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We study the asymptotic distribution, as the volume parameter goes to 1, of the peak (largest part) of finite- or slowly-growing-width cylindric plane partitions weighted by their trace, seam, and volume. There are two natural asymptotic…

Probability · Mathematics 2021-12-01 Dan Betea , Alessandra Occelli

In this paper, we study the stationary distributions for the stochastic vertex models. Our main focus is the stochastic six vertex (S6V) model. We show that the extremal stationary distributions of the S6V model are given by product…

Probability · Mathematics 2023-03-23 Yier Lin

We consider $N$ non-intersecting Brownian bridges conditioned to stay below a fixed threshold. We consider a scaling limit where the limit shape is tangential to the threshold. In the large $N$ limit, we determine the limiting distribution…

Probability · Mathematics 2022-03-18 Patrik L. Ferrari , Bálint Vető

The 15-vertex model of Statistical Mechanics is studied on a square domain with partially oriented boundary. With DWBC the model would reduce to the six-vertex model, but more general boundary configurations are available. After…

Statistical Mechanics · Physics 2018-07-23 Kari Eloranta

Sub-Gaussian estimates for the natural random walk is typical of many regular fractal graphs. Subordination shows that there exist heavy tailed jump processes whose jump indices are greater than or equal to two. However, the existing…

Probability · Mathematics 2018-03-13 Mathav Murugan , Laurent Saloff-Coste

We define and study a model of winding for non-colliding particles in finite trees. We prove that the asymptotic behavior of this statistic satisfies a central limiting theorem, analogous to similar results on winding of bounded particles…

Combinatorics · Mathematics 2020-04-03 David A. Levin , Eric Ramos , Benjamin Young

In this paper, we use a formula obtained in [8] to study certain asymptotic behaviors of GUE (Gaussian unitary ensemble) correlators. More precisely, we obtain large genus asymptotics of enumerations of ordinary graphs and ribbon graphs…

Mathematical Physics · Physics 2025-12-19 Jiayi Zhao

Bootstrap percolation is a process that is used to model the spread of an infection on a given graph. In the model considered here each vertex is equipped with an individual threshold. As soon as the number of infected neighbors exceeds…

Probability · Mathematics 2022-10-25 Nils Detering , Thilo Meyer-Brandis , Konstantinos Panagiotou

We obtain an asymptotic formula for the partition function of the six-vertex model with partial domain wall boundary conditions in the ferroelectric phase region. The proof is based on a formula for the partition function involving the…

Mathematical Physics · Physics 2015-02-23 Pavel Bleher , Karl Liechty

We study the asymptotic behavior of wavelet coefficients of random processes with long memory. These processes may be stationary or not and are obtained as the output of non--linear filter with Gaussian input. The wavelet coefficients that…

Probability · Mathematics 2010-07-28 Marianne Clausel , François Roueff , Murad S. Taqqu , Ciprian A. Tudor

A cyclic random motion at finite velocity with orthogonal directions is considered in the plane and in $\mathbb{R}^3$. We obtain in both cases the explicit conditional distributions of the position of the moving particle when the number of…

Probability · Mathematics 2020-01-01 E. Orsingher , R. Garra , A. I. Zeifman

We identify general conditions under which regenerative processes with dependent cycles and cycle lengths are asymptotically independent. The result is applied to various models. In particular, independent L\'evy processes with dependent…

Probability · Mathematics 2017-11-22 Royi Jacobovic , Offer Kella

The dynamics of a point particle in a periodic array of spherical scatterers converges, in the limit of small scatterer size, to a random flight process, whose paths are piecewise linear curves generated by a Markov process with memory two.…

Mathematical Physics · Physics 2010-08-25 Jens Marklof , Andreas Strömbergsson

Several methods are available in the literature to stochastically compare random variables and random vectors. We introduce the notion of asymptotic stochastic order for random processes and define four such orders. Various properties and…

Probability · Mathematics 2021-03-03 Sugata Ghosh , Asok K. Nanda

We study the asymptotic behaviour of Markov processes on large weighted Erdos-Renyi graphs where the transition rates of the vertices are only influenced by the state of their neighbours and the corresponding weight on the edges. We find…

Probability · Mathematics 2020-04-07 Daniel Keliger , Illes Horvath

We consider an inhomogeneous Erd\H{o}s-R\'enyi random graph ensemble with exponentially decaying random disconnection probabilities determined by an i.i.d. field of variables with heavy tails and infinite mean associated to the vertices of…

Probability · Mathematics 2026-04-01 Luca Avena , Diego Garlaschelli , Rajat Subhra Hazra , Margherita Lalli

In this paper, we investigate the exact asymptotic behavior of the connectivity probability in the Erdos-Renyi graph G(n,p), under different asymptotic assumptions on the edge probability p=p(n). We propose a novel approach based on the…

Probability · Mathematics 2025-04-14 B. Chinyaev , A. Shklyaev

Non-asymptotic theory of random matrices strives to investigate the spectral properties of random matrices, which are valid with high probability for matrices of a large fixed size. Results obtained in this framework find their applications…

Probability · Mathematics 2013-08-02 Mark Rudelson

The exploration of a two-dimensional wind-driven ocean model with no-slip boundaries reveals the existence of a turbulent asymptotic regime where energy dissipation becomes independent of fluid viscosity. This asymptotic flow represents an…

Fluid Dynamics · Physics 2024-05-03 Lennard Miller , Antoine Venaille , Bruno Deremble

We present elliptical processes, a family of non-parametric probabilistic models that subsume Gaussian processes and Student's t processes. This generalization includes a range of new heavy-tailed behaviors while retaining computational…

Machine Learning · Computer Science 2023-11-23 Maria Bånkestad , Jens Sjölund , Jalil Taghia , Thomas B. Schöon
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