SearcharxivSearch

arXiv · 1207.5021

Nonlinear driven diffusive systems with dissipation: fluctuating hydrodynamics

Abstract

We consider a general class of nonlinear diffusive models with bulk dissipation and boundary driving, and derive its hydrodynamic description in the large size limit. Both the average macroscopic behavior and the fluctuating properties of the hydrodynamic fields are obtained from the microscopic dynamics. This analysis yields a fluctuating balance equation for the local energy density at the mesoscopic level, characterized by two terms: (i) a diffusive term, with a current that fluctuates around its average behavior given by nonlinear Fourier's law, and (ii) a dissipation term which is a general function of the local energy density. The quasi-elasticity of microscopic dynamics, required in order to have a nontrivial competition between diffusion and dissipation in the macroscopic limit, implies a noiseless dissipation term in the balance equation, so dissipation fluctuations are enslaved to those of the density field. The microscopic complexity is thus condensed in just three transport coefficients, the diffusivity, the mobility and a new dissipation coefficient, which are explicitly calculated within a local equilibrium approximation. Interestingly, the diffusivity and mobility coefficients obey an Einstein relation despite the fully nonequilibrium character of the problem. The general theory here presented is applied to a particular albeit broad family of systems, the simplest nonlinear dissipative variant of the so-called KMP model for heat transport. The theoretical predictions are compared to extensive numerical simulations, and an excellent agreement is found.

Explore related subjects

Keep this discovery

BibTeXRIS

A. Prados, A. Lasanta, Pablo I. Hurtado. 2012-07-20. Nonlinear driven diffusive systems with dissipation: fluctuating hydrodynamics. https://doi.org/10.1103/physreve.86.031134

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Universal sampling of spin systems across quenched disorder

Statistical physics extracts macroscopic laws by averaging over the many microscopic degrees of freedom of a system. Disordered systems demand a second and far harder average, one over the quenched randomness itself. The classic analytical routes, the replica and cavity methods, become uncontrolled outside mean-field or tree-like limits, and conventional numerical algorithms like parallel tempering require expensive, independent equilibration for every disorder realization. In this work, we introduce a universal neural variational framework that amortizes inference across the disorder ensemble, eliminating both the need for per-instance Markov chain equilibration and the cost of retraining instance-specific variational ansatzes. Built on an encoder-decoder Transformer architecture, after training once, it produces an explicit approximation to the Boltzmann distribution given previously unseen disorder realizations without further optimization. We validate this framework on 2D Edwards-Anderson models, and apply it to the random-bond Ising model, successfully capturing the Binder cumulant crossings near the Nishimori multicritical point. These results shift the object of variational inference from the single instance to the disorder ensemble, opening a route to frustrated many-body systems where instance-by-instance computation is prohibitive.

cond-mat.stat-mech

Information-Theoretic Characterization of Macroscopic Chaos Emerging from the Chemical Master Equation

Open chemical reaction networks exhibit stochastic concentration dynamics at finite system sizes, whereas their macroscopic limit is governed by deterministic rate equations that can display chaos. In this Letter, we show theoretically that a rate of information loss constructed from two-time mutual information recovers the Kolmogorov-Sinai entropy in the deterministic limit. We verify this result through numerical simulations of a Markov jump process for a three-species system involving seven reactions.

cond-mat.stat-mech

Orientational order on non-orientable domains

We study the statistical properties of passive and active many-body systems with orientational degrees of freedom on non-orientable domains. By rephrasing topological constraints as non-local symmetry relations on an orientable double-cover, we show that non-orientability eliminates global rotational soft modes without acting like an external field. In a passive XY model, this results in topological caging, where orientational fluctuations that exhibit conventional diffusive behavior on a torus saturate on a Klein bottle to a finite value that we compute exactly in the thermodynamic limit. In models of active self-propelled particles with orientational degrees of freedom, topological caging persists despite continuously changing interaction neighborhoods. In an active Ising spin model, non-orientability enforces the coexistence of ordered anti-parallel domains with vanishing global polar order, a state that is absent on orientable domains.

cond-mat.stat-mech