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We study a 2-parametric family of probability measures on an infinite-dimensional simplex (the Thoma simplex). These measures originate in harmonic analysis on the infinite symmetric group (S.Kerov, G.Olshanski and A.Vershik, Comptes Rendus…

Representation Theory · Mathematics 2008-03-02 Grigori Olshanski

A representation of heterogeneous stochastic populations that are composed of sub-populations with different levels of distinguishability is introduced together with an analysis of its properties. It is demonstrated that any instance of…

Probability · Mathematics 2019-12-02 Jeremie Houssineau , Daniel E. Clark

The aim of the present survey paper is to provide an accessible introduction to a new chapter of representation theory - harmonic analysis for noncommutative groups with infinite-dimensional dual space. I omitted detailed proofs but tried…

Representation Theory · Mathematics 2007-05-23 Grigori Olshanski

In these lectures we discuss some elementary concepts in connection with the theory of symmetric spaces applied to ensembles of random matrices. We review how the relationship between random matrix theory and symmetric spaces can be used in…

Mathematical Physics · Physics 2007-05-23 Ulrika Magnea

This article (written in Polish) is aimed for a wide mathematical audience. It is intended as an introductory text concerning problems of the asymptotic theory of symmetric groups.

Representation Theory · Mathematics 2018-12-04 Piotr Sniady

We present an overview of selected topics in random permutations and random partitions highlighting analogies with random matrix theory.

Combinatorics · Mathematics 2011-04-22 Grigori Olshanski

This brief article gives an overview of quantum mechanics as a {\em quantum probability theory}. It begins with a review of the basic operator-algebraic elements that connect probability theory with quantum probability theory. Then quantum…

Quantum Physics · Physics 2020-02-04 Hendra I. Nurdin

We introduce categories of extended Gaussian maps and Gaussian relations which unify Gaussian probability distributions with relational nondeterminism in the form of linear relations. Both have crucial and well-understood applications in…

Logic in Computer Science · Computer Science 2023-06-08 Dario Stein , Richard Samuelson

There has been quite some activity and progress concerning spectral asymptotics of random operators that are defined on percolation subgraphs of different types of graphs. In this short survey we record some of these results and explain the…

Mathematical Physics · Physics 2015-03-13 Peter Müller , Peter Stollmann

We give a summary of the results from Parts I-V (math.RT/9804086, math.RT/9804087, math.RT/9804088, math.RT/9810013, math.RT/9810014). Our work originated from harmonic analysis on the infinite symmetric group. The problem of spectral…

Representation Theory · Mathematics 2007-05-23 Alexei Borodin , Grigori Olshanski

Domain theory has a long history of applications in theoretical computer science and mathematics. In this article, we explore the relation of domain theory to probability theory and stochastic processes. The goal is to establish a theory in…

Logic · Mathematics 2020-02-06 Michael Mislove

Representation theory and the theory of symmetric functions have played a central role in Random Matrix Theory in the computation of quantities such as joint moments of traces and joint moments of characteristic polynomials of matrices…

Mathematical Physics · Physics 2025-04-18 Bhargavi Jonnadula , Jonathan P. Keating , Francesco Mezzadri

We introduce the mathematical theory of the particle systems that interact via permutations, where the transition rates are assigned not to the jumps from a site to a site, but to the permutations themselves. This permutation processes can…

Probability · Mathematics 2007-05-23 Yevgeniy Kovchegov

These are lecture notes written at the University of Zurich during spring 2014 and spring 2015. The first part of the notes gives an introduction to probability theory. It explains the notion of random events and random variables,…

Probability · Mathematics 2020-11-02 Nima Moshayedi

Probabilistic graphical modeling is a branch of machine learning that uses probability distributions to describe the world, make predictions, and support decision-making under uncertainty. Underlying this modeling framework is an elegant…

Machine Learning · Computer Science 2025-07-24 Jacqueline Maasch , Willie Neiswanger , Stefano Ermon , Volodymyr Kuleshov

Few, if any, applications of quantum technology are as widely known as the quantum simulation of quantum matter. Consequently, many interesting questions have been sparked at the intersection of condensed matter, quantum chemistry, and…

Quantum Physics · Physics 2025-12-17 James Daniel Whitfield

Since their appearance in the 1950s, computational models capable of performing probabilistic choices have received wide attention and are nowadays pervasive in almost every areas of computer science. Their development was also inextricably…

Logic in Computer Science · Computer Science 2024-09-19 Melissa Antonelli , Ugo Dal Lago , Paolo Pistone

We review a recent development at the interface between discrete mathematics on one hand and probability theory and statistics on the other, specifically the use of Markov chains and their boundary theory in connection with the asymptotics…

Statistics Theory · Mathematics 2023-11-03 Rudolf Grübel

We explore the interplay between random and deterministic phenomena using a representation of uncertainty based on the measure-theoretic concept of outer measure. The meaning of the analogues of different probabilistic concepts is…

Methodology · Statistics 2020-04-21 Jeremie Houssineau

In this article, we discuss the remarkable connection between two very different fields, number theory and nuclear physics. We describe the essential aspects of these fields, the quantities studied, and how insights in one have been…

Number Theory · Mathematics 2010-11-16 Frank W. K. Firk , Steven J. Miller
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