SearcharxivSearch

arXiv · 2402.16332

Lower bound for large transversal fluctuations in exactly solvable KPZ models

Abstract

The study of transversal fluctuation of the optimal path has been a crucial aspect of the Kadar-Parisi-Zhang (KPZ) universality class. In this paper, we establish a new probability lower bound, with optimal exponential order, for the rare event in which a given level of the optimal path has a large transversal fluctuation. We present our results in both zero and positive temperature settings. The previously known lower bounds were obtained in zero temperature models, and they hold for the maximum transversal fluctuation along the entire geodesic (Hammond-Sarkar'20) or the starting portion of the geodesic at a local scale (Agarwal'23). Our result improves upon these as now the rare event can demand where the large fluctuation occurs exactly along the optimal path, on both local and global scales. Our proof utilizes the coupling method: we first obtain a version of the estimate in the semi-infinite setting using duality and then transfer the result to finite paths using planar monotonicity. Our method differs from the previous works (Agarwal'23, Hammond-Sarkar'20), and in fact, we do not require fine information about the left tail moderate deviation, which played a crucial role in (Agarwal'23, Hammond-Sarkar'20).

Explore related subjects

Keep this discovery

BibTeXRIS

Xiao Shen. 2024-02-26. Lower bound for large transversal fluctuations in exactly solvable KPZ models. https://arxiv.org/abs/2402.16332

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