English
Related papers

Related papers: Deviations from normal distributions in artificial…

200 papers

The need to analyze the available large synoptic multi-band surveys drives the development of new data-analysis methods. Photometric redshift estimation is one field of application where such new methods improved the results, substantially.…

Instrumentation and Methods for Astrophysics · Physics 2018-01-31 Antonio D'Isanto , Kai Lars Polsterer

The 1-point matter density probability distribution function (PDF) captures some of the non-Gaussian information lost in standard 2-point statistics. The matter PDF can be well predicted at mildly non-linear scales using large deviations…

Cosmology and Nongalactic Astrophysics · Physics 2025-09-16 Beth McCarthy Gould , Lina Castiblanco , Cora Uhlemann , Oliver Friedrich

In this paper, the classical problem of the probabilistic characterization of a random variable is re-examined. A random variable is usually described by the probability density function (PDF) or by its Fourier transform, namely the…

Mathematical Physics · Physics 2013-01-22 Giulio Cottone , Mario Di Paola

We study the probability distribution function (PDF) of the mass density in simulations of supersonic turbulence with properties appropriate for molecular clouds. For this study we use Athena, a new higher-order Godunov code. We find there…

Astrophysics · Physics 2008-09-23 M. Nicole Lemaster , James M. Stone

The Ly$\alpha$ forest transmission probability distribution function (PDF) is an established probe of the intergalactic medium (IGM) astrophysics, especially the temperature-density relationship of the IGM. We measure the transmission PDF…

We discuss a Bayesian methodology for the solution of the inverse problem underlying the determination of parton distribution functions (PDFs). In our approach, Gaussian Processes (GPs) are used to model the PDF prior, while Bayes theorem…

High Energy Physics - Phenomenology · Physics 2024-07-03 Alessandro Candido , Luigi Del Debbio , Tommaso Giani , Giacomo Petrillo

We analytically calculate the star formation efficiency and dense self-gravitating gas fraction in the presence of magneto-gravo-turbulence using the model of Burkhart (2018), which employs a piecewise lognormal and powerlaw density…

Astrophysics of Galaxies · Physics 2019-07-24 Blakesley Burkhart , Philip Mocz

In this work, we study non-parametric estimation of joint probabilities of a given set of discrete and continuous random variables from their (empirically estimated) 2D marginals, under the assumption that the joint probability could be…

Machine Learning · Computer Science 2022-03-04 Shaan ul Haque , Ajit Rajwade , Karthik S. Gurumoorthy

We discuss the non-self-averaging phenomena in the critical point of weakly disordered Ising ferromagnet. In terms of the renormalized replica Ginzburg-Landau Hamiltonian in dimensions D <4, we derive an explicit expression for the…

Statistical Mechanics · Physics 2016-01-26 Victor Dotsenko , Yu. Holovatch

Probabilistic time series forecasting involves estimating the distribution of future based on its history, which is essential for risk management in downstream decision-making. We propose a deep state space model for probabilistic time…

Machine Learning · Computer Science 2021-02-02 Longyuan Li , Junchi Yan , Xiaokang Yang , Yaohui Jin

Bayesian estimation strategies represent the most fundamental formulation of the state estimation problem available, and apply readily to nonlinear systems with non-Gaussian uncertainties. The present paper introduces a novel method for…

Optimization and Control · Mathematics 2013-01-22 T R Bewley , A S Sharma

The article derives some novel independence measures and contrast functions for Blind Source Separation (BSS) application. For the $k^{th}$ order differentiable multivariate functions with equal hyper-volumes (region bounded by…

Machine Learning · Computer Science 2015-04-13 Dharmani Bhaveshkumar C

The probability density function (PDF) of velocity fluctuations is studied experimentally for grid turbulence in a systematical manner. At small distances from the grid, where the turbulence is still developing, the PDF is sub-Gaussian. At…

Fluid Dynamics · Physics 2009-11-07 H. Mouri , M. Takaoka , A. Hori , Y. Kawashima

A sample of eight quasars observed at high resolution and signal-to-noise is used to determine the probability distribution function (PDF), the power spectrum, and the correlation function of the transmitted flux in the \lya forest, in…

In this Letter we investigate the shape of the probability distribution of column densities (PDF) in molecular clouds. Through the use of low-noise, extinction-calibrated \textit{Herschel}/\textit{Planck} emission data for eight molecular…

Solar and Stellar Astrophysics · Physics 2015-06-23 Marco Lombardi , João Alves , Charles J. Lada

The probability distribution functions (PDFs) for atomic, molecular, and total gas surface densities of M33 are determined at a resolution of about 50~pc over regions that share coherent morphological properties to unveil fingerprints of…

Astrophysics of Galaxies · Physics 2018-10-03 Edvige Corbelli , Bruce G. Elmegreen , Jonathan Braine , David Thilker

A practical computational scheme based on time-dependent density functional theory (TDDFT) and ultrasoft pseudopotential (USPP) is developed to study electron dynamics in real time. A modified Crank-Nicolson time-stepping algorithm is…

Materials Science · Physics 2007-05-23 Xiaofeng Qian , Ju Li , Xi Lin , Sidney Yip

Plasma density fluctuations in the edge plasma of the RFX-mod device are measured through the Gas Puffing Imaging Diagnostics. Statistical features of the signal are quantified in terms of the Probability Distribution Function (PDF), and…

Plasma Physics · Physics 2007-05-23 F. Sattin , P. Scarin , M. Agostini , R. Cavazzana , G. Serianni , M. Spolaore , N. Vianello

A probabilistic circuit (PC) succinctly expresses a function that represents a multivariate probability distribution and, given sufficient structural properties of the circuit, supports efficient probabilistic inference. Typically a PC…

Machine Learning · Computer Science 2024-08-09 Oliver Broadrick , William Cao , Benjie Wang , Martin Trapp , Guy Van den Broeck

With the growth of large photometric surveys, accurately estimating photometric redshifts, preferably as a probability density function (PDF), and fully understanding the implicit systematic uncertainties in this process has become…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-15 M. Carrasco Kind , R. J. Brunner
‹ Prev 1 3 4 5 6 7 10 Next ›