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@MapCollaboration

M.A.P. Collaboration

Multi-dimensional Analyses of Partonic distributions

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The MAP (Multi-dimensional Analyses of Partonic distributions) collaboration is a pioneering initiative in the field of hadronic physics. It brings together a group of experts in QCD phenomenology to extract information about the distribution of partons inside hadrons across multidimensional momentum and configuration spaces. Key objects of study include Transverse Momentum Distributions (TMDs), Generalized Parton Distributions (GPDs), and Fragmentation Functions (FFs).

This GitHub repository is our central platform for sharing codes and disseminating research results.

FC99D1F1-B635-4148-8934-7C87B953B289_1_105_c

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  1. NangaParbat NangaParbat Public

    Nanga Parbat: a fitting framework for the determination of the non-perturbative component of TMD distributions

    HTML 3 5

  2. MontBlanc MontBlanc Public

    A code for the determination of collinear distributions

    Jupyter Notebook 2 5

Repositories

Showing 5 of 5 repositories
  • MontBlanc Public

    A code for the determination of collinear distributions

    MapCollaboration/MontBlanc’s past year of commit activity
    Jupyter Notebook 2 GPL-3.0 5 1 1 Updated Jul 17, 2024
  • Denali Public

    Code devoted to the extraction of polarised PDFs

    MapCollaboration/Denali’s past year of commit activity
    Jupyter Notebook 0 GPL-3.0 0 0 0 Updated Apr 9, 2024
  • NangaParbat Public

    Nanga Parbat: a fitting framework for the determination of the non-perturbative component of TMD distributions

    MapCollaboration/NangaParbat’s past year of commit activity
    HTML 3 GPL-3.0 5 2 0 Updated Apr 5, 2024
  • .github Public

    Multi-dimensional Analyses of Partonic distributions

    MapCollaboration/.github’s past year of commit activity
    0 0 0 0 Updated Jun 30, 2023
  • TMDMAP22-results Public

    Results of the global fits of unpolarized TMDs (MAP TMD 22)

    MapCollaboration/TMDMAP22-results’s past year of commit activity
    HTML 0 0 0 0 Updated Jun 1, 2022

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