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We survey the connections between the six-vertex (square ice) model of 2d statistical mechanics and random matrix theory. We highlight the same universal probability distributions appearing on both sides, and also indicate related open…

Mathematical Physics · Physics 2024-04-11 Vadim Gorin , Matthew Nicoletti

On a finite graph, there is a natural family of Boltzmann probability measures on cycle-rooted spanning forests, parametrized by weights on cycles. For a certain subclass of those weights, we construct Gibbs measures in infinite volume, as…

Probability · Mathematics 2023-08-21 Héloïse Constantin

For an $n\times n$ Laplacian random matrix $L$ with Gaussian entries it is proven that the fluctuations of the largest eigenvalue and the largest diagonal entry of $L/\sqrt{n-1}$ are Gumbel. We first establish suitable non-asymptotic…

Probability · Mathematics 2021-01-22 Santiago Arenas-Velilla , Victor Pérez-Abreu

The Airy line ensemble is a positive-integer indexed system of random continuous curves whose finite dimensional distributions are given by the multi-line Airy process. It is a natural object in the KPZ universality class: for example, its…

Probability · Mathematics 2021-01-07 Alan Hammond

The extension of the statistical parton distributions to include their transverse momentum dependence (TMD) is revisited by considering that the proton target has a finite longitudinal momentum. The TMD will be generated by means of a…

High Energy Physics - Phenomenology · Physics 2015-06-15 Claude Bourrely , Franco Buccella , Jacques Soffer

The classical random matrix theory is mostly focused on asymptotic spectral properties of random matrices as their dimensions grow to infinity. At the same time many recent applications from convex geometry to functional analysis to…

Functional Analysis · Mathematics 2014-03-05 Mark Rudelson , Roman Vershynin

We study Gibbs partitions that typically form a unique giant component. The remainder is shown to converge in total variation toward a Boltzmann-distributed limit structure. We demon- strate how this setting encompasses arbitrary weighted…

Combinatorics · Mathematics 2016-12-15 Benedikt Stufler

We consider random polytopes in the $d$-dimensional Euclidean space that are the convex hulls i.i.d. random points selected according to beta-prime distributions. These distributions are rotationally symmetric, heavy-tailed, and their…

Metric Geometry · Mathematics 2026-03-24 Ferenc Fodor , Balázs Grünfelder

Latent-variable energy-based models (LVEBMs) assign a single normalized energy to joint pairs of observed data and latent variables, offering expressive generative modeling while capturing hidden structure. We recast maximum-likelihood…

Machine Learning · Computer Science 2025-10-20 Shiqin Tang , Shuxin Zhuang , Rong Feng , Runsheng Yu , Hongzong Li , Youzhi Zhang

A weighted recursive tree is an evolving tree in which vertices are assigned random vertex-weights and new vertices connect to a predecessor with a probability proportional to its weight. Here, we study the maximum degree and near-maximum…

Probability · Mathematics 2023-01-31 Laura Eslava , Bas Lodewijks , Marcel Ortgiese

Akemann, Ipsen and Kieburg recently showed that the squared singular values of products of M rectangular random matrices with independent complex Gaussian entries are distributed according to a determinantal point process with a correlation…

Mathematical Physics · Physics 2015-06-16 Arno B. J. Kuijlaars , Lun Zhang

We introduce and study the permanence properties of the class of linear transfers between probability measures. This class contains all cost minimizing mass transports, but also martingale mass transports, the Schrodinger bridge associated…

Analysis of PDEs · Mathematics 2018-10-29 Malcolm Bowles , Nassif Ghoussoub

The degree of entanglement of random pure states in bipartite quantum systems can be estimated from the distribution of the extreme Schmidt eigenvalues. For a bipartition of size M\geq N, these are distributed according to a…

Mathematical Physics · Physics 2011-06-07 Gernot Akemann , Pierpaolo Vivo

We study discrete $\beta$-ensembles as introduced in [17]. We obtain rigidity estimates on the particle locations, i.e. with high probability, the particles are close to their classical locations with an optimal error estimate. We prove the…

Probability · Mathematics 2017-08-04 Alice Guionnet , Jiaoyang Huang

Last passage percolation (LPP) is a model of a directed metric and a zero-temperature polymer where the main observable is a directed path evolving in a random environment accruing as energy the sum of the random weights along itself. When…

Probability · Mathematics 2025-01-07 Shirshendu Ganguly , Victor Ginsburg , Kyeongsik Nam

The transport of high-energy particles in the presence of small-scale, turbulent magnetic fields is a long-standing issue in astrophysics. Analytical theories on transport perpendicular to the large-scale magnetic field disagree with…

High Energy Astrophysical Phenomena · Physics 2025-10-03 Marco Kuhlen , Vo Hong Minh Phan , Philipp Mertsch

For the exactly solvable model of exponential last passage percolation on $\mathbb{Z}^2$, it is known that given any non-axial direction, all the semi-infinite geodesics starting from points in $\mathbb{Z}^2$ in that direction almost surely…

Probability · Mathematics 2023-08-15 Márton Balázs , Riddhipratim Basu , Sudeshna Bhattacharjee

We develop a new probabilistic method for deriving deviation estimates in directed planar polymer and percolation models. The key estimates are for exit points of geodesics as they cross transversal down-right boundaries. These bounds are…

Probability · Mathematics 2023-08-30 Elnur Emrah , Christopher Janjigian , Timo Seppäläinen

We study the asymptotic behavior of the partition function and the correlation kernel in random matrix ensembles of the form $\frac{1}{Z_n} \big|\det \big( M^2-tI \big)\big|^{\alpha} e^{-n\operatorname{Tr} V(M)}dM$, where $M$ is an $n\times…

Mathematical Physics · Physics 2016-03-24 Tom Claeys , Benjamin Fahs

We study computational aspects of repulsive Gibbs point processes, which are probabilistic models of interacting particles in a finite-volume region of space. We introduce an approach for reducing a Gibbs point process to the hard-core…

Data Structures and Algorithms · Computer Science 2023-12-15 Tobias Friedrich , Andreas Göbel , Maximilian Katzmann , Martin Krejca , Marcus Pappik