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Intermittency in MHD turbulence has been analyzed using high resolution 2D numerical simulations. We show that the Probability Distribution Functions (PDFs) of the fluctuations of the Elsasser fields, magnetic field and velocity field…

Chaotic Dynamics · Physics 2015-06-26 L. Sorriso-Valvo , V. Carbone , P. Veltri , H. Politano , A. Pouquet

We present the first lattice results on isovector unpolarized and longitudinally polarized parton distribution functions (PDFs) at physical pion mass. The PDFs are obtained using the large-momentum effective field theory (LaMET) framework…

High Energy Physics - Lattice · Physics 2018-09-12 Huey-Wen Lin , Jiunn-Wei Chen , Tomomi Ishikawa , Jian-Hui Zhang

In this talk, we present our recent work on next-to-leading order (NLO) nuclear parton distribution functions (nPDFs), which we call EPS09. As an extension to earlier NLO analyses, we complement the deep inelastic scattering and Drell-Yan…

High Energy Physics - Phenomenology · Physics 2009-06-17 Kari J. Eskola , Hannu Paukkunen , Carlos A. Salgado

We perform a comprehensive new Monte Carlo analysis of high-energy lepton-lepton, lepton-hadron and hadron-hadron scattering data to simultaneously determine parton distribution functions (PDFs) in the proton and parton to hadron…

High Energy Physics - Phenomenology · Physics 2021-10-20 E. Moffat , W. Melnitchouk , T. C. Rogers , N. Sato

The use of machine learning algorithms in theoretical and experimental high-energy physics has experienced an impressive progress in recent years, with applications from trigger selection to jet substructure classification and detector…

High Energy Physics - Phenomenology · Physics 2018-09-13 Juan Rojo

Diffusion Map is a spectral dimensionality reduction technique which is able to uncover nonlinear submanifolds in high-dimensional data. And, it is increasingly applied across a wide range of scientific disciplines, such as biology,…

Machine Learning · Computer Science 2026-01-29 Sönke Beier , Paula Pirker-Díaz , Friedrich Pagenkopf , Karoline Wiesner

This manuscript outlines a software package that facilitates working with probability distributions by means of Monte-Carlo methods, in a way that allows for propagation of multivariate probability distributions through arbitrary functions.…

Mathematical Software · Computer Science 2020-01-22 Fredrik Bagge Carlson

DisCoPy is a Python toolkit for computing with monoidal categories. It comes with two flexible data structures for string diagrams: the first one for planar monoidal categories based on lists of layers, the second one for symmetric monoidal…

Category Theory · Mathematics 2023-11-20 Alexis Toumi , Richie Yeung , Boldizsár Poór , Giovanni de Felice

Accurate Standard Model predictions of proton-proton collisions are essential for interpreting the current and forthcoming experimental measurements from high-energy colliders. The quest for physics beyond the Standard Model is in fact…

High Energy Physics - Phenomenology · Physics 2025-04-09 Giacomo Magni

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

We investigate the single-file dynamics of a tagged particle in a system consisting of N hardcore interacting particles (the particles cannot pass each other) which are diffusing in a one-dimensional system where the particles have…

Statistical Mechanics · Physics 2009-11-13 Tobias Ambjornsson , Ludvig Lizana , Michael A. Lomholt , Robert J. Silbey

We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation…

High Energy Physics - Phenomenology · Physics 2017-04-05 Tie-Jiun Hou , Jun Gao , Joey Huston , Pavel Nadolsky , Carl Schmidt , Daniel Stump , Bo-Ting Wang , Ke-Ping Xie , Sayipjamal Dulat , Jon Pumplin , C. -P. Yuan

We present appjsonify, a Python-based PDF-to-JSON conversion toolkit for academic papers. It parses a PDF file using several visual-based document layout analysis models and rule-based text processing approaches. appjsonify is a flexible…

Computation and Language · Computer Science 2023-10-04 Atsuki Yamaguchi , Terufumi Morishita

The library scikit-fda is a Python package for Functional Data Analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated…

The recently developed "Data Set Diagonalization" method (DSD) is applied to measure compatibility of the data sets that are used to determine parton distribution functions (PDFs). Discrepancies among the experiments are found to be…

High Energy Physics - Phenomenology · Physics 2010-04-22 Jon Pumplin

Probability density function (PDF) based turbulent combustion modelling is limited by the need to store multi-dimensional PDF tables that can take up large amounts of memory. A significant saving in storage can be achieved by using various…

Computational Engineering, Finance, and Science · Computer Science 2020-05-21 Rishikesh Ranade , Genong Li , Shaoping Li , Tarek Echekki

BiFold calculates the density-dependent (DDM3Y$n$, BDM3Y$n$, CDM3Y$n$) or independent double folded potentials between two colliding spherical nuclei. It is written in a Python package form to give the ability to use the potentials directly…

Computational Physics · Physics 2022-12-05 Mesut Karakoç

We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic resonance Imaging and Cosmology (COSMIC) project. This package provides a set of…

Instrumentation and Methods for Astrophysics · Physics 2020-07-03 S. Farrens , A. Grigis , L. El Gueddari , Z. Ramzi , Chaithya G. R. , S. Starck , B. Sarthou , H. Cherkaoui , P. Ciuciu , J. -L. Starck

I present a determination of longitudinally-polarized parton distribution functions of the proton from inclusive deep-inelastic scattering data: NNPDFpol1.0+. This determination, based on the NNPDF methodology, upgrades a previous analysis,…

High Energy Physics - Phenomenology · Physics 2016-02-17 Emanuele R. Nocera
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