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We study probabilistic and combinatorial aspects of natural volume-and-trace weighted plane partitions and their continuous analogues. We prove asymptotic limit laws for the largest parts of these ensembles in terms of new and known hard-…

Combinatorics · Mathematics 2020-11-17 Dan Betea , Alessandra Occelli

In this paper, we study the asymptotic behaviour of plane partitions distributed according to a $q^{\text{Volume}}$-weighted Muttalib--Borodin ensemble and its associated discrete point process. We establish a Large Deviation Principle for…

Probability · Mathematics 2026-04-09 Jonathan Husson , Guido Mazzuca , Alessandra Occelli

We find the universal limiting correlation kernels of the Muttalib-Borodin (MB) ensembles with integer parameter $\theta \geq 2$ at $0$ in the transitive regime between the hard edge regime and the soft edge regime. This generalizes the…

Mathematical Physics · Physics 2025-10-09 Dong Wang , Shuai-Xia Xu

The theory of P\'olya ensembles of positive definite random matrices provides structural formulas for the corresponding biorthogonal pair, and correlation kernel, which are well suited to computing the hard edge large $N$ asymptotics. Such…

Mathematical Physics · Physics 2020-08-05 Peter J. Forrester , Shi-Hao Li

We investigate the limiting behavior of discrete determinantal point processes (DPPs) towards continuous DPPs when the size of the set to sample from goes to infinity. We propose a non-asymptotic characterization of this limit in terms of…

Probability · Mathematics 2026-03-03 Hugo Jaquard , Nicolas Keriven

We analyse the hard edge limit of the Muttalib-Borodin ensembles with general potential, and show that the limiting correlation kernel found in the ensemble with linear potential is universal. We also prove the Plancherel-Rotach type…

Mathematical Physics · Physics 2023-12-25 Dong Wang

In this paper, we consider Muttalib-Borodin ensemble of Laguerre type, a determinantal point process over $[0,\infty)$ which depends on the varying weights $x^{\alpha}e^{-nV(x)}$, $\alpha>-1$, and a parameter $\theta$. For $\theta$ being a…

Probability · Mathematics 2022-01-03 Dong Wang , Lun Zhang

We study probabilities of various rare events for the limiting point process that appears at the random matrix hard edge. We also show a transition from hard edge to bulk behavior. Asymptotic events studied include a central limit theorem…

Probability · Mathematics 2017-11-22 Diane Holcomb

A system of non-intersecting squared Bessel processes is considered which all start from one point and they all return to another point. Under the scaling of the starting and ending points when the macroscopic boundary of the paths touches…

Probability · Mathematics 2019-05-20 Steven Delvaux , Bálint Vető

Muttalib--Borodin ensembles are characterised by the pair interaction term in the eigenvalue probability density function being of the form $\prod_{1 \le j < k \le N}(\lambda_k - \lambda_j) (\lambda_k^\theta - \lambda_j^\theta)$. We study…

Mathematical Physics · Physics 2017-05-15 Peter J. Forrester , Dong Wang

The (BC type) z-measures are a family of four parameter $z, z', a, b$ probability measures on the path space of the nonnegative Gelfand-Tsetlin graph with Jacobi-edge multiplicities. We can interpret the $z$-measures as random point…

Representation Theory · Mathematics 2018-06-15 Cesar Cuenca

Noncolliding Brownian motion (Dyson's Brownian motion model with parameter $\beta=2$) and noncolliding Bessel processes are determinantal processes; that is, their space-time correlation functions are represented by determinants. Under a…

Probability · Mathematics 2015-02-13 Hirofumi Osada , Hideki Tanemura

The Muttalib-Borodin ensemble is a probability density function for $n$ particles on the positive real axis that depends on a parameter $\theta$ and a weight $w$. We consider a varying exponential weight that depends on an external field…

Classical Analysis and ODEs · Mathematics 2021-07-07 L. D. Molag

A discrete Gelfand-Tsetlin pattern is a configuration of particles in Z^2. The particles are arranged in a finite number of consecutive rows, numbered from the bottom. There is one particle on the first row, two particles on the second row,…

Probability · Mathematics 2015-07-24 Erik Duse , Anthony Metcalfe

We investigate the hard edge scaling limit of the ensemble defined by the squared singular values of the product of two coupled complex random matrices. When taking the coupling parameter to be dependent on the size of the product matrix,…

Mathematical Physics · Physics 2016-12-23 Gernot Akemann , Eugene Strahov

It has been proved by Bovier & Hartung [Elect. J. Probab. 19 (2014)] that the maximum of a variable-speed branching Brownian motion (BBM) in the weak correlation regime converges to a randomly shifted Gumbel distribution. The random shift…

Probability · Mathematics 2017-12-13 Constantin Glenz , Nicola Kistler , Marius A. Schmidt

We study the local statistics of orthogonal polynomial ensembles near a hard edge, subject to a multiplicative deformation of the measure. Probabilistically, this deformation corresponds to a position-dependent conditional thinning of the…

Mathematical Physics · Physics 2026-02-23 Leslie Molag , Guilherme L. F. Silva , Lun Zhang

We study infinite-horizon robust Markov decision processes (MDPs) on continuous state spaces with structured rectangular ambiguity set. The proposed ambiguity set falls within the convex hull of unknown generating kernels. We utilize the…

Optimization and Control · Mathematics 2026-05-28 Mengmeng Li , Yifan Hu , Daniel Kuhn , Yan Li

We consider the limiting process that arises at the hard edge of Muttalib--Borodin ensembles. This point process depends on $\theta > 0$ and has a kernel built out of Wright's generalized Bessel functions. In a recent paper, Claeys, Girotti…

Mathematical Physics · Physics 2019-07-01 Christophe Charlier , Jonatan Lenells , Julian Mauersberger

This paper characterizes the maximum mean discrepancies (MMD) that metrize the weak convergence of probability measures for a wide class of kernels. More precisely, we prove that, on a locally compact, non-compact, Hausdorff space, the MMD…

Machine Learning · Computer Science 2021-09-06 Carl-Johann Simon-Gabriel , Alessandro Barp , Bernhard Schölkopf , Lester Mackey
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