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In this contribution we discuss the main outcomes of our studies on the so called double parton distribution functions (dPDFs), accessible quantities in high energy proton-proton and proton nucleus collisions, in double parton scattering…

High Energy Physics - Phenomenology · Physics 2020-01-08 Matteo Rinaldi

A method to approximate continuous multi-dimensional probability density functions (PDFs) using their projections and correlations is described. The method is particularly useful for event classification when estimates of systematic…

Data Analysis, Statistics and Probability · Physics 2009-10-31 Dean Karlen

Many disordered crystalline materials show chemical short range order and relaxation of neighboring atoms. Local structural information can be obtained by analyzing the atomic pair distribution function (PDF). The viability of reverse Monte…

Materials Science · Physics 2007-05-23 Th. Proffen

By means of the multifractal analysis (MFA), the expressions of the probability density functions (PDFs) are unified in a compact analytical formula which is valid for various quantities in turbulence. It is shown that the formula can…

Statistical Mechanics · Physics 2009-11-10 Toshihico Arimitsu , Naoko Arimitsu

A new and simple statistical approach is performed to calculate the parton distribution functions (PDFs) of the nucleon in terms of light-front kinematic variables. We do not put in any extra arbitrary parameter or corrected term by hand,…

High Energy Physics - Phenomenology · Physics 2009-03-12 Yunhua Zhang , Lijing Shao , Bo-Qiang Ma

We present a new software package designed to reduce the computational burden of hadron collider measurements in Parton Distribution Function (PDF) fits. The APFELgrid package converts interpolated weight tables provided by APPLgrid files…

High Energy Physics - Phenomenology · Physics 2017-01-04 Valerio Bertone , Stefano Carrazza , Nathan P. Hartland

We present a new regression model for the determination of parton distribution functions (PDF) using techniques inspired from deep learning projects. In the context of the NNPDF methodology, we implement a new efficient computing framework…

High Energy Physics - Phenomenology · Physics 2019-09-04 Stefano Carrazza , Juan Cruz-Martinez

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

Molecular dynamics (MD) simulations play a crucial role in resolving the underlying conformational dynamics of molecular systems. However, their capability to correctly reproduce and predict dynamics in agreement with experiments is limited…

Chemical Physics · Physics 2025-05-19 Ivan Gilardoni , Valerio Piomponi , Thorben Fröhlking , Giovanni Bussi

In this paper we demonstrate that multi-modal Probability Distribution Functions (PDFs) may be efficiently sampled using an algorithm originally developed for numerical integrations by Monte-Carlo methods. This algorithm can be used to…

Computational Physics · Physics 2009-10-31 K. J. Abraham , L. M. Haines

The xFitter project (former HERAFitter project) is an open-source package that provides a framework for the determination of the parton distribution functions (PDFs) of the proton for many different kinds of analyses in Quantum…

High Energy Physics - Phenomenology · Physics 2017-09-06 Francesco Giuli

This paper investigates probability density functions (PDFs) that are continuous everywhere, nearly uniform around the mode of distribution, and adaptable to a variety of distribution shapes ranging from bell-shaped to rectangular. From the…

Machine Learning · Computer Science 2022-04-01 Osamu Fujita

Due to the popularity of portable document format (PDF) and increasing number of vulnerabilities in major PDF viewer applications, malware writers continue to use it to deliver malware via web downloads, email attachments and other methods…

Cryptography and Security · Computer Science 2018-08-22 Jason Zhang

We present new sets of nuclear parton distribution functions (nPDFs) at next-to-leading order (NLO) and next-to-next-to-leading order (NNLO). Our analyses are based on deeply inelastic scattering data with charged-lepton and neutrino beams…

High Energy Physics - Phenomenology · Physics 2019-12-17 Marina Walt , Ilkka Helenius , Werner Vogelsang

We present the first NNPDF full set of Parton Distribution Functions from a comprehensive DIS analysis. This approach, combining a Monte Carlo sampling of the probability measure in the space of PDFs with the use of neural networks as…

High Energy Physics - Phenomenology · Physics 2009-11-13 Maria Ubiali

The goal of this study is to determine a set of diffractive parton distribution function (diffractive PDFs) from a QCD analysis of all available and up-to-date diffractive deep inelastic scattering (diffractive DIS) data sets from HERA $ep$…

High Energy Physics - Phenomenology · Physics 2019-04-02 Hamzeh Khanpour

We present NeoPDF, an interpolation library that supports both collinear and transverse momentum-dependent parton distribution functions. NeoPDF is designed to be fast and reliable, with modern functionalities that target both current and…

High Energy Physics - Phenomenology · Physics 2025-10-07 Tanjona R. Rabemananjara

Double parton distribution functions (dPDFs), entering the double parton scattering (DPS) cross section, are unknown fundamental quantities encoding new interesting properties of hadrons. Here, the pion dPDFs are investigated within…

High Energy Physics - Phenomenology · Physics 2020-08-26 Matteo Rinaldi

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

We validate the use of matrix factorization for the automatic identification of relevant components from atomic pair distribution function (PDF) data. We also present a newly developed software infrastructure for analyzing the PDF data…