SearcharxivSearch

arXiv · 1512.08364

Self-consistent theory for inhomogeneous systems with mesoscopic fluctuations

Abstract

We have developed a theory for inhomogeneous systems that allows for incorporation of effects of mesoscopic fluctuations. A hierarchy of equations relating the correlation and direct correlation functions for the local excess $ϕ({\bf r})$ of the volume fraction of particles $ζ$ has been obtained, and an approximation leading to a closed set of equations for the two-point functions has been introduced. We have solved numerically the self-consistent equations for one (1D) and three (3D) dimensional models with short-range attraction and long-rannge repulsion (SALR). Predictions for all the qualitative properties of the 1D model agree with the exact results, but only semi-quantitative agreement is obtained in the simplest version of the theory. The effects of fluctuations in the two considered 3D models are significantly different, despite very similar properties of these models in the mean-field approximation. In both cases we obtain the sequence of large - small - large compressibility for increasing $ζ$. The very small compressibility is accompanied by the oscillatory decay of correlations with the correlation length orders of magnitude larger than the size of particles. Only in one of the two considered models for decreasing temperature the small compressibility becomes very small and the large compressibility becomes very large, and eventually van der Waals loops appear. Further studies are necessary to determine the nature of the strongly inhomogeneous phase present for intermediate volume fractions in 3D.

Explore related subjects

Keep this discovery

BibTeXRIS

Alina Ciach, Wojciech T. Gozdz. 2016-04-28. Self-consistent theory for inhomogeneous systems with mesoscopic fluctuations. https://doi.org/10.1088/0953-8984%2F28%2F41%2F414010

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