SearcharxivSearch

arXiv · 2404.13444

Stationary Measure of the Open KPZ Equation through the Enaud-Derrida Representation

Abstract

Recent works of Barraquand and Le Doussal and Bryc, Kuznetsov, Wang, and Wesolowski gave a description of the open KPZ stationary measure as the sum of a Brownian motion and a Brownian motion reweighted by a Radon-Nikodym derivative. Subsequent work of Barraquand and Le Doussal used the Enaud-Derrida representation of the DEHP algebra to formulate the open ASEP stationary measure in terms of the sum of a random walk and a random walk reweighted by a Radon-Nikodym derivative. They show that this Radon-Nikodym derivative converges pointwise to the Radon-Nikodym derivative that characterizes the open KPZ stationary measure. This article proves that the corresponding sequence of measures converges weakly to the open KPZ stationary measure. This provides an alternative proof of the probabilistic formulation of the open KPZ stationary measure, which avoids dealing explicitly with finite dimensional distributions. We also provide the first construction of the measure on intervals of a general length and for the full range of parameters in the fan region $(u+v>0)$.

Explore related subjects

Keep this discovery

BibTeXRIS

Zoe Himwich. 2024-04-20. Stationary Measure of the Open KPZ Equation through the Enaud-Derrida Representation. https://arxiv.org/abs/2404.13444

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