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Poisson Voronoi diagrams are useful for modeling and describing various natural patterns and for generating random lattices. Although this particular space tessellation is intensively studied by mathematicians, in two- and three dimensional…

软凝聚态物质 · 物理学 2008-02-20 F. Jarai-Szabo , Z. Neda

The one-point probability distribution function (pdf) of the large-scale density field is an important tool to follow the evolution of cosmological structures. In this paper we present a new model for this pdf for all regimes and all…

天体物理学 · 物理学 2009-11-10 Patrick Valageas , Dipak Munshi

This paper proposes a comprehensive and unprecedented framework that streamlines the derivation of exact, compact -- yet tractable -- solutions for the probability density function (PDF) and cumulative distribution function (CDF) of the sum…

信号处理 · 电气工程与系统科学 2025-06-04 Fernando Darío Almeida García , Michel Daoud Yacoub , José Cândido Silveira Santos Filho

The statistical characterization of the sum of random variables (RVs) are useful for investigating the performance of wireless communication systems. We derive exact closed-form expressions for the probability density function (PDF) and…

信息论 · 计算机科学 2019-10-24 Hongyang Du , Jiayi Zhang , Julian Cheng , Bo Ai

The one-point probability distribution function (PDF) is a powerful summary statistic for non-Gaussian cosmological fields, such as the weak lensing (WL) convergence reconstructed from galaxy shapes or cosmic microwave background (CMB)…

宇宙学与河外天体物理 · 物理学 2021-01-04 Leander Thiele , J. Colin Hill , Kendrick M. Smith

Turbulence is essential for understanding the structure and dynamics of molecular clouds and star-forming regions. There is a need for adequate tools to describe and characterize the properties of turbulent flows. One-point probability…

天体物理学 · 物理学 2008-11-26 Ralf S. Klessen

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is…

流体动力学 · 物理学 2010-03-24 J. Bakosi , P. Franzese , Z. Boybeyi

This paper investigates probability density functions (PDFs) that are continuous everywhere, nearly uniform around the mode of distribution, and adaptable to a variety of distribution shapes ranging from bell-shaped to rectangular. From the…

机器学习 · 计算机科学 2022-04-01 Osamu Fujita

Context: Statistical properties of the cosmic density fields are to a large extent encoded in the shape of the one-point density probability distribution functions (PDF). In order to successfully exploit such observables, a detailed…

宇宙学与河外天体物理 · 物理学 2022-07-20 Francis Bernardeau

Mathematical models based on probability density functions (PDF) have been extensively used in hydrology and subsurface flow problems, to describe the uncertainty in porous media properties (e.g., permeability modelled as random field).…

流体动力学 · 物理学 2020-06-01 Matteo Icardi , Marco Dentz

Based on the canonical correlation analysis we derive series representations of the probability density function (PDF) and the cumulative distribution function (CDF) of the information density of arbitrary Gaussian random vectors as well as…

信息论 · 计算机科学 2022-07-13 Jonathan Huffmann , Martin Mittelbach

The probability distribution function (PDF) of the mass surface density of molecular clouds provides essential information about the structure of molecular cloud gas and condensed structures out of which stars may form. In general, the PDF…

星系天体物理 · 物理学 2015-06-22 Jörg Fischera

Fusing probabilistic information is a fundamental task in signal and data processing with relevance to many fields of technology and science. In this work, we investigate the fusion of multiple probability density functions (pdfs) of a…

信号处理 · 电气工程与系统科学 2023-01-20 Günther Koliander , Yousef El-Laham , Petar M. Djurić , Franz Hlawatsch

The joint probability distribution function (PDF) of the density within multiple concentric spherical cells is considered. It is shown how its cumulant generating function can be obtained at tree order in perturbation theory as the Legendre…

宇宙学与河外天体物理 · 物理学 2014-11-19 Francis Bernardeau , Christophe Pichon , Sandrine Codis

We present a new analytic calculation for the redshift-space evolution of the 1-point galaxy Probability Distribution Function (PDF). The nonlinear evolution of the matter density field is treated by second-order Eulerian perturbation…

天体物理学 · 物理学 2009-10-31 Peter Watts , Andrew Taylor

We investigate the single-point velocity probability density function (PDF) in three-dimensional fully developed homogeneous isotropic turbulence within the framework of PDF equations focussing on deviations from Gaussianity. A joint…

流体动力学 · 物理学 2011-02-18 Michael Wilczek , Anton Daitche , Rudolf Friedrich

The probability distribution function (PDF) of the mass surface density is an essential characteristic of the structure of molecular clouds or the interstellar medium in general. Observations of the PDF of molecular clouds indicate a…

星系天体物理 · 物理学 2015-06-18 Joerg Fischera

In probability density function (PDF) methods a transport equation is solved numerically to compute the time and space dependent probability distribution of several flow variables in a turbulent flow. The joint PDF of the velocity…

流体动力学 · 物理学 2010-06-04 J. Bakosi , P. Franzese , Z. Boybeyi

We introduce a method for calculating the probability density function (PDF) of a turbulent density field in three dimensions using only information contained in the projected two-dimensional column density field. We test the method by…

星系天体物理 · 物理学 2015-05-18 Christopher M. Brunt , Christoph Federrath , Daniel J. Price

One-point probability distribution functions (PDFs) of the cosmic matter density are powerful cosmological probes that extract non-Gaussian properties of the matter distribution and complement two-point statistics. Computing the covariance…

宇宙学与河外天体物理 · 物理学 2023-01-09 Cora Uhlemann , Oliver Friedrich , Aoife Boyle , Alex Gough , Alexandre Barthelemy , Francis Bernardeau , Sandrine Codis
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