Berlin, 2009. doi: 10.1007/978-3-540-71050-9.
[23]	C. Villani, On the spatially homogeneous Landau equation for Maxwellian mocecules, Math. Mod. Meth. Appl. Sci., 8 (1998), 957-983. doi: 10.1142/S0218202598000433.
[24]	F.-Y. Wang, Logarithmic Sobolev inequalities on noncompact Riemannian manifolds, Probab. Theory Related Fields, 109 (1997), 417-424. doi: 10.1007/s004400050137.
[25]	F.-Y. Wang, Harnack inequality and applications for stochastic generalized porous media equations, Ann. Probab., 35 (2007), 1333-1350. doi: 10.1214/009117906000001204.
[26]	F.-Y. Wang, Harnack Inequalities and Applications for Stochastic Partial Differential Equations, Springer, Berlin, 2013. doi: 10.1007/978-1-4614-7934-5.
[27]	F.-Y. Wang, Harnack inequalities on manifolds with boundary and applications, J. Math. Pures Appl., 94 (2010), 304-321. doi: 10.1016/j.matpur.2010.03.001.
[28]	F.-Y. Wang, Harnack inequality for SDE with multiplicative noise and extension to Neumann semigroup on nonconvex manifolds, Ann. Probab., 39 (2011), 1449-1467. doi: 10.1214/10-AOP600.
[29]	F.-Y. Wang, Integration by parts formula and shift Harnack inequality for stochastic equations, Ann. Probab., 42 (2014), 994-1019. doi: 10.1214/13-AOP875.
[30]	F.-Y. Wang and C. Yuan, Harnack inequalities for functional SDEs with multiplicative noise and applications, Stoch. Proc. Appl., 121 (2011), 2692-2710. doi: 10.1016/j.spa.2011.07.001.
[31]	F.-Y. Wang, Distribution-dependent SDEs for Landau type equations, Stoch. Proc. Appl., 128 (2018), 595-621. doi: 10.1016/j.spa.2017.05.006.
[32]	T. Yamada and S. Watanabe, On the uniqueness of solutions of stochastic differential equations Ⅰ & Ⅱ, J. Math. Kyoto Univ., 11 (1971), 155-167. doi: 10.1215/kjm/1250523620.