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We use the ellipsoidal collapse approximation to investigate the nonlinear redshift space evolution of the density field with primordial non-Gaussianity of the local f_{nl}-type. We utilize the joint distribution of eigenvalues of the…

宇宙学与河外天体物理 · 物理学 2015-05-13 Tsz Yan Lam , Vincent Desjacques , Ravi K. Sheth

The Lyman-$\alpha$ forest is a highly non-linear field with a lot of information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics.…

宇宙学与河外天体物理 · 物理学 2017-10-18 Agnieszka M. Cieplak , Anže Slosar

We develop a new computational framework to solve the partial differential equations (PDEs) governing the flow of the joint probability density functions (PDFs) in continuous-time stochastic nonlinear systems. The need for computing the…

最优化与控制 · 数学 2019-08-08 Kenneth F. Caluya , Abhishek Halder

Many systems in nature and laboratories are far from equilibrium and exhibit significant fluctuations, invalidating the key assumptions of small fluctuations and short memory time in or near equilibrium. A full knowledge of Probability…

统计力学 · 物理学 2017-11-15 Eun-jin Kim , Lucille-Marie Tenk`es , Rainer Hollerbach , Ovidiu Radulescu

We report on probability-density-functions (PDF) of the mass density in numerical simulations of highly compressible hydrodynamic flows and the corresponding structure formation of Lagrangian particles advected by the flows. Numerical…

流体动力学 · 物理学 2009-11-13 Christoph Beetz , Christian Schwarz , Jürgen Dreher , Rainer Grauer

We study the non-Gaussian tail of the probability distribution function of density in cosmological N-Body simulations for a variety of initial conditions. We compare the behaviour of the non-Gaussian tail in the real space with that in the…

天体物理学 · 物理学 2007-05-23 J. S. Bagla , Suryadeep Ray

Intermittency in fluid turbulence can be evidentiated through the analysis of Probability Distribution Functions (PDF) of velocity fluctuations, which display a strong non-gaussian behavior at small scales. In this paper we investigate the…

混沌动力学 · 物理学 2007-05-23 V. Carbone , P. Giuliani , L. Sorriso-Valvo , P. Veltri , R. Bruno , E. Martines , V. Antoni

The properties of the probability distribution function of the cosmological continuous density field are studied. We present further developments and compare dynamically motivated methods to derive the PDF. One of them is based on the…

天体物理学 · 物理学 2009-10-22 F. Bernardeau , L. Kofman

A theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events in unforced zonal flows is provided within the Charney-Hasegawa-Mima (CHM) model. The governing equation is…

等离子体物理 · 物理学 2015-05-13 Johan Anderson , Gert J. J. Botha

The statistical properties of the $E \times B$ flux in different types of plasma turbulence simulations are investigated using probability density distribution functions (PDF). The physics included in the models ranges from two dimensional…

等离子体物理 · 物理学 2009-11-10 Volker Naulin , Odd Erik Garcia , Anders Henry Nielsen , Jens Juul Rasmussen

The shape and tails of partial distribution functions (PDF) for a financial signal, i.e. the S&P500 and the turbulent nature of the markets are linked through a model encompassing Tsallis nonextensive statistics and leading to evolution…

凝聚态物理 · 物理学 2009-11-10 Marcel Ausloos , Kristinka Ivanova

In probability density function (PDF) methods of turbulent flows, the joint PDF of several flow variables is computed by numerically integrating a system of stochastic differential equations for Lagrangian particles. A mathematically exact…

流体动力学 · 物理学 2010-06-17 J. Bakosi

A Lagrangian method is used to show that the power-law with a -7/2 exponent in the negative tail of the pdf of the velocity gradient and of velocity increments, predicted by E, Khanin, Mazel and Sinai (1997 Phys. Rev. Lett. 78, 1904) for…

凝聚态物理 · 物理学 2009-10-31 J. Bec , U. Frisch

Probability Distributions Functions (PDFs) of fluctuations of plasma edge parameters are skewed curves fairly different from normal distributions, whose shape appears almost independent of the plasma conditions and devices. We start from a…

等离子体物理 · 物理学 2009-04-23 F. Sattin

The behavior of the probability density function (PDF) transport equation at the limits of the probability space is studied from the point of view of fluid mechanics. Different boundary conditions are considered depending on the nature of…

流体动力学 · 物理学 2025-02-04 Luis Valiño , Juan Hierro

The likelihood calculation of a vast number of particles is the computational bottleneck for the particle filter in applications where the observation information is rich. For fast computing the likelihood of particles, a numerical fitting…

信息论 · 计算机科学 2017-07-31 Tiancheng Li , Shudong Sun , Juan M. Corchado , Tariq P. Sattar , Shubin Si

We present an extensive numerical study of the time irreversibility of the dynamics of heavy inertial particles in three-dimensional, statistically homogeneous and isotropic turbulent flows. We show that the probability density function…

流体动力学 · 物理学 2018-03-07 Akshay Bhatnagar , Anupam Gupta , Dhrubaditya Mitra , Rahul Pandit

We use a suite of 3D simulations of star-forming molecular clouds, with and without stellar feedback and magnetic fields, to investigate the effectiveness of different fitting methods for volume and column density probability distribution…

星系天体物理 · 物理学 2023-05-22 Avery Kiihne , Sabrina M. Appel , Blakesley Burkhart , Vadim A. Semenov , Christoph Federrath

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

The normal distribution is used as a unified probability distribution, however, our researcher found that it is not good agreed with the real-life dynamical system's data. We collected and analyzed representative naturally occurring data…

动力系统 · 数学 2020-11-06 Wei Ping Cheng , Zhi Hong Zhang , Pu Wang