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Tool for studying the 3D quark and gluon distributions in the nucleon

Home Page: https://gepard.phy.hr/

License: GNU Affero General Public License v3.0

Python 100.00%

physics qcd quark gluon proton nucleon particle-physics

gepard's Introduction

Synopsis

Gepard - tool for studying the 3D quark and gluon distributions in the nucleon

Modelling Generalized Parton Distributions (GPD) and Compton form factors (CFF).
Perturbative NLO QCD evolution of GPDs
Calculation of deeply virtual Compton scattering (DVCS) and deeply virtual meson production (DVMP) observables to NLO accuracy.
Fitting parametrized models to the experimental data.

Installation

Gepard is a Python package available from standard PyPI repository so you should be able to install the latest version together with the required dependencies by simply issuing

pip install gepard

Of course, you should have Python first (version 3.7 at the least), as well as pip, which all major Linux distributions have as standard package. See the documentation for alternative instalation from sources, which is also easy.

Gepard is developed on Linux, but is tested also on Windows and MacOS. Please complain if you have problems.

Using

See the documentation, available at https://gepard.phy.hr/. Also there are lots of examples in the tests subdirectory.

Citing

If you use Gepard for your scientific publications, you might want to cite the arXiv:hep-ph/0703179 paper where theoretical framework that is implemented in the Gepard code is described in some detail.

Copyright and license

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License v3.0 or later. See the file LICENCE for details.

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hamzeh-khanpour camsonne

gepard's Issues

Concurrent use of shelve db broken

[Errno 11] Resource temporarily unavailable occurs often. This could be fixed by introducing some locks.

Numeric regressions

Some tests slightly failing for unknown reasons. Nothing show-stopping:

test_fit2 8.139 != 8.489. This is found to be due to pyminuit --> iminuit change (tests passes on initial release of py2 branch, and then fails like above after commenting out pyminuit import.) It is not clear why other fits are not affected by this package change. We should just go to iminuit and not worry about this one.
ntgl2 DVEMNLO_test.py:test_gepardTFFsNLO 0.54106 != 0.53283. Same for py2 and py3.

pybrain model is severely suboptimal

Calculation of given CFF is done by activating a net, which calculates all CFFs, and then disposing of all CFFs apart from the needed one. This is then repeated for each needed CFF. This makes everything slower by a factor of 5-10.

Superfluous nodes in DR output layers

CFFs that are not trained but are calculated from other CFFs (like in dispersion relations approach or flavor decomposition) still must be present as nodes in output layer. This probably doesn't lead to any errors, but is confusing and unclean coding.

Warning (from warnings module):
  File [...]\Python310\site-packages\gepard\evolution.py", line 270
    tginv = ephnd/np.tan(np.pi*znd/2)
RuntimeWarning: overflow encountered in tan

And three other tan overflows in other places, all related to MSBAR non-diagonal evolution.
Number obtained at the end looks all right, though. No such error on Linux.