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We investigate the occurrence of additive and multiplicative structures in random subsets of the natural numbers. Specifically, for a Bernoulli random subset of $\mathbb{N}$ where each integer is included independently with probability…

Combinatorics · Mathematics 2025-11-03 Sukrit Chakraborty , Sayan Goswami , Sourav Kanti Patra

We use sets of assignments, a.k.a. teams, and measures on them to define probabilities of first-order formulas in given data. We then axiomatise first-order properties of such probabilities and prove a completeness theorem for our…

Logic · Mathematics 2016-09-09 Tapani Hyttinen , Gianluca Paolini , Jouko Väänänen

It is well known that the joint probability density of the eigenvalues of Gaussian ensembles of random matrices may be interpreted as a Coulomb gas. We review these classical results for hermitian and complex random matrices, with special…

Statistical Mechanics · Physics 2007-05-23 P. Leboeuf

This chapter provides a tutorial overview of first principles methods to describe the properties of matter at the ground state or equilibrium. It begins with a brief introduction to quantum and statistical mechanics for predicting the…

Computational Engineering, Finance, and Science · Computer Science 2020-10-14 Jianzhong Wu , Mengyang Gu

The Poisson boundary of a group G with a probability measure \mu is the space of ergodic components of the time shift in the path space of the associated random walk. Via a generalization of the classical Poisson formula it gives an…

Dynamical Systems · Mathematics 2007-05-23 Vadim A. Kaimanovich

We show that simple explicit formulas can be obtained for several relevant quantities related to the laws of the uniformly sampled Brownian bridge, Brownian meander and three dimensional Bessel process. To prove such results, we use the…

Probability · Mathematics 2013-11-11 Mathieu Rosenbaum , Marc Yor

We study a family of free stochastic processes whose covariance kernels $K$ may be derived as a transform of a tempered measure $\sigma$. These processes arise, for example, in consideration non-commutative analysis involving free…

Operator Algebras · Mathematics 2013-11-14 Daniel Alpay , Palle Jorgensen , Guy Salomon

We consider the distribution of free path lengths, or the distance between consecutive bounces of random particles, in an n-dimensional rectangular box. If each particle travels a distance R, then, as R tends to infinity the free path…

Dynamical Systems · Mathematics 2018-11-14 Samuel Holmin , Pär Kurlberg , Daniel Månsson

We continue here the study of free extreme values begun in Ben Arous and Voiculescu (2006). We study the convergence of the free point processes associated with free extreme values to a free Poisson random measure (Voiculescu (1998),…

Probability · Mathematics 2012-03-26 G. Ben Arous , V. Kargin

Free probability and random matrix theory has shown to be a fruitful combination in many fields of research, such as digital communications, nuclear physics and mathematical finance. The link between free probability and eigenvalue…

Probability · Mathematics 2007-05-23 Øyvind Ryan , Mérouane Debbah

Combining intuitive probabilistic assumptions with the basic laws of classical thermodynamics, using the latter to express probabilistic parameters in terms of the thermodynamic quantities, we get a simple unified derivation of the…

Probability · Mathematics 2022-05-03 Vassili N. Kolokoltsov

These lecture notes provide an introduction to free probability theory, with a focus on tools and techniques useful in the study of large random matrices. Topics include freeness, free cumulants, additive and multiplicative free…

Probability · Mathematics 2025-06-13 Vladislav Kargin

We derive exceedingly simple practical procedures revealing the quantum nature of states and measurements by the violation of classical upper bounds on the statistics of arbitrary measurements. Data analysis is minimum and definite…

Quantum Physics · Physics 2009-04-28 Ángel Rivas , Alfredo Luis

We consider the free additive convolution of two probability measures $\mu$ and $\nu$ on the real line and show that $\mu\boxplus\nu$ is supported on a single interval if $\mu$ and $\nu$ each has single interval support. Moreover, the…

Mathematical Physics · Physics 2018-10-30 Zhigang Bao , Laszlo Erdos , Kevin Schnelli

We consider the moment space $\mathcal{M}_n$ corresponding to $p \times p$ real or complex matrix measures defined on the interval $[0,1]$. The asymptotic properties of the first $k$ components of a uniformly distributed vector $(S_{1,n},…

Probability · Mathematics 2011-05-18 Jan Nagel , Holger Dette

This is the first installment of a series of papers whose aim is to lay a foundation for homotopy probability theory by establishing its basic principles and practices. The notion of a homotopy probability space is an enrichment of the…

Probability · Mathematics 2015-10-29 Jae-Suk Park

An important functional of Poisson random measure is the negative binomial process (NBP). We use NBP to introduce a generalized Poisson-Kingman distribution and its corresponding random discrete probability measure. This random discrete…

Statistics Theory · Mathematics 2023-07-04 Sadegh Chegini , Mahmoud Zarepour

We study the density of states (DOS) for disordered systems whose spectral statistics can be described by a Gaussian ensemble of almost diagonal Hermitian random matrices. The matrices have independent random entries $ H_{i \geq j} $ with…

Disordered Systems and Neural Networks · Physics 2016-08-31 Oleg Yevtushenko , Vladimir E. Kravtsov

We present a new approach to absolute continuity of laws of Poisson functionals. The theoretical framework is that of local Dirichlet forms as a tool to study probability spaces. The method gives rise to a new explicit calculus that we show…

Probability · Mathematics 2013-01-29 Nicolas Bouleau , Laurent Denis

Many statistical models can be simulated forwards but have intractable likelihoods. Approximate Bayesian Computation (ABC) methods are used to infer properties of these models from data. Traditionally these methods approximate the posterior…

Machine Learning · Statistics 2018-04-03 George Papamakarios , Iain Murray
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