On Dean–Kawasaki Dynamics with Smooth Drift Potential
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Abstract
We consider the Dean–Kawasaki equation with smooth drift interaction potential and show that measure-valued solutions exist only in certain parameter regimes in which case they are given by finite Langevin particle systems with mean field interaction.
Keywords
Dean–Kawasaki equation Langevin dynamics Wasserstein diffusion Itô formula for measure-valued processesMathematics Subject Classification
60H15 60K35 82C22 60G57 82C31Notes
References
- 1.Andres, S., von Renesse, M.-K.: Particle approximation of the Wasserstein diffusion. J. Funct. Anal. 258(11), 3879–3905 (2010)MathSciNetCrossRefGoogle Scholar
- 2.Archer, A.J., Rauscher, M.: Dynamical density functional theory for interacting Brownian particles: stochastic or deterministic? J. Phys. A 37(40), 9325–9333 (2004)ADSMathSciNetCrossRefGoogle Scholar
- 3.Bertini, L., De Sole, A., Gabrielli, D., Jona-Lasinio, G., Landim, C.: Macroscopic fluctuation theory. Rev. Mod. Phys. 87, 593–636 (2015)ADSMathSciNetCrossRefGoogle Scholar
- 4.Cornalba, F., Shardlow, T., Zimmer, J.: From weakly interacting particles to a regularised Dean-Kawasaki model. arXiv:1811.06448 (2018)
- 5.Cornalba, F., Shardlow, T., Zimmer, J.: A regularized Dean-Kawasaki model: derivation and analysis. SIAM J. Math. Anal. 51(2), 1137–1187 (2019)MathSciNetCrossRefGoogle Scholar
- 6.Dawson, D.A.: Measure-valued Markov processes, École d’Été de Probabilités de Saint-Flour XXI—1991. Lecture Notes in Mathematics, vol. 1541, pp. 1–260. Springer, Berlin (1993)Google Scholar
- 7.de la Torre, J.A., Espanol, P., Donev, A.: Finite element discretization of non-linear diffusion equations with thermal fluctuations. J. Chem. Phys. 142(9), 094115 (2015)ADSCrossRefGoogle Scholar
- 8.Dean, D.S.: Langevin equation for the density of a system of interacting Langevin processes. J. Phys. A 29(24), L613–L617 (1996)ADSMathSciNetCrossRefGoogle Scholar
- 9.Delfau, J.-B., Ollivier, H., López, C., Blasius, B., Hernández-Garcí a, E.: Pattern formation with repulsive soft-core interactions: discrete particle dynamics and Dean-Kawasaki equation. Phys. Rev. E 94(4), 042120 (2016)ADSMathSciNetCrossRefGoogle Scholar
- 10.Donev, A., Fai, T.G., Vanden-Eijnden, E.: A reversible mesoscopic model of diffusion in liquids: from giant fluctuations to Fick’s law. J. Stat. Mech.: Theory Exp. 2014(4), P04004 (2014)CrossRefGoogle Scholar
- 11.Donev, A., Vanden-Eijnden, E.: Dynamic density functional theory with hydrodynamic interactions and fluctuations. J. Chem. Phys. 140(23), 234115 (2014)ADSCrossRefGoogle Scholar
- 12.Embacher, P., Dirr, N., Zimmer, J., Reina, C.: Computing diffusivities from particle models out of equilibrium. Proc. R. Soc. A 474(2212), 20170694 (2018)ADSMathSciNetCrossRefGoogle Scholar
- 13.Fehrman, B., Gess, B.: Well-posedness of nonlinear diffusion equations with nonlinear, conservative noise. Arch. Ration. Mech. Anal. 233(1), 249–322 (2019)MathSciNetCrossRefGoogle Scholar
- 14.Frusawa, H., Hayakawa, R.: On the controversy over the stochastic density functional equations. J. Phys. A 33(15), L155 (2000)ADSMathSciNetCrossRefGoogle Scholar
- 15.Giacomin, G., Lebowitz, J.L., Presutti, E.: Deterministic and stochastic hydrodynamic equations arising from simple microscopic model systems, Stochastic partial differential equations: six perspectives. Mathematical Surveys and Monographs, vol. 64, pp. 107–152. American Mathematical Society, Providence, RI (1999)zbMATHGoogle Scholar
- 16.Jack, R.L., Zimmer, J.: Geometrical interpretation of fluctuating hydrodynamics in diffusive systems. J. Phys. A 47(48), 485001 (2014)MathSciNetCrossRefGoogle Scholar
- 17.Jacquin, Hugo, Kim, Bongsoo, Kawasaki, Kyozi, van Wijland, Frédéric: Brownian dynamics: From glassy to trivial. Phys. Rev. E 91, 022130 (2015)ADSCrossRefGoogle Scholar
- 18.Kallenberg, O.: Foundations of Modern Probability, Probability and Its Applications (New York), 2nd edn. Springer, New York (2002)zbMATHGoogle Scholar
- 19.Kawasaki, K.: Stochastic model of slow dynamics in supercooled liquids and dense colloidal suspensions. Physica A 208(1), 35–64 (1994)ADSCrossRefGoogle Scholar
- 20.Kim, B., Kawasaki, K., Jacquin, H., van Wijland, F.: Equilibrium dynamics of the Dean-Kawasaki equation: mode-coupling theory and its extension. Phys. Rev. E 89, 012150 (2014)ADSCrossRefGoogle Scholar
- 21.Kipnis, C., Olla, S., Varadhan, S.R.S.: Hydrodynamics and large deviation for simple exclusion processes. Commun. Pure Appl. Math. 42(2), 115–137 (1989)MathSciNetCrossRefGoogle Scholar
- 22.Konarovskyi, V.: Coalescing-fragmentation Wasserstein dynamics: particle approach. arXiv:1711.03011 (2017)
- 23.Konarovskyi, V., von Renesse, M.: Reversible coalescing-fragmentating Wasserstein dynamics on the real line. arXiv:1709.02839 (2017)
- 24.Konarovskyi, V., von Renesse, M.-K.: Modified massive Arratia flow and Wasserstein diffusion. Commun. Pure Appl. Math. 72(4), 764–800 (2019)MathSciNetCrossRefGoogle Scholar
- 25.Konarovskyi, V., Lehmann, T., von Renesse, M.-K.: Dean-Kawasaki dynamics: ill-posedness vs. triviality. Electron. Commun. Probab 24, 8–9 (2019)MathSciNetCrossRefGoogle Scholar
- 26.Marconi, U.M.B., Tarazona, P.: Dynamic density functional theory of fluids. J. Chem. Phys. 110(16), 8032–8044 (1999)ADSCrossRefGoogle Scholar
- 27.Marconi, U.M.B., Tarazona, P.: Dynamic density functional theory of fluids. J. Phys.: Condens. Matter 12(8A), A413 (2000)ADSGoogle Scholar
- 28.Marx, V.: A new approach for the construction of a Wasserstein diffusion. Electron. J. Probab. 23, 54 (2018)MathSciNetCrossRefGoogle Scholar
- 29.Rotskoff, G.M., Vanden-Eijnden, E.: Neural networks as interacting particle systems: asymptotic convexity of the loss landscape and universal scaling of the approximation error. Preprint. arXiv:1805.00915 (2018)
- 30.Sadhu, T., Derrida, B.: Correlations of the density and of the current in non-equilibrium diffusive systems. J. Stat. Mech.: Theory Exp. 2016(11), 113202 (2016)MathSciNetCrossRefGoogle Scholar
- 31.Schiavo, L.D.: The Dirichlet-Ferguson diffusion on the space of probability measures over a closed Riemannian manifold. arXiv:1811.11598 (2018)
- 32.Solon, A.P., Cates, M.E., Tailleur, J.: Active Brownian particles and run-and-tumble particles: a comparative study. Eur. Phys. J. Spec. Top. 224(7), 1231–1262 (2015)CrossRefGoogle Scholar
- 33.Spohn, H.: Large Scale Dynamics of Interacting Particles. Springer, Berlin (1991)CrossRefGoogle Scholar
- 34.Velenich, A., Chamon, C., Cugliandolo, L.F., Kreimer, D.: On the Brownian gas: a field theory with a Poissonian ground state. J. Phys. A 41(23), 235002 (2008)MathSciNetCrossRefGoogle Scholar
- 35.Veretennikov, A.Y., Veretennikova, E.V.: On partial derivatives of multivariate Bernstein polynomials. Sib. Adv. Math. 26(4), 294–305 (2016)CrossRefGoogle Scholar
- 36.von Renesse, M.-K., Sturm, K.-T.: Entropic measure and Wasserstein diffusion. Ann. Probab. 37(3), 1114–1191 (2009)MathSciNetCrossRefGoogle Scholar
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