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Generalized quantum measurements with N distinct outcomes are used for determining the density matrix, of order d, of an ensemble of quantum systems. The resulting probabilities are represented by a point in an N-dimensional space. It is…

Quantum Physics · Physics 2009-10-31 Asher Peres , Daniel Terno

In simple -- but selected -- quantum systems, the probability distribution determined by the ground state wave function is infinitely divisible. Like all simple quantum systems, the Euclidean temporal extension leads to a system that…

Quantum Physics · Physics 2007-05-23 John R. Klauder

Let $X_1,\ldots,X_M$ and $Y_1,\ldots,Y_N$ be independent zero mean normal random variables with variances $\sigma_{X_i}^2$, $i=1,\ldots,M$, and $\sigma_{Y_j}^2$, $j=1,\ldots,N$, respectively, and let $X=X_1\cdots X_M$ and $Y=Y_1\cdots Y_N$.…

Probability · Mathematics 2026-01-21 Robert E. Gaunt , Heather L. Sutcliffe

Transmutation is a technique for extending classical probability distributions in order to give them more flexibility. In this paper, we are interested in cubic transmutations of the Pareto distribution. We establish a general formula that…

Methodology · Statistics 2025-03-14 Edoh Katchekpele , Issa Cherif Geraldo , Tchilabalo Abozou Kpanzou

A novel approach towards construction of absolutely continuous distributions over the unit interval is proposed. Considering two absolutely continuous random variables with positive support, this method conditions on their convolution to…

Statistics Theory · Mathematics 2021-01-13 Aniket Biswas , Subrata Chakraborty

We consider the distribution of the sum and the maximum of a collection of independent exponentially distributed random variables. The focus is laid on the explicit form of the density functions (pdf) of non-i.i.d. sequences. Those are…

Probability · Mathematics 2013-07-16 Markus Bibinger

This article introduces a method for adjusting macro-particle weights within a particle distribution while preserving statistical and physical properties. The method allows the weights of the new macro-particle distribution to be determined…

Computational Physics · Physics 2024-03-19 Nicolas Pichoff , Samuel Marini

Normalizing flows provide a general mechanism for defining expressive probability distributions, only requiring the specification of a (usually simple) base distribution and a series of bijective transformations. There has been much recent…

The diffusion of finite-size hard-core interacting particles in two- or three-dimensional confined domains is considered in the limit that the confinement dimensions become comparable to the particle's dimensions. The result is a nonlinear…

Mathematical Physics · Physics 2017-03-23 Maria Bruna , S. Jonathan Chapman

The distribution of the sum of r-th power of standard normal random variables is a generalization of the chi-squared distribution. In this paper, we represent the probability density function of the random variable by an one-dimensional…

Classical Analysis and ODEs · Mathematics 2018-06-25 Tamio Koyama

We consider an agent interacting with an unknown environment. The environment is a function which maps natural numbers to natural numbers; the agent's set of hypotheses about the environment contains all such functions which are computable…

Artificial Intelligence · Computer Science 2007-12-31 Peter de Blanc

As observers of the universe we are physical systems within it. If the universe is very large in space and/or time, the probability becomes significant that the data on which we base predictions is replicated at other locations in…

High Energy Physics - Theory · Physics 2015-05-18 Mark Srednicki , James Hartle

Some concepts, such as non-compactness measure and condensing operators, defined on metric spaces are extended to uniform spaces. Such extensions allow us to locate, in the context of uniform spaces, some classical results existing in…

General Topology · Mathematics 2015-11-25 Raúl Fierro

We consider the problem of approximating two, possibly unrelated probability distributions from a single complex-valued function $\psi$ and its Fourier transform. We show that this problem always has a solution within a specified degree of…

Mathematical Physics · Physics 2011-01-12 W. D. Flanders , G. Japaridze

Probabilistic programming is becoming increasingly popular thanks to its ability to specify problems with a certain degree of uncertainty. In this work, we focus on term rewriting, a well-known computational formalism. In particular, we…

Programming Languages · Computer Science 2025-03-20 Germán Vidal

I present here some results on the statistical behaviour of large random matrices in an ensemble where the probability distribution is not a function of the eigenvalues only. The perturbative expansion can be cast in a closed form and the…

Disordered Systems and Neural Networks · Physics 2008-02-03 Giorgio Parisi

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that is routinely generated. In applications that are constrained by memory and computational intensity, excessively large…

Machine Learning · Computer Science 2023-02-28 Malik Hassanaly , Bruce A. Perry , Michael E. Mueller , Shashank Yellapantula

The distribution function of a random distance in three dimensions is given and some new three-dimensional d2-tests of randomness are suggested. We show that our test statistics are not correlated with the usual test statistics and are…

Applications · Statistics 2014-02-24 Sergii Koliada

Computing and storing probabilities is a hard problem as soon as one has to deal with complex distributions over multiple random variables. The problem of efficient representation of probability distributions is central in term of…

Artificial Intelligence · Computer Science 2016-08-16 David Bellot , Pierre Bessiere

Distance distributions are a key building block in stochastic geometry modelling of wireless networks and in many other fields in mathematics and science. In this paper, we propose a novel framework for analytically computing the closed…

Information Theory · Computer Science 2019-03-20 Ross Pure , Salman Durrani , Fei Tong , Jianping Pan