Gradient flow structure for McKean-Vlasov equations on discrete spaces

Matthias Erbar; Max  Fathi; Vaios  Laschos; André Schlichting

doi:10.3934/dcds.2016096

Article Contents

2016, Volume 36, Issue 12: 6799-6833. Doi: 10.3934/dcds.2016096

This issue Previous Article Compressible vortex sheets separating from solid boundaries Next Article Quantitative logarithmic Sobolev inequalities and stability estimates

Gradient flow structure for McKean-Vlasov equations on discrete spaces

1.
University of Bonn, Institute for Applied Mathematics, Endenicher Allee 60, 53115 Bonn
2.
University of California, Berkeley, Evans Hall, Berkeley, California 94720-3840
3.
Weierstrass Institut, Mohrenstraße 39, 10117 Berlin
4.
University of Bonn, Germany, Endenicher Allee 60, 53115 Bonn

Received: December 31, 2015

Revised: July 31, 2016

Published: May 2017

Abstract Related Papers Cited by

Abstract

In this work, we show that a family of non-linear mean-field equations on discrete spaces can be viewed as a gradient flow of a natural free energy functional with respect to a certain metric structure we make explicit. We also prove that this gradient flow structure arises as the limit of the gradient flow structures of a natural sequence of $N$-particle dynamics, as $N$ goes to infinity.

Keywords:

Mathematics Subject Classification: Primary: 60J27; Secondary: 34A34, 49J40, 49J45.

Citation:

Related Papers

Cited by

References

[1]	S. Adams, N. Dirr, M. A. Peletier and J. Zimmer, From a large-deviations principle to the Wasserstein gradient flow: a new micro-macro passage, Comm. Math. Phys., 307 (2011), 791-815.doi: 10.1007/s00220-011-1328-4.
[2]	L. Ambrosio, N. Gigli and G. Savaré, Gradient Flows in Metric Spaces and in the Space of Probability Measures, 2nd edition, Lectures in Mathematics ETH Zürich, Birkhäuser Verlag, Basel, 2008.doi: 10.1007/978-3-7643-8722-8.
[3]	L. Ambrosio, G. Savaré and L. Zambotti, Existence and stability for Fokker-Planck equations with log-concave reference measure, Probab. Theory Related Fields, 145 (2009), 517-564.doi: 10.1007/s00440-008-0177-3.
[4]	P. Billingsley, Probability and Measure, 2nd edition, Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics, John Wiley & Sons, Inc., New York, 1999.
[5]	F. Bolley, A. Guillin and C. Villani, Quantitative concentration inequalities for empirical measures on non-compact spaces, Probab. Theory Related Fields, 137 (2007), 541-593.doi: 10.1007/s00440-006-0004-7.
[6]	A. Budhiraja, P. Dupuis, M. Fischer and K. Ramanan, Limits of relative entropies associated with weakly interacting particle systems, Electron. J. Probab., 20 (2015), 22pp.doi: 10.1214/EJP.v20-4003.
[7]	A. Budhiraja, P. Dupuis, M. Fischer and K. Ramanan, Local stability of Kolmogorov forward equations for finite state nonlinear Markov processes, Electron. J. Probab., 20 (2015), 30pp.doi: 10.1214/EJP.v20-4004.
[8]	G. Buttazzo, Semicontinuity, Relaxation and Integral Representation in the Calculus of Variations, vol. 207 of Pitman Research Notes in Mathematics Series, Longman Scientific & Technical, Harlow; copublished in the United States with John Wiley & Sons, Inc., New York, 1989.
[9]	J. A. Carrillo, R. J. McCann and C. Villani, Kinetic equilibration rates for granular media and related equations: entropy dissipation and mass transportation estimates, Rev. Mat. Iberoamericana, 19 (2003), 971-1018.doi: 10.4171/RMI/376.
[10]	J. A. Carrillo, R. J. McCann and C. Villani, Contractions in the 2-Wasserstein length space and thermalization of granular media, Arch. Ration. Mech. Anal., 179 (2006), 217-263.doi: 10.1007/s00205-005-0386-1.
[11]	P. Cattiaux, A. Guillin and F. Malrieu, Probabilistic approach for granular media equations in the non-uniformly convex case, Probab. Theory Related Fields, 140 (2008), 19-40.doi: 10.1007/s00440-007-0056-3.
[12]	P. Dai Pra and F. den Hollander, McKean-Vlasov limit for interacting random processes in random media, J. Statist. Phys., 84 (1996), 735-772.doi: 10.1007/BF02179656.
[13]	S. Daneri and G. Savaré, Lecture notes on gradient flows and optimal transport, in Optimal Transportation, vol. 413 of London Math. Soc. Lecture Note Ser., Cambridge Univ. Press, Cambridge, 2014, 100-144.doi: 10.1017/CBO9781107297296.007.
[14]	D. A. Dawson and J. Gärtner, Large deviations from the McKean-Vlasov limit for weakly interacting diffusions, Stochastics, 20 (1987), 247-308.doi: 10.1080/17442508708833446.
[15]	E. De Giorgi, A. Marino and M. Tosques, Problems of evolution in metric spaces and maximal decreasing curve, Atti Accad. Naz. Lincei Rend. Cl. Sci. Fis. Mat. Natur. (8), 68 (1980), 180-187.
[16]	N. Dirr, V. Laschos and J. Zimmer, Upscaling from particle models to entropic gradient flows, J. Math. Phys., 53 (2012), 063704, 9 pp.doi: 10.1063/1.4726509.
[17]	R. Dobrushin, Vlasov equations, Functional Analysis and Its Applications, 13 (1979), 48-58,96.doi: 10.1007/BF01077243.
[18]	J. Dolbeault, B. Nazaret and G. Savaré, A new class of transport distances between measures, Calc. Var. Partial Differential Equations, 34 (2009), 193-231.doi: 10.1007/s00526-008-0182-5.
[19]	M. H. Duong, V. Laschos and M. Renger, Wasserstein gradient flows from large deviations of many-particle limits, ESAIM Control Optim. Calc. Var., 19 (2013), 1166-1188.doi: 10.1051/cocv/2013049.
[20]	P. Dupuis and R. S. Ellis, A Weak Convergence Approach to the Theory of Large Deviations, Wiley Series in Probability and Statistics: Probability and Statistics, John Wiley & Sons, Inc., New York, 1997, A Wiley-Interscience Publication.doi: 10.1002/9781118165904.
[21]	M. Erbar, Gradient flows of the entropy for jump processes, Ann. Inst. H. Poincaré Probab. Statist., 50 (2014), 920-945.doi: 10.1214/12-AIHP537.
[22]	M. Erbar and J. Maas, Ricci curvature of finite Markov chains via convexity of the entropy, Arch. Ration. Mech. Anal., 206 (2012), 997-1038.doi: 10.1007/s00205-012-0554-z.
[23]	M. Erbar and J. Maas, Gradient flow structures for discrete porous medium equations, Discrete Contin. Dyn. Syst., 34 (2014), 1355-1374.doi: 10.3934/dcds.2014.34.1355.
[24]	M. Erbar, J. Maas and M. Renger, From large deviations to Wasserstein gradient flows in multiple dimensions, Electron. Commun. Probab., 20 (2015), 1-12.doi: 10.1214/ECP.v20-4315.
[25]	M. Fathi, A gradient flow approach to large deviations for diffusion processes, J. Math. Pures Appl., (2016).doi: 10.1016/j.matpur.2016.03.018.
[26]	M. Fathi and M. Simon, The gradient flow approach to hydrodynamic limits for the simple exclusion process, In P. Gonçalves and A. J. Soares, From Particle Systems to Partial Differential Equations III: Particle Systems and PDEs III, Braga, Portugal, December 2014, 167-184, Springer International Publishing, Cham, 2016.
[27]	N. Gigli and J. Maas, Gromov-Hausdorff convergence of discrete transportation metrics, SIAM J. Math. Anal., 45 (2013), 879-899.doi: 10.1137/120886315.
[28]	R. Jordan, D. Kinderlehrer and F. Otto, The variational formulation of the Fokker-Planck equation, SIAM J. Math. Anal., 29 (1998), 1-17.doi: 10.1137/S0036141096303359.
[29]	C. Kipnis and C. Landim, Scaling Limits of Interacting Particle Systems, vol. 320 of Grundlehren der Mathematischen Wissenschaften, Springer-Verlag, Berlin, 1999.doi: 10.1007/978-3-662-03752-2.
[30]	D. A. Levin, M. J. Luczak and Y. Peres, Glauber dynamics for the mean-field Ising model: Cut-off, critical power law, and metastability, Probab. Theory Related Fields, 146 (2010), 223-265.doi: 10.1007/s00440-008-0189-z.
[31]	J. Maas, Gradient flows of the entropy for finite Markov chains, J. Funct. Anal., 261 (2011), 2250-2292.doi: 10.1016/j.jfa.2011.06.009.
[32]	F. Malrieu, Convergence to equilibrium for granular media equations and their Euler schemes, Ann. Appl. Probab., 13 (2003), 540-560.doi: 10.1214/aoap/1050689593.
[33]	N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller and E. Teller, Equations of state calculations by fast computing machines, J. Chem. Phys., 21 (1953), 1087-1091.doi: 10.1063/1.1699114.
[34]	A. Mielke, Geodesic convexity of the relative entropy in reversible Markov chains, Calc. Var. Partial Differential Equations, 48 (2013), 1-31.doi: 10.1007/s00526-012-0538-8.
[35]	A. Mielke, On evolutionary $\Gamma$-convergence for gradient systems, Springer International Publishing, Cham, 3 (2016), 187-249.doi: 10.1007/978-3-319-26883-5_3.
[36]	K. Oelschläger, A martingale approach to the law of large numbers for weakly interacting stochastic processes, Ann. Probab., 12 (1984), 458-479.doi: 10.1214/aop/1176993301.
[37]	F. Otto, The geometry of dissipative evolution equations: The porous medium equation, Comm. Partial Differential Equations, 26 (2001), 101-174.doi: 10.1081/PDE-100002243.
[38]	E. Sandier and S. Serfaty, Gamma-convergence of gradient flows with applications to Ginzburg-Landau, Comm. Pure Appl. Math., 57 (2004), 1627-1672.doi: 10.1002/cpa.20046.
[39]	A. Schlichting, Macroscopic limits of the Becker-Döring equations via gradient flows, arXiv:1607.08735.
[40]	S. Serfaty, Gamma-convergence of gradient flows on Hilbert and metric spaces and applications, Discrete Contin. Dyn. Syst., 31 (2011), 1427-1451.doi: 10.3934/dcds.2011.31.1427.
[41]	A.-S. Sznitman, Topics in Propagation of Chaos, in École d'Été de Probabilités de Saint-Flour XIX-1989, vol. 1464 of Lecture Notes in Math., Springer, Berlin, 1991, 165-251.doi: 10.1007/BFb0085169.