Langevin equation in systems with also negative temperatures

We discuss how to derive a Langevin equation (LE) in non standard systems, i.e. when the kinetic part of the Hamiltonian is not the usual quadratic function. This generalization allows to consider also cases with negative absolute temperature. We first give some phenomenological arguments suggesting the shape of the viscous drift, replacing the usual linear viscous damping, and its relation with the diffusion coefficient modulating the white noise term. As a second step, we implement a procedure to reconstruct the drift and the diffusion term of the LE from the time-series of the momentum of a heavy particle embedded in a large Hamiltonian system. The results of our reconstruction are in good agreement with the phenomenological arguments. Applying the method to systems with negative temperature, we can observe that also in this case there is a suitable Langevin equation, obtained with a precise protocol, able to reproduce in a proper way the statistical features of the slow variables. In other words, even in this context, systems with negative temperature do not show any pathology.

[1]  D. Sherrington Stochastic Processes in Physics and Chemistry , 1983 .

[2]  A. Pikovsky,et al.  Reconstruction of a random phase dynamics network from observations , 2017, 1711.06453.

[3]  M. Smoluchowski Zur kinetischen Theorie der Brownschen Molekularbewegung und der Suspensionen , 1906 .

[4]  Angelo Vulpiani,et al.  A consistent description of fluctuations requires negative temperatures , 2015, 1509.07369.

[5]  Robert S. MacKay,et al.  Langevin equation for slow degrees of freedom of Hamiltonian systems , 2010 .

[6]  N. Kampen,et al.  a Power Series Expansion of the Master Equation , 1961 .

[7]  A. Vulpiani,et al.  The fluctuation-dissipation relation: how does one compare correlation functions and responses? , 2009, 0907.2791.

[8]  U. Seifert Stochastic thermodynamics, fluctuation theorems and molecular machines , 2012, Reports on progress in physics. Physical Society.

[9]  A. Vulpiani,et al.  About thermometers and temperature , 2017, 1711.02349.

[10]  R. E. Turner Motion of a heavy particle in a one dimensional chain , 1960 .

[11]  Massimo Cencini,et al.  Predicting the future from the past: An old problem from a modern perspective , 2012, 1210.6758.

[12]  A. Vulpiani,et al.  Temperature in and out of equilibrium: A review of concepts, tools and attempts , 2017, 1711.03770.

[13]  Jaideep Pathak,et al.  Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data. , 2017, Chaos.

[14]  H Kantz,et al.  Indispensable finite time corrections for Fokker-Planck equations from time series data. , 2001, Physical review letters.

[15]  Christian Maes,et al.  The modified Langevin description for probes in a nonlinear medium , 2016, Journal of physics. Condensed matter : an Institute of Physics journal.

[16]  Andrea Puglisi,et al.  Granular Brownian motion , 2010, 1003.4462.

[17]  Roberto Franzosi,et al.  Discrete breathers and negative-temperature states , 2013 .

[18]  E Weinan,et al.  Heterogeneous multiscale methods: A review , 2007 .

[19]  J Peinke,et al.  Comment on "Indispensable finite time corrections for Fokker-Planck equations from time series data". , 2002, Physical review letters.

[20]  R. Zwanzig Nonlinear generalized Langevin equations , 1973 .

[21]  George Sugihara,et al.  Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling , 2015, Proceedings of the National Academy of Sciences.

[22]  Muhammad Sahimi,et al.  Approaching complexity by stochastic methods: From biological systems to turbulence , 2011 .

[23]  S. S. Hodgman,et al.  Negative Absolute Temperature for Motional Degrees of Freedom , 2012, Science.

[24]  P. Mazur,et al.  On the statistical mechanical theory of brownian motion , 1964 .

[25]  D. Lemons,et al.  Paul Langevin’s 1908 paper “On the Theory of Brownian Motion” [“Sur la théorie du mouvement brownien,” C. R. Acad. Sci. (Paris) 146, 530–533 (1908)] , 1997 .

[26]  A. Nawroth,et al.  An Iterative Procedure for the Estimation of Drift and Diffusion Coefficients of Langevin Processes , 2005 .

[27]  Lars Onsager,et al.  Fluctuations and Irreversible Processes , 1953 .

[28]  A. Stuart,et al.  Extracting macroscopic dynamics: model problems and algorithms , 2004 .

[29]  G. W. Ford,et al.  Statistical Mechanics of Assemblies of Coupled Oscillators , 1965 .

[30]  Paolo Politi,et al.  Nonequilibrium Statistical Physics: A Modern Perspective , 2017 .

[31]  Massimo Cencini,et al.  Transport properties of chaotic and non-chaotic many particle systems , 2007, 0712.0467.

[32]  Christian Maes,et al.  How Statistical Forces Depend on the Thermodynamics and Kinetics of Driven Media. , 2015, Physical review letters.

[33]  S. Takeno Continuum approximation for the motion of a heavy particle in one- and three-dimensional lattices. , 1962 .

[34]  Angelo Vulpiani,et al.  Chaos and Coarse Graining in Statistical Mechanics , 2008 .