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The probability density function (PDF) of a random variable associated with the solution of a partial differential equation (PDE) with random parameters is approximated using a truncated series expansion. The random PDE is solved using two…

Numerical Analysis · Mathematics 2021-01-25 Giacomo Capodaglio , Max Gunzburger , Henry P. Wynn

We introduce a theory for the development of a transitional column density $\Sigma_{\rm TP}$ between the lognormal and the power-law forms of the probability distribution function (PDF) in a molecular cloud. Our turbulent…

Solar and Stellar Astrophysics · Physics 2019-08-14 Sayantan Auddy , Shantanu Basu , Takahiro Kudoh

If two probability density functions (PDFs) have values for their first $n$ moments which are quite close to each other (upper bounds of their differences are known), can it be expected that the PDFs themselves are very similar? Shown below…

Statistics Theory · Mathematics 2018-08-16 Pranava Chaitanya Jayanti , Konstantina Trivisa

Experimental results for the evolution of the probability distribution function (PDF) of a scalar mixed by a turbulence flow in a channel are presented. The sequence of PDF from an initial skewed distribution to a sharp Gaussian is found to…

Classical Physics · Physics 2009-11-13 Antoine Venaille , Joel Sommeria

The analytical formalism to obtain the probability distribution functions (PDFs) of spherically-averaged cosmic densities and velocity divergences in the mildly non-linear regime is presented. A large-deviation principle is applied to those…

Cosmology and Nongalactic Astrophysics · Physics 2017-08-03 Cora Uhlemann , Sandrine Codis , Oliver Hahn , Christophe Pichon , Francis Bernardeau

Supersonic turbulence is a key player in controlling the structure and star formation potential of molecular clouds (MCs). The three-dimensional (3D) turbulent Mach number, $\mathcal{M}$, allows us to predict the rate of star formation.…

Astrophysics of Galaxies · Physics 2019-07-17 James R. Beattie , Christoph Federrath , Ralf S. Klessen , Nicola Schneider

In this paper, we study the statistical evolution of the large-scale structure (LSS), focusing on the joint probability distribution function (PDF) of the coarse-grained cosmic field and its role in constructing effective dynamics. As the…

Cosmology and Nongalactic Astrophysics · Physics 2021-10-20 Xin Wang

We investigate the statistics of turbulence in emulsions of two-immiscible fluids of same density. We compute for the first time velocity increments between points conditioned to be located in the same phase or in different phases and…

We introduce the state-of-the-art deep learning Denoising Diffusion Probabilistic Model (DDPM) as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps. We adopt…

Astrophysics of Galaxies · Physics 2023-06-28 Duo Xu , Jonathan C. Tan , Chia-Jung Hsu , Ye Zhu

We present the first prediction of the probability distribution function (PDF) for self-organization of shear flows modeled by a nonlinear diffusion equation with a stochastic forcing. A novel non-perturbative method based on a coherent…

Fluid Dynamics · Physics 2009-04-26 Eun-jin Kim , Han-Li Liu , Johan Anderson

We solve an inverse problem for fluid particle pair-statistics: we show that a time sequence of probability density functions (PDF's) of separations can be exactly reproduced by solving the diffusion equation with a suitable time-dependent…

Fluid Dynamics · Physics 2015-06-16 Gregory L. Eyink , Damien Benveniste

For Poisson-Delaunay triangulations in $d$-dimensional Euclidean space $\mathbb{R}^{d}$, a structured and computationally efficient form of the probability density function (PDF) of the volume of a typical cell is analytically derived in…

Information Theory · Computer Science 2018-05-11 Minghua Xia , Sonia Aïssa

The time evolution of the probability density function (PDF) of the mass density is formulated and solved for systems in free-fall using a simple appoximate function for the collapse of a sphere. We demonstrate that a pressure-free collapse…

Astrophysics of Galaxies · Physics 2015-06-17 Philipp Girichidis , Lukas Konstandin , Anthony P. Whitworth , Ralf S. Klessen

We present an analytical description of the probability distribution function (PDF) of the smoothed three-dimensional matter density field for modified gravity and dark energy. Our approach, based on the principles of Large Deviations…

Cosmology and Nongalactic Astrophysics · Physics 2022-04-05 Matteo Cataneo , Cora Uhlemann , Christian Arnold , Alex Gough , Baojiu Li , Catherine Heymans

Motivated by oceanographic observational datasets, we propose a probabilistic neural network (PNN) model for calculating turbulent energy dissipation rates from vertical columns of velocity and density gradients in density stratified…

The extraction of inhomogeneous 3-dimensional densities around tagged solutes from molecular simulations is known to have a very high computational cost because this is traditionally performed by collecting histograms, with each discrete…

Chemical Physics · Physics 2019-08-22 Samuel W. Coles , Daniel Borgis , Rodolphe Vuilleumier , Benjamin Rotenberg

An important idea underlying a plausible dynamical theory of circulation in three-dimensional turbulence is the so-called Area Rule, according to which the probability density function (PDF) of the circulation around closed loops depends…

Fluid Dynamics · Physics 2021-10-22 Kartik P. Iyer , Sachin S. Bharadwaj , Katepalli R. Sreenivasan

A method of modelling the three-dimensional microstructure of random isotropic two-phase materials is proposed. The information required to implement the technique can be obtained from two-dimensional images of the microstructure. The…

Disordered Systems and Neural Networks · Physics 2009-10-31 Anthony Roberts

In this paper, a new formalism for the filtered density function (FDF) approach is developed for the treatment of turbulent polydispersed two-phase flows in LES simulations. Contrary to the FDF used for turbulent reactive single-phase…

Fluid Dynamics · Physics 2012-02-07 Sergio Chibbaro , jean-Pierre Minier

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…

Optimization and Control · Mathematics 2019-08-08 Kenneth F. Caluya , Abhishek Halder