Noise-Induced Drift in Stochastic Differential Equations with Arbitrary Friction and Diffusion in the Smoluchowski-Kramers Limit

We consider the dynamics of systems with arbitrary friction and diffusion. These include, as a special case, systems for which friction and diffusion are connected by Einstein fluctuation-dissipation relation, e.g. Brownian motion. We study the limit where friction effects dominate the inertia, i.e. where the mass goes to zero (Smoluchowski-Kramers limit). Using the Itô stochastic integral convention, we show that the limiting effective Langevin equations has different drift fields depending on the relation between friction and diffusion. Alternatively, our results can be cast as different interpretations of stochastic integration in the limiting equation, which can be parametrized by α∈ℝ. Interestingly, in addition to the classical Itô (α=0), Stratonovich (α=0.5) and anti-Itô (α=1) integrals, we show that position-dependent α=α(x), and even stochastic integrals with α∉[0,1] arise. Our findings are supported by numerical simulations.

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  H. Kramers Brownian motion in a field of force and the diffusion model of chemical reactions , 1940 .

[3]  Dr. M. G. Worster Methods of Mathematical Physics , 1947, Nature.

[4]  Edward Nelson Dynamical Theories of Brownian Motion , 1967 .

[5]  M. Turelli Random environments and stochastic calculus. , 1977, Theoretical population biology.

[6]  D. Ermak,et al.  Brownian dynamics with hydrodynamic interactions , 1978 .

[7]  H. Sussmann On the Gap Between Deterministic and Stochastic Ordinary Differential Equations , 1978 .

[8]  C. Gardiner Handbook of Stochastic Methods , 1983 .

[9]  S. Swain Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences , 1984 .

[10]  L. Arnold Stochastic Differential Equations: Theory and Applications , 1992 .

[11]  W. Ebeling Stochastic Processes in Physics and Chemistry , 1995 .

[12]  S. Shreve,et al.  Stochastic differential equations , 1955, Mathematical Proceedings of the Cambridge Philosophical Society.

[13]  J. Breslin The University of Arizona , 2000 .

[14]  P. Lancon,et al.  Drift without flux: Brownian walker with a space dependent diffusion coefficient , 2001 .

[15]  A. Veretennikov,et al.  On the poisson equation and diffusion approximation 3 , 2001, math/0506596.

[16]  Andrew M. Stuart,et al.  A model for preferential concentration , 2002 .

[17]  M. Freidlin Some Remarks on the Smoluchowski–Kramers Approximation , 2004 .

[18]  G. Pavliotis,et al.  Itô versus Stratonovich white-noise limits for systems with inertia and colored multiplicative noise. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Ericka Stricklin-Parker,et al.  Ann , 2005 .

[20]  Andrew M. Stuart,et al.  Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times , 2005, Multiscale Model. Simul..

[21]  E. Saar Multiscale Methods , 2006, astro-ph/0612370.

[22]  École d'été de probabilités de Saint-Flour,et al.  Differential equations driven by rough paths , 2007 .

[23]  P. Ao,et al.  On the existence of potential landscape in the evolution of complex systems , 2007, Complex..

[24]  T C Lubensky,et al.  State-dependent diffusion: Thermodynamic consistency and its path integral formulation. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  P. Ao Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics from Darwinian Dynamics. , 2008, Communications in theoretical physics.

[26]  Grigorios A. Pavliotis,et al.  Multiscale Methods: Averaging and Homogenization , 2008 .

[27]  Xiongzhi Chen Brownian Motion and Stochastic Calculus , 2008 .

[28]  J. Wehr,et al.  Influence of noise on force measurements. , 2010, Physical review letters.

[29]  J. Wehr,et al.  Force measurement in the presence of Brownian noise: equilibrium-distribution method versus drift method. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.