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The probability density function (PDF) associated with a given set of samples is approximated by a piecewise-linear polynomial constructed with respect to a binning of the sample space. The kernel functions are a compactly supported basis…

Numerical Analysis · Mathematics 2020-08-04 Giacomo Capodaglio , Max Gunzburger

Pinning down the total neutrino mass and the dark energy equation of state is a key aim for upcoming galaxy surveys. Weak lensing is a unique probe of the total matter distribution whose non-Gaussian statistics can be quantified by the…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-08 Aoife Boyle , Cora Uhlemann , Oliver Friedrich , Alexandre Barthelemy , Sandrine Codis , Francis Bernardeau , Carlo Giocoli , Marco Baldi

The evolution of probability distribution functions (PDFs) of continuous density, velocity and velocity derivatives ( deformation tensor) fields in the theory of cosmological gravitational instability are considered. We show that in the…

Astrophysics · Physics 2007-05-23 Lev Kofman

This paper tackles the issue of real-time parametric estimation of a wide class of probability density functions from limited datasets. This type of estimation addresses recent applications that require joint sensing and actuation. The…

Information Theory · Computer Science 2022-03-21 Ahmad A. Masoud

Through viewing out the literature, many generated distributions took a new special form of probability density function (PDF) in which it is written as a linear combination of n other distributions. Therefore, we define in this paper a new…

Statistics Theory · Mathematics 2022-11-15 Therar Kadri , Amina Halat

We introduce a new technique based on artificial neural networks which allows us to make accurate predictions for the spectral energy distributions (SEDs) of large samples of galaxies, at wavelengths ranging from the far-ultra-violet to the…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 C. Almeida , C. M. Baugh , C. G. Lacey , C. S. Frenk , G. L. Granato , L. Silva , A. Bressan

We employ the LuxQED approach to compute the polarized photon PDF (photon pPDF). This approach expresses the pPDF in terms of the structure functions $g_1$ and $g_2$. Different models for the structure functions are employed according to…

High Energy Physics - Phenomenology · Physics 2024-10-30 Daniel de Florian , Lucas Palma Conte , Gabriel Fernando Volonnino

We apply the Distillation spatial smearing program to the extraction of the unpolarized isovector valence PDF of the nucleon. The improved volume sampling and control of excited-states afforded by distillation leads to a dramatically…

We study the one-point probability distribution function (PDF) for matter density averaged over spherical cells. The leading part to the PDF is defined by spherical collapse dynamics, whereas the next-to-leading part comes from the…

Cosmology and Nongalactic Astrophysics · Physics 2023-08-08 Anton Chudaykin , Mikhail M. Ivanov , Sergey Sibiryakov

We use a suite of 3D simulations of star-forming molecular clouds, with and without stellar feedback and magnetic fields, to investigate the effectiveness of different fitting methods for volume and column density probability distribution…

Astrophysics of Galaxies · Physics 2023-05-22 Avery Kiihne , Sabrina M. Appel , Blakesley Burkhart , Vadim A. Semenov , Christoph Federrath

Recent innovations in diffusion probabilistic models have paved the way for significant progress in image, text and audio generation, leading to their applications in generative time series forecasting. However, leveraging such abilities to…

Machine Learning · Computer Science 2025-11-07 Yuansan Liu , Sudanthi Wijewickrema , Dongting Hu , Christofer Bester , Stephen O'Leary , James Bailey

Probability Distributions Functions (PDFs) of fluctuations of plasma edge parameters are skewed curves fairly different from normal distributions, whose shape appears almost independent of the plasma conditions and devices. We start from a…

Plasma Physics · Physics 2009-04-23 F. Sattin

The projected normal distribution, also known as the angular Gaussian distribution, is obtained by dividing a multivariate normal random variable $\mathbf{x}$ by its norm $\sqrt{\mathbf{x}^T \mathbf{x}}$. The resulting random variable…

Methodology · Statistics 2025-06-24 Daniel Herrera-Esposito , Johannes Burge

We present a measurement of the Lyman alpha flux probability distribution function (PDF) measured from a set of eight high resolution quasar spectra with emission redshifts at 3.3 < z < 3.8. We carefully study the effect of metal absorption…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 F. Calura , E. Tescari , V. D'Odorico , M. Viel , S. Cristiani , T. -S. Kim , J. S. Bolton

The amount, size, and complexity of astronomical data-sets and databases are growing rapidly in the last decades, due to new technologies and dedicated survey telescopes. Besides dealing with poly-structured and complex data, sparse data…

Instrumentation and Methods for Astrophysics · Physics 2021-03-08 Kai Lars Polsterer , Antonio D'Isanto , Sebastian Lerch

Stochastic resetting can be naturally understood as a renewal process governing the evolution of an underlying stochastic process. In this work, we formally derive well-known results of diffusion with resets from a renewal theory…

Statistical Mechanics · Physics 2022-10-05 Axel Masó-Puigdellosas , Daniel Campos , Vicenç Méndez

The diffusion of colloids inside an active system-e.g. within a living cell or the dynamics of active particles itself (e.g. self-propelled particles) can be modeled through overdamped Langevin equation which contains an additional noise…

Statistical Mechanics · Physics 2024-12-06 Koushik Goswami , K. L. Sebastian

One of the most puzzling properties of observed galaxies is the universality of the empirical correlation between the star formation rate and average gas surface density on kiloparsec scales (the Schmidt law). In this study I present…

Astrophysics · Physics 2011-05-12 Andrey V. Kravtsov

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

We utilize the probability distribution function (PDF) of normalized convergence maps reconstructed from the Subaru Hyper Suprime-Cam (HSC) Y1 shear catalogue, in combination with the power spectrum, to measure the matter clustering…

Cosmology and Nongalactic Astrophysics · Physics 2023-11-23 Leander Thiele , Gabriela A. Marques , Jia Liu , Masato Shirasaki