Abstract
We now turn to problems in statistical mechanics where the assumption of thermal equilibrium does not apply. In nonequilibrium problems, one should in principle solve the full Liouville equation, at least approximately. There are many situations in which one attempts to do that under different assumptions and conditions, giving rise to the Euler and Navier–Stokes equations, the Boltzmann equation, the Vlasov equation, etc.
An erratum to this chapter is available at http://dx.doi.org/10.1007/978-1-4614-6980-3_10
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-1-4614-6980-3_10
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptions9.9 Bibliography
B. Alder and T. Wainwright, Decay of the velocity correlation function, Phys. Rev. A 1 (1970), pp. 1–12.
R. Balescu, Statistical Dynamics, Matter out of Equilibrium, Imperial College Press, London, 1997.
D. Bernstein, Optimal prediction of the Burgers equation, Mult. Mod. Sim. 6 (2007), pp. 27–52.
S. Chandrasekhar, Stochastic problems in physics and astronomy, Rev. Mod. Phys. 15 (1943), pp. 1–88; reprinted in N. Wax, Selected Papers on Noise and Stochastic Processes, Dover, New York, 1954.
A.J. Chorin, O.H. Hald, and R. Kupferman, Optimal prediction and the Mori–Zwanzig representation of irreversible processes, Proc. Natl. Acad. Sci. USA 97 (2000), pp. 2968–2973.
A.J. Chorin, O.H. Hald, and R. Kupferman, Optimal prediction with memory, Physica D, 166 (2002), pp. 239–257.
A.J. Chorin and P. Stinis, Problem reduction, renormalization, and memory, Comm. Appl. Math. Comp. Sci. 1 (2005), pp. 1–27.
D. Evans and G. Morriss, Statistical Mechanics of Nonequilibrium Liquids, Academic, New York, 1990.
G. Ford, M. Kac, and P. Mazur, Statistical mechanics of assemblies of coupled oscillators, J. Math. Phys. 6 (1965), pp. 504–515.
S. Goldstein, On diffusion by discontinuous movements and on the telegraph equation, Q. J. Mech. Appl. Math., 4 (1951), pp. 129–156.
D. Givon, R. Kupferman, and A. Stuart, Extracting macroscopic dynamics, model problems and algorithms, Nonlinearity 17 (2004), pp. R55–R127.
O. H. Hald and P. Stinis, Optimal prediction and the rate of decay of solutions of the Euler equations in two and three dimensions, Proc. Nat. Acad. Sc. USA 104 (2007), pp. 6527–6532.
P. Hohenberg and B. Halperin, Theory of dynamical critical phenomena, Rev. Mod. Phys. 49 (1977) pp. 435–479.
M. Kac, A stochastic model related to the telegrapher’s equation, Rocky Mountain J. Math. 4 (1974), pp. 497–509.
A. Majda, I. Timofeyev, and E. Vanden Eijnden, A mathematical framework for stochastic climate models, Comm. Pure Appl. Math. 54, (2001), pp. 891–947.
G. Papanicolaou, Introduction to the asymptotic analysis of stochastic equations, in Modern Modeling of Continuum Phenomena, R. DiPrima (ed.), Providence RI, 1974.
P. Stinis, Stochastic optimal prediction for the Kuramoto–Sivashinski equation, Multiscale Model. Simul. 2 (2004), pp. 580–612.
K. Theodoropoulos, Y.H. Qian and I. Kevrekidis, Coarse stability and bifurcation analysis using timesteppers: a reaction diffusion example, Proc. Natl. Acad. Sci. USA 97 (2000), pp. 9840–9843.
R. Zwanzig, Problems in nonlinear transport theory, in Systems Far from Equilibrium, L. Garrido (ed.), Springer-Verlag, New York, 1980.
R. Zwanzig, Nonlinear generalized Langevin equations, J. Statist. Phys. 9 (1973), pp. 423–450.
R. Zwanzig, Irreversible Statistical Mechanics, Oxford, 2002.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Chorin, A.J., Hald, O.H. (2013). Generalized Langevin Equations. In: Stochastic Tools in Mathematics and Science. Texts in Applied Mathematics, vol 58. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6980-3_9
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6980-3_9
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6979-7
Online ISBN: 978-1-4614-6980-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)