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In this talk we present the results of the investigation on the so called double parton distribution functions (dPDFs), accessible quantities in high energy proton-proton and proton nucleus collisions, in double parton scattering processes…

High Energy Physics - Phenomenology · Physics 2021-02-03 Matteo Rinaldi

We present preliminary results on the determination of spin-dependent, or polarised, Parton Distribution Functions (PDFs) from all relevant inclusive polarised DIS data. The analysis is performed within the NNPDF approach, which provides a…

High Energy Physics - Phenomenology · Physics 2012-06-26 Emanuele R. Nocera , Stefano Forte , Giovanni Ridolfi , Juan Rojo

Since the first determination of a structure function many decades ago, all methodologies used to determine structure functions or parton distribution functions (PDFs) have employed a common prefactor as part of the parametrization. The…

High Energy Physics - Phenomenology · Physics 2022-03-09 Stefano Carrazza , Juan M. Cruz-Martinez , Roy Stegeman

A thorough understanding of the issues surrounding the determination of parton distributions is crucial due to their importance to calculations of LHC observables. However, it is still not fully understood how much of an impact…

High Energy Physics - Phenomenology · Physics 2014-09-16 Christopher S. Deans

We consider the generic problem of performing a global fit to many independent data sets each with a different overall multiplicative normalization uncertainty. We show that the methods in common use to treat multiplicative uncertainties…

High Energy Physics - Phenomenology · Physics 2010-06-02 The NNPDF Collaboration , Richard D. Ball , Luigi Del Debbio , Stefano Forte , Alberto Guffanti , Jose I. Latorre , Juan Rojo , Maria Ubiali

A Python package for the analysis of dark-field X-ray microscopy (DFXM) and rocking curve imaging (RCI) data is presented. \textit{darfix} provides a set of data processing and visualization tools that can be either imported as library…

We extract two nonsinglet nucleon Parton Distribution Functions from lattice QCD data for reduced Ioffe-time pseudodistributions. We perform such analysis within the NNPDF framework, considering data coming from different lattice ensembles…

High Energy Physics - Phenomenology · Physics 2021-03-17 Luigi Del Debbio , Tommaso Giani , Joseph Karpie , Kostas Orginos , Anatoly Radyushkin , Savvas Zafeiropoulos

The framework of multifractal analysis (MFA) is distilled to the most sophisticated one. Within this transparent framework, it is shown that the harmonious representation of MFA utilizing two distinct Tsallis distribution functions, one for…

Statistical Mechanics · Physics 2009-11-10 T. Arimitsu , N. Arimitsu

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

Parton distribution functions play a pivotal role in hadron collider phenomenology. They are non-perturbative quantities extracted from fits to available data, and their scale dependence is dictated by the DGLAP evolution equations. In this…

High Energy Physics - Phenomenology · Physics 2024-08-08 Salvador A. Ochoa-Oregon , David F. Rentería-Estrada , Roger J. Hernández-Pinto , German F. R. Sborlini , Pia Zurita

A Materials Project based open-source Python tool, MPInterfaces, has been developed to automate the high-throughput computational screening and study of interfacial systems. The framework encompasses creation and manipulation of interface…

SfePy (Simple finite elements in Python) is a software for solving various kinds of problems described by partial differential equations in one, two or three spatial dimensions by the finite element method. Its source code is mostly (85\%)…

Mathematical Software · Computer Science 2019-08-20 Robert Cimrman , Vladimír Lukeš , Eduard Rohan

We discuss the determination of the parton substructure of hadrons by casting it as a peculiar form of pattern recognition problem in which the pattern is a probability distribution, and we present the way this problem has been tackled and…

High Energy Physics - Phenomenology · Physics 2020-08-31 Stefano Forte , Stefano Carrazza

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

The interest into parton distribution functions (PDFs) and fragmentation functions (FFs) in current high energy physics research is twofold. On the one hand, they are fundamental objects to conduct precision phenomenology studies, e.g. at…

High Energy Physics - Phenomenology · Physics 2025-09-22 Tanishq Sharma

Parton distribution functions (PDFs) describe universal properties of bound states and allow us to calculate scattering amplitudes in processes with large momentum transfer. Calculating PDFs involves the evaluation of matrix elements with a…

High Energy Physics - Lattice · Physics 2025-02-10 Mari Carmen Bañuls , Krzysztof Cichy , C. -J. David Lin , Manuel Schneider

I review recent progress in the NNPDF global analyses of parton distributions (PDFs) focusing on developments contributing to its new upcoming release: NNPDF4.0. The NNPDF4.0 determination represents unprecedented progress in three main…

High Energy Physics - Phenomenology · Physics 2021-04-20 Juan Rojo

The determination of the parton distribution functions (PDFs) is crucial for a complete understanding of the protons and neutrons that make most of the visible matter in the universe. Years of dedicated studies have yielded a quite precise…

High Energy Physics - Phenomenology · Physics 2018-10-02 Pia Zurita

This paper introduces $\textit{arfpy}$, a python implementation of Adversarial Random Forests (ARF) (Watson et al., 2023), which is a lightweight procedure for synthesizing new data that resembles some given data. The software…

Machine Learning · Statistics 2023-11-14 Kristin Blesch , Marvin N. Wright

MPC (Magneto-Photonic Crystal) Optimisation is a feature-rich Windows software application designed to enable researchers to analyze the optical and magneto-optical spectral properties of multilayers containing gyrotropic constituents. A…

Applied Physics · Physics 2019-05-03 M. Vasiliev , K. Alameh , M. Nur-E-Alam