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Max stable laws are limit laws of linearly normalized partial maxima of indepen- dent, identically distributed (iid) random variables (rvs). These are analogous to stable laws which are limit laws of normalized partial sums of iid rvs. In…

Statistics Theory · Mathematics 2016-11-25 Sreenivasan Ravi , Ali Saeb

Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distribution estimation. This problem can be ill-posed, however, since…

Machine Learning · Computer Science 2024-12-02 Julius Vetter , Guy Moss , Cornelius Schröder , Richard Gao , Jakob H. Macke

We have set ourselves the task of obtaining the probability distribution function of the mass density of a self-gravitating isothermal compressible turbulent fluid from its physics. We have done this in the context of a new notion: the…

Astrophysics of Galaxies · Physics 2018-01-10 Sava Donkov , Ivan Stefanov

The halo-mediated inverse mass cascade is a key feature of the intermediate statistically steady state for self-gravitating collisionless dark matter flow (SG-CFD). A broad spectrum of halos and halo groups are necessary to form from…

Cosmology and Nongalactic Astrophysics · Physics 2022-07-12 Zhijie Xu

We consider a generic system composed of a fixed number of particles distributed over a finite number of energy levels. We make only general assumptions about system's properties and the entropy. System's constraints other than fixed number…

Probability · Mathematics 2020-03-12 Tomasz M. Łapiński

Prompted by the realisation that the statistical entropy of an ideal gas in the micro-canonical ensemble should not fluctuate or change over time, the meaning of the H-theorem is re-interpreted from the perspective of information theory in…

General Physics · Physics 2013-01-09 David Sands , Jeremy Dunning-Davies

We derive the expression of the reference distribution function for magnetically confined plasmas far from the thermodynamic equilibrium. The local equilibrium state is fixed by imposing the minimum entropy production theorem and the…

Generating samples from limited information is a fundamental problem across scientific domains. Classical maximum entropy methods provide principled uncertainty quantification from moment constraints but require sampling via MCMC or…

This brief note aims to introduce the recent paradigm of distributional robustness in the field of shape and topology optimization. Acknowledging that the probability law of uncertain physical data is rarely known beyond a rough…

Optimization and Control · Mathematics 2023-01-13 Charles Dapogny , Franck Iutzeler , Andrea Meda , Boris Thibert

A theory to predict the steady state position of a dissipative, flow-controlled system, as defined by a control volume, is developed based on the Maximum Entropy (MaxEnt) principle of Jaynes, involving minimisation of a generalised free…

Classical Physics · Physics 2015-05-13 Robert K. Niven

A fluid system is derived to describe electrostatic magnetized plasma turbulence at scales somewhat larger than the Larmor radius of a given species. It is related to the Hasegawa- Mima equation, but does not conserve enstrophy, and, as a…

Plasma Physics · Physics 2020-09-09 G. G. Plunk

A cascade model is described based on multiplier distributions determined from 3D direct numerical simulations (DNS) of turbulent particle laden flows, which include two-way coupling between the phases at global mass loadings equal to…

Astrophysics · Physics 2015-06-30 Robert C. Hogan , Jeffrey N. Cuzzi

Traditionally, the Method of (Shannon-Kullback's) Relative Entropy Maximization (REM) is considered with linear moment constraints. In this work, the method is studied under frequency moment constraints which are non-linear in…

Data Analysis, Statistics and Probability · Physics 2012-08-27 M. Grendar, , M. Grendar

On a compact group the Haar probability measure plays the role of uniform distribution. The entropy and rate distortion theory for this uniform distribution is studied. New results and simplified proofs on convergence of convolutions on…

Information Theory · Computer Science 2010-05-27 Peter Harremoes

A well-known result across information theory, machine learning, and statistical physics shows that the maximum entropy distribution under a mean constraint has an exponential form called the Gibbs-Boltzmann distribution. This is used for…

Machine Learning · Computer Science 2020-06-26 Amir R. Asadi , Emmanuel Abbe

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…

Astrophysics of Galaxies · Physics 2015-06-18 Joerg Fischera

We present a maximum entropy approach to analyze the internal dynamics of a small system in contact with a large bath e.g. a solute-solvent system. For the small solute, the fluctuations around the mean values of observables are not…

Statistical Mechanics · Physics 2015-06-11 Purushottam D. Dixit

In this work, we consider a recently proposed entropy S (called varentropy) defined by a variational relationship dI=beta*(d<x>-<dx>) as a measure of uncertainty of random variable x. By definition, varentropy underlies a generalized…

Statistical Mechanics · Physics 2020-10-28 C. J. Ou , A. El Kaabouchi , L. Nivanen , F. Tsobnang , A. Le Méhauté , Qiuping A. Wang

In this article, we proposed a new probability distribution named as power Maxwell distribution (PMaD). It is another extension of Maxwell distribution (MaD) which would lead more flexibility to analyze the data with non-monotone failure…

Applications · Statistics 2018-07-04 Abhimanyu Singh Yadav , Hassan S. Bakouch , Sanjay Kumar Singh , Umesh Singh

We suggest a new model for the structure of a magnetic field embedded high $\beta$ turbulent plasma, based on the popular notion that the magnetic field will tend to separate into individual flux tubes. We point out that interactions…

Astrophysics · Physics 2007-05-23 E. T. Vishniac