PDFxTMDLib · C++17 and Python

A unified library for PDFs and TMDs.

PDFxTMDLib is an open-source library for evaluating collinear parton distribution functions and transverse-momentum-dependent distributions from standard or custom grids.

Installation Tutorials API reference
Language
C++17 with Python bindings
Scope
Collinear PDFs and TMDs
License
GPL-3.0
Platforms
Linux, macOS, and Windows

I

Principal features

A practical interface with room to extend

Unified set access

Load collinear or TMD sets, select individual members, inspect metadata, and evaluate flavors through a consistent family of interfaces.

Browse the API reference

Extensible C++ design

Use the default components or provide custom readers, interpolators, and extrapolators for specialized data and research workflows.

Read the C++ tutorial

Analysis utilities

Calculate central values, asymmetric uncertainties, correlations, and the strong coupling using set metadata in C++ or Python.

Read the Python tutorial

II

A first calculation

Evaluate a collinear distribution

The high-level PDFSet interface manages all members of a set and provides access to metadata, uncertainty calculations, correlations, and strong coupling.

Install the library, configure a data-set search path, and evaluate the desired parton flavor.

Installation guide Configure PDF sets

example.cppC++
#include <PDFxTMDLib/PDFSet.h>
#include <iostream>

int main() {
    PDFxTMD::PDFSet<PDFxTMD::CollinearPDFTag> set("MSHT20nlo_as120");
    auto central = set[0];

    const double x = 0.1;
    const double mu2 = 10000.0; // GeV^2
    const double gluon = central->pdf(PDFxTMD::PartonFlavor::g, x, mu2);

    std::cout << "g(x, mu2) = " << gluon << '\n';
}

III

A simple path

From installation to analysis

  1. 01

    Install

    Build the C++ library with CMake or install the Python bindings from PyPI.

    Open
  2. 02

    Configure

    Download a collinear or TMD set and add its parent directory to config.yaml.

    Open
  3. 03

    Calculate

    Follow complete C++ and Python examples for values, uncertainties, correlations, and αs.

    Open

IV

Reference shelf

Project resources

Source repositoryImplementation, releases, examples, and issue tracking Python packageInstall the published bindings with pip Jupyter notebookRun the maintained tutorial in Google Colab API referenceDoxygen documentation for classes, templates, and functions Project paperArchitecture, validation, and scientific context DownloadsTMD grids, utilities, and integration packages

Open-source research software

Use PDFxTMDLib in your work.

When PDFxTMDLib contributes to published research, please cite the project paper.

Get started Citation details