SearcharxivSearch

arXiv · 2404.18364

Interface motion from Glauber-Kawasaki dynamics of non-gradient type

Abstract

We consider the Glauber-Kawasaki dynamics on a $d$-dimensional periodic lattice of size $N$, that is, a stochastic time evolution of particles performing random walks with interaction subject to the exclusion rule (Kawasaki part), in general, of non-gradient type, together with the effect of the creation and annihilation of particles (Glauber part) whose rates are set to favor two levels of particle density, called sparse and dense. We then study the limit of our dynamics under the hydrodynamic space-time scaling, that is, $1/N$ in space and a diffusive scaling $N^2$ for the Kawasaki part and another scaling $K=K(N)$, which diverges slower, for the Glauber part in time. In the limit as $N\to\infty$, we show that the particles autonomously make phase separation into sparse or dense phases at the microscopic level, and an interface separating two regions is formed at the macroscopic level and evolves under an anisotropic curvature flow. In the present article, we show that the particle density at the macroscopic level is well approximated by a solution of a reaction-diffusion equation with a nonlinear diffusion term of divergence form and a large reaction term. Furthermore, by applying the results of Funaki, Gu and Wang [arXiv:2404.12234] for the convergence rate of the diffusion matrix approximated by local functions, we obtain a quantitative hydrodynamic limit as well as the upper bound for the allowed diverging speed of $K=K(N)$. The above result for the derivation of the interface motion is proved by combining our result with that in a companion paper by Funaki and Park [arXiv:2403.01732], in which we analyzed the asymptotic behavior of the solution of the reaction-diffusion equation obtained in the present article and derived an anisotropic curvature flow in the situation where the macroscopic reaction term determined from the Glauber part is bistable and balanced.

Explore related subjects

Keep this discovery

BibTeXRIS

Tadahisa Funaki. 2024-04-29. Interface motion from Glauber-Kawasaki dynamics of non-gradient type. https://arxiv.org/abs/2404.18364

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

KEEP EXPLORING

Related papers

Averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection

In this paper, we study averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection. First, we derive a general averaging principle applicable to such equations under minimal assumptions. Subsequently, since the coefficients of the obtained averaged equation still depend on the small scaling parameter $\e$, we impose either periodic or asymptotic conditions on the coefficients, thereby obtain two distinct averaged equations whose coefficients are independent of $\e$ and establish two averaging principles. Stopping times and Khasminskii's time discretization schemes play an important role. Finally, a concrete example is provided to illustrate the applicability and validity of the theoretical results.

math.PR

Spectral properties of Random Matrices

We give the theoretical foundations of random matrix theory through the definitions of a random matrix, a random probability measure and the corresponding empirical spectral distribution. The technical tool we use is the Stieltjes transform method through which we prove optimal convergence of the empirical spectral distribution of random sample covariance matrices to the deterministic Marchenko-Pastur distribution. We also give new results about the rigidity of the eigenvalues of this random sample covariance matrix and the rate of their convergence. We then define the Dyson equation method to prove new local laws about a random matrix model that interpolates between the Marchenko-Pastur distribution, the elliptical law and the circular law. Through our work these local laws can be considered universal.

math.PR

Moments approach for the elephant random walk

We discuss the method of moments for the one-dimensional elephant random walk (ERW). We first derive a differential recurrence relation for the characteristic function of the ERW, which yields a corresponding system of recurrence relations for its moments. We then obtain asymptotic approximations for the moments in each of the three parameter regimes of the ERW. Finally, by establishing the convergence of the moments and verifying the corresponding moment-determinacy conditions, we identify the limiting distributions of the ERW in each regime.

math.PR