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The Riemannian geometry of covariance matrices has been essential to several successful applications, in computer vision, biomedical signal and image processing, and radar data processing. For these applications, an important ongoing…

Statistics Theory · Mathematics 2017-05-15 Salem Said , Hatem Hajri , Lionel Bombrun , Baba C. Vemuri

Bayesian estimation of Gaussian graphical models has proven to be challenging because the conjugate prior distribution on the Gaussian precision matrix, the G-Wishart distribution, has a doubly intractable partition function. Recent…

Neurons and Cognition · Quantitative Biology 2014-09-10 Max Hinne , Alex Lenkoski , Tom Heskes , Marcel van Gerven

The properties of the galaxy distribution at large scales are usually studied using statistics which are assumed to be self-averaging inside a given sample. We present a new analysis able to quantitatively map galaxy large scale structures…

This paper presents an analysis of properties of two hybrid discretization methods for Gaussian derivatives, based on convolutions with either the normalized sampled Gaussian kernel or the integrated Gaussian kernel followed by central…

Numerical Analysis · Mathematics 2025-01-31 Tony Lindeberg

Non-Gaussianities of dynamical origin are disentangled from primordial ones using the formalism of large deviation statistics with spherical collapse dynamics. This is achieved by relying on accurate analytical predictions for the one-point…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-27 Cora Uhlemann , Enrico Pajer , Christophe Pichon , Takahiro Nishimichi , Sandrine Codis , Francis Bernardeau

With the developments of large galaxy surveys or cosmic shear surveys it is now possible to map the dark matter distribution at truly cosmological scales. Detailed examinations of the statistical properties of the dark matter distribution…

Astrophysics · Physics 2007-05-23 Francis Bernardeau

This paper aims to study the configuration of two components caused by rotational and tidal distortions in the model of a binary system. The potentials of the two distorted components can be approximated to 2nd-degree harmonics.…

Solar and Stellar Astrophysics · Physics 2015-05-13 H. F. Song , Z. Zhong , Y. Lu

Random Matrix Theory is a powerful tool in applied mathematics. Three canonical models of random matrix distributions are the Gaussian Orthogonal, Unitary and Symplectic Ensembles. For matrix ensembles defined on k-fold tensor products of…

Mathematical Physics · Physics 2024-05-06 Michael Brodskiy , Owen L. Howell

We investigate statistical distributions of differences in gravitational-lensing deflections between two light rays, the so-called lensing excursion angles. A probability distribution function of the lensing excursion angles, which plays a…

Astrophysics · Physics 2009-11-10 Takashi Hamana , Matthias Bartelmann , Naoki Yoshida , Christoph Pfrommer

In this paper we extend the recent theory of shear-localization in 2-dimensional amorphous solids to 3-D. In 2-D the fundamental instability of shear-localization is related to the appearance of a line of displacement quadrupoles, that…

Soft Condensed Matter · Physics 2015-12-11 Ratul Dasgupta , Oleg Gendelman , Pankaj Mishra , Itamar Procaccia , Carmel A. B. Z. Shor

Large-scale structures, observed today, are generally believed to have grown from random, small-amplitude inhomogeneities, present in the early Universe. We investigate how gravitational instability drives the distribution of these…

Astrophysics · Physics 2009-10-22 R. Juszkiewicz , F. R. Bouchet , S. Colombi

We derive efficient recursive formulas giving the exact distribution of the largest eigenvalue for finite dimensional real Wishart matrices and for the Gaussian Orthogonal Ensemble (GOE). In comparing the exact distribution with the…

Information Theory · Computer Science 2014-10-21 Marco Chiani

This paper covers the material of our two talks. We describe a series of projects based upon perturbative expansions to follow the gravitational evolution of the one point probability distribution functions (PDFs) for the density contrast…

Astrophysics · Physics 2007-05-23 F. R. Bouchet , R. Juszkiewicz

Context: Two-point correlation functions are used throughout cosmology as a measure for the statistics of random fields. When used in Bayesian parameter estimation, their likelihood function is usually replaced by a Gaussian approximation.…

Cosmology and Nongalactic Astrophysics · Physics 2011-10-07 David Keitel , Peter Schneider

Stochastic separation theorems play important role in high-dimensional data analysis and machine learning. It turns out that in high dimension any point of a random set of points can be separated from other points by a hyperplane with high…

Probability · Mathematics 2020-12-02 Sergey Sidorov , Nikolai Zolotykh

Toroidal structures are a common feature in a wide variety of astrophysical objects, including dusty tori in AGNs, rings in galaxies, protoplanetary disks, and others. The matter distribution in such structures is not homogeneous and can be…

Astrophysics of Galaxies · Physics 2025-01-22 Elena Bannikova , Serhii Skolota , Massimo Capaccioli

A Lagrangian experimental study of an axisymmetric turbulent water jet is performed to investigate the highly anisotropic and inhomogeneous flow field. The measurements were conducted within a Lagrangian exploration module, an icosahedron…

In this paper, we investigate gravitational waves beyond the linear approximation, focusing on second-order contributions sourced by linearized waves in the transverse-traceless (TT) gauge. A general spacetime metric is constructed, and…

General Relativity and Quantum Cosmology · Physics 2025-05-06 M. A. Misyura

We summarise recent results for the chiral Random Two-Matrix Theory constructed to describe QCD in the epsilon-regime with imaginary chemical potential. The virtue of this theory is that unquenched Lattice simulations can be used to…

High Energy Physics - Theory · Physics 2008-11-26 G. Akemann

This paper first strictly proved that the growth of the second moment of a large class of Gaussian processes is not greater than power function and the covariance matrix is strictly positive definite. Under these two conditions, the maximum…

Statistics Theory · Mathematics 2022-07-21 Shifei Luo