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The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description…

High Energy Physics - Phenomenology · Physics 2015-12-09 Claude Bourrely , Jacques Soffer

We present an alternative algorithm to global fitting procedures to construct Parton Distribution Functions (PDFs) parametrizations. The proposed algorithm uses Self-Organizing Maps (SOMs) which at variance with the standard Neural…

High Energy Physics - Phenomenology · Physics 2017-08-23 H. Honkanen , S. Liuti , Y. C. Loitiere , D. Brogan , P. Reynolds

The Nested Dirichlet Distribution (NDD) provides a flexible alternative to the Dirichlet distribution for modeling compositional data, relaxing constraints on component variances and correlations through a hierarchical tree structure. While…

Methodology · Statistics 2026-01-16 Jacob A. Turner , Monnie McGee , Bianca A. Luedeker

We review the theoretical foundations, methodological approaches and current status of the determination of nuclear parton distribution functions (PDFs). A large variety of measurements in fixed-target and collider experiments provide…

High Energy Physics - Phenomenology · Physics 2024-07-16 M. Klasen

Maximum Mean Discrepancy (MMD) has been widely used in the areas of machine learning and statistics to quantify the distance between two distributions in the $p$-dimensional Euclidean space. The asymptotic property of the sample MMD has…

Statistics Theory · Mathematics 2023-08-29 Hanjia Gao , Xiaofeng Shao

The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description…

High Energy Physics - Phenomenology · Physics 2015-10-22 Jacques Soffer , Claude Bourrely

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

Study of parton distribution functions (PDFs) has led to a finer cognisance of the structure of partons in hadrons and the proton structure functions in deep inelastic scattering (DIS). PDFs are instrumental in predicting results for most…

High Energy Physics - Phenomenology · Physics 2025-10-02 Akbari Jahan , Diptimonta Neog

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

Stimulated by the need of describing useful notions related to information measures, we introduce the `pdf-related distributions'. These are defined in terms of transformation of absolutely continuous random variables through their own…

Probability · Mathematics 2024-05-02 Antonio Di Crescenzo , Luca Paolillo , Alfonso Suarez-Llorens

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

Multi-parton distribution functions (mPDFs) are non-perturbative objects that are important in the prediction of multiple scattering rates at hadron colliders. In the case where the scales associated with all partons in the mPDF are the…

High Energy Physics - Phenomenology · Physics 2025-10-07 Oleh Fedkevych , Jonathan R. Gaunt , Seonagh Smith

The distribution closeness testing (DCT) assesses whether the distance between a distribution pair is at least $\epsilon$-far. Existing DCT methods mainly measure discrepancies between a distribution pair defined on discrete one-dimensional…

Machine Learning · Computer Science 2025-10-10 Zhijian Zhou , Liuhua Peng , Xunye Tian , Feng Liu

Parton distribution functions (PDFs) with QED corrections extracted from the QED$\otimes$QCD DGLAP evolution equations in the framework of "valon" model. Our results for the PDFs with QED corrections in this phenomenological model are in…

High Energy Physics - Phenomenology · Physics 2017-10-25 Marzieh Mottaghizadeh , Fatemeh Taghavi Shahri , Parvin Eslami

In this contribution we present a status report on the recent progress towards an analysis of nuclear parton distribution functions (nPDFs) using the NNPDF methodology. We discuss how the NNPDF fitting approach can be extended to account…

High Energy Physics - Phenomenology · Physics 2018-11-15 Rabah Abdul Khalek , Jacob J. Ethier , Juan Rojo

The trimming scheme with a prefixed cutoff portion is known as a method of improving the robustness of statistical models such as multivariate Gaussian mixture models (MG- MMs) in small scale tests by alleviating the impacts of outliers.…

Computation and Language · Computer Science 2014-05-20 Dalei Wu , Haiqing Wu

We present {\tt SKMHS22}, a new set of diffractive parton distribution functions (PDFs) and their uncertainties at next-to-leading-order accuracy in perturbative QCD within the {\tt xFitter} framework. We describe all available diffractive…

High Energy Physics - Phenomenology · Physics 2022-10-05 Maral Salajegheh , Hamzeh Khanpour , Ulf-G Meißner , Hadi Hashamipour , Maryam Soleymaninia

A contribution is presented to the study of hadron spectroscopy through the use of fractals and discrete scale invariance implying log-periodic corrections to continuous scaling. The masses of mesons and baryons, reported by the Particle…

General Physics · Physics 2011-05-11 Boris Tatischeff

In the context of a recent CTEQ6.6 global analysis, we review a new technique for studying correlated theoretical uncertainties in hadronic observables associated with imperfect knowledge of parton distribution functions (PDFs). The…

High Energy Physics - Phenomenology · Physics 2008-09-08 Pavel M. Nadolsky

We consider the problem of evaluating dynamic consistency in discrete time probabilistic filters that approximate stochastic system state densities with Gaussian mixtures. Dynamic consistency means that the estimated probability…

Methodology · Statistics 2024-03-18 Nisar Ahmed , Luke Burks , Kailah Cabral , Alyssa Bekai Rose
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