Derivation of a Langevin equation in a system with multiple scales: the case of negative temperatures

Abstract

We consider the problem of building a continuous stochastic model, i.e. a Langevin or Fokker-Planck equation, through a well-controlled coarse-graining procedure. Such a method usually involves the elimination of the fast degrees of freedom of the "bath" to which the particle is coupled. Specifically, we look into the general case where the bath may be at negative temperatures, as found - for instance - in models and experiments with bounded effective kinetic energy. Here, we generalise previous studies by considering the case in which the coarse-graining leads to (i) a renormalisation of the potential felt by the particle, and (ii) spatially dependent viscosity and diffusivity. In addition, a particular relevant example is provided, where the bath is a spin system and a sort of phase transition takes place when going from positive to negative temperatures. A Chapman-Enskog-like expansion allows us to rigorously derive the Fokker-Planck equation from the microscopic dynamics. Our theoretical predictions show an excellent agrement with numerical simulations.

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Cited by in corpus (6)

• Statistical Mechanics of Systems with Negative Temperature
• Negative-temperature Fourier transport in one-dimensional systems
• H-theorem at negative temperature: the random exchange model with bounds
• Non-equilibrium attractor for non-linear stochastic dynamics
• Buckling in a rotationally invariant spin-elastic model
• Effective Equations in complex systems: from Langevin to machine learning