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The formula for probability density functions (PDFs) has been extended to include PDF for energy dissipation rates in addition to other PDFs such as for velocity fluctuations, velocity derivatives, fluid particle accelerations, energy…

Statistical Mechanics · Physics 2009-11-11 T. Arimitsu , N. Arimitsu

Eigenvalue correlations of random matrix ensembles as a function of an external perturbation are investigated vis the Dyson Brownian Motion Model in the situation where the level density has a hard edge singularity. By solving a linearized…

Condensed Matter · Physics 2009-10-22 Kasper Eriksen , Yang Chen

It is well known that the joint probability density of the eigenvalues of Gaussian ensembles of random matrices may be interpreted as a Coulomb gas. We review these classical results for hermitian and complex random matrices, with special…

Statistical Mechanics · Physics 2007-05-23 P. Leboeuf

We introduce a new functional representation of probability density functions (PDFs) of non-negative random variables via a product of a monomial factor and linear combinations of decaying exponentials with complex exponents. This…

Probability · Mathematics 2018-02-13 Gregory Beylkin , Lucas Monzon , Ignas Satkauskas

Counting experiments often rely on Monte Carlo simulations for predictions of Poisson expectations. The accompanying uncertainty from the finite Monte Carlo sample size can be incorporated into parameter estimation by modifying the Poisson…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 Thorsten Glüsenkamp

There are several methods to treat ensembles of random matrices in symmetric spaces, circular matrices, chiral matrices and others. Orthogonal polynomials and the supersymmetry method are particular powerful techniques. Here, we present a…

Mathematical Physics · Physics 2014-11-20 Mario Kieburg , Thomas Guhr

The estimation of probability density functions (PDF) using approximate maps is a fundamental building block in computational probability. We consider forward problems in uncertainty quantification: the inputs or the parameters of a…

Numerical Analysis · Mathematics 2022-03-28 Amir Sagiv

The evolution of both quantum and classical ensembles may be described via the probability density P on configuration space, its canonical conjugate S, and an_ensemble_ Hamiltonian H[P,S]. For quantum ensembles this evolution is, of course,…

Quantum Physics · Physics 2009-11-10 Michael J. W. Hall

At large quantum numbers, the probability densities for particle-in-a-box or simple harmonic oscillator converge to the classical result upon coarse-graining the quantum mechanical probability densities by introducing a finite resolution in…

Quantum Physics · Physics 2024-11-05 Raghunathan Ramakrishnan

We propose a probabilistic semantic filtering framework in which parameters of a dynamical system are inferred and associated with a closed set of semantic classes in a map. We extend existing methods to a multi-parameter setting using a…

Systems and Control · Electrical Eng. & Systems 2026-01-15 Marcus Greiff , Ray Zhang , Thomas Lew , John Subosits

Classical binomial identities are established by giving probabilistic interpretations to the summands. The examples include Vandermonde identity and some generalizations.

Combinatorics · Mathematics 2011-11-17 Christophe Vignat , Victor H. Moll

We present a general method for the reconstruction of the one-point Probability Distribution Function of the local aperture mass in weak lensing maps. Exact results, that neglect the lens-lens coupling and departure form the Born…

Astrophysics · Physics 2007-05-23 F. Bernardeau , P. Valageas

We investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established "MSTW 2008" global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the…

High Energy Physics - Phenomenology · Physics 2012-08-13 G. Watt , R. S. Thorne

We present an investigation of the theoretical uncertainties in parton distribution functions (PDFs) due to missing higher-order corrections in the perturbative predictions used in the fit, and their relationship to the uncertainties in…

High Energy Physics - Phenomenology · Physics 2019-05-02 L. A. Harland-Lang , R. S. Thorne

A simple position probability density formulation is presented for the motion of a particle in a spherically symmetric potential. The approach provides an alternative to Newtonian methods for presentation in an elementary course, and…

Physics Education · Physics 2007-05-23 Lorenzo J. Curtis , David G. Ellis

We present the MCscales approach for incorporating scale uncertainties in parton distribution functions (PDFs). The new methodology builds on the Monte Carlo sampling for propagating experimental uncertainties into the PDF space that…

High Energy Physics - Phenomenology · Physics 2023-03-27 Zahari Kassabov , Maria Ubiali , Cameron Voisey

Duality identities in random matrix theory for products and powers of characteristic polynomials, and for moments, are reviewed. The structure of a typical duality identity for the average of a positive integer power $k$ of the…

Mathematical Physics · Physics 2025-01-14 Peter J. Forrester

According to the classification scheme of the generalized random matrix ensembles, we present various kinds of concrete examples of the generalized ensemble, and derive their joint density functions in an unified way by one simple formula…

Mathematical Physics · Physics 2007-05-23 Jinpeng An , Zhengdong Wang , Kuihua Yan

We present a discussion on the methods for extracting a given parameter from measurements of hadronic data, with particular focus on determinations of the strong coupling constant. We show that when the PDF dependency on the determination…

High Energy Physics - Phenomenology · Physics 2018-02-15 Zahari Kassabov

We consider the distribution of the sum and the maximum of a collection of independent exponentially distributed random variables. The focus is laid on the explicit form of the density functions (pdf) of non-i.i.d. sequences. Those are…

Probability · Mathematics 2013-07-16 Markus Bibinger