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The probability density function (PDF) of some global average quantity plays a fundamental role in critical and highly correlated systems. We explicitly compute this quantity as a function of the magnetization for the two dimensional XY…

High Energy Physics - Lattice · Physics 2009-12-03 G. Palma , D. Zambrano

We study the dependence of the transverse mass distribution of the charged lepton and the missing energies on the parton distributions (PDFs) adapted to the $W$ boson mass measurements at the CDF and ATLAS experiments. We compare the shape…

High Energy Physics - Phenomenology · Physics 2022-05-10 Jun Gao , DianYu Liu , Keping Xie

A method providing optimal estimate of probability density functions (PDFs) from time series is proposed. It allows almost arbitrary resolution PDFs when applied to either, sampled analytic functions or digitized data from experiments. When…

Data Analysis, Statistics and Probability · Physics 2007-05-30 R. Labbé

In non-linear scales, the matter density distribution is not Gaussian. Consequently, the widely used two-point correlation function is not adequate anymore to capture the matter density field's entire behaviour. Among all statistics beyond…

Cosmology and Nongalactic Astrophysics · Physics 2022-04-20 Mohammad Ansari Fard , Zahra Baghkhani , Laya Ghodsi , Sina Taamoli , Farbod Hassani , Shant Baghram

Density estimation plays a crucial role in many data analysis tasks, as it infers a continuous probability density function (PDF) from discrete samples. Thus, it is used in tasks as diverse as analyzing population data, spatial locations in…

Machine Learning · Computer Science 2021-07-26 Patrik Puchert , Pedro Hermosilla , Tobias Ritschel , Timo Ropinski

It has been shown that the large--scale correlation functions of the density field (and velocity divergence field) follow a specific hierarchy in the quasilinear regime and for Gaussian initial conditions (Bernardeau 1992). The exact…

Astrophysics · Physics 2007-05-23 F. Bernardeau

Machine learning models based on convolutional neural networks have been used for predicting space groups of crystal structures from their atomic pair distribution function (PDF). However, the PDFs used to train the model are calculated…

Materials Science · Physics 2022-06-20 Ling Lan , Chia-Hao Liu , Qiang Du , Simon J. L. Billinge

Extending previous studies, we derive generic predictions for lower order cumulants and their correlators for individual tomographic bins as well as between two different bins. We derive the corresponding one- and two-point joint…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Dipak Munshi , Peter Coles , Martin Kilbinger

We study the motion of a Brownian particle in a medium with inhomogeneous temperature. In the overdamped regime of low Reynolds numbers, the probability distribution function (PDF) of the particle is obtained from the van Kampen diffusion…

Statistical Mechanics · Physics 2019-06-06 Oded Farago

We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS…

We consider systems of particles hopping stochastically on $d$-dimensional lattices with space-dependent probabilities. We map the master equation onto an evolution equation in a Fock space where the dynamics are given by a quantum…

Condensed Matter · Physics 2007-05-23 Gunter Schuetz , Sven Sandow

We obtain an exact result for the midpoint probability distribution function (pdf) of the stationary continuum directed polymer, when averaged over the disorder. It is obtained by relating that pdf to the linear response of the stochastic…

Disordered Systems and Neural Networks · Physics 2017-10-09 Christian Maes , Thimothée Thiery

We propose a new, physically motivated fitting function for density PDFs in turbulent gas. Although it is known that when gas is isothermal, the PDF is approximately lognormal in the core, high-resolution simulations show large deviations…

Astrophysics of Galaxies · Physics 2013-07-02 Philip F. Hopkins

We study the spatial distribution of dark matter halos in the Universe in terms of their number density contrast, related to the underlying dark matter fluctuation via a non-local and non-linear bias random field. The description of the…

Astrophysics · Physics 2009-10-30 Paolo Catelan , Sabino Matarrese , Cristiano Porciani

Sampling-based motion planning algorithms are widely used in robotics because they are very effective in high-dimensional spaces. However, the success rate and quality of the solutions are determined by an adequate selection of their…

We derive relations between transverse momentum dependent distribution functions (TMDs) and the usual parton distribution functions (PDFs) in the 3D covariant parton model, which follow from Lorentz invariance and the assumption of a…

High Energy Physics - Phenomenology · Physics 2011-05-10 A. V. Efremov , P. Schweitzer , O. V. Teryaev , P. Zavada

Position probability distribution of a set of massive mutually exclusive particles in one dimension has been defined. Examples with a given two mutually exclusive particles system are considered. It is emphasized that quantum particles at…

Quantum Physics · Physics 2016-10-28 Rasool Kheiry , Shahram Salehi

The purpose of this study is to describe a perfect fluid matter distribution that leads to a constant curvature region, thanks to the effect of a non-minimal coupling. This distribution exhibits a density profile within the range found in…

General Relativity and Quantum Cosmology · Physics 2011-07-04 J. Páramos , O. Bertolami

We provide a set of general tools for studying the alignments of dark matter halos and galaxies with respect to the large scale structure. The statistics of the positioning of these objects is represented by a Probability Distribution…

Cosmology and Nongalactic Astrophysics · Physics 2009-12-08 Juan E. Betancort-Rijo , Ignacio Trujillo

We examine the dependence of parton distribution functions (PDFs) on the value of the QCD coupling strength $\alpha_{s}(M_{Z})$. We explain a simple method that is rigorously valid in the quadratic approximation normally applied in PDF…

High Energy Physics - Phenomenology · Physics 2014-11-20 Hung-Liang Lai , Joey Huston , Zhao Li , Pavel Nadolsky , Jon Pumplin , Daniel Stump , C. -P. Yuan