This site refers to the latest GEMC project (version 3 and above).

For CLAS12 simulations refer to this page. For previous GEMC version, refer to this page.

Database-driven architecture
GEant Monte-Carlo

GEMC is a database-driven Monte Carlo simulation program based on Geant4. Key features include:


Databases

Running simulations does not require previous knowledge of C++ or Geant4. A typical workflow looks like this:

  1. Geant4 geometry and materials are uploaded to databases using python
  2. GEMC reads databases and builds the Geant4 world
  3. Particles are transported by Geant4.
  4. Hits are digitized and streamed to the desired formats.
Database-driven architecture

Typical gemc workflow: the Geant4 world is defined from databases sources.
Users can add run time conditions, particles, etc. Geant4's steps are collected in hits, digitized and streamed.



Python API

GEMC does not need to be re-compiled when the geometry is changed.

Python is used to create and upload to databases the geometry, materials, mirrors, etc. The API supports pyvista visualization of the geometry.

Python API example
An example geometry: a flux plane (generated with the snippet below) collects hits from all particles generated by a beam of protons impinging on a liquid hydrogen target. The pyvista option allows immediate visualization of the geometry, which is later simulated through Geant4
flux_z = 50
flux_dx = 1
flux_dim = world_size * 0.8
gvolume = GVolume("FluxPlane")
gvolume.mother = "root"
gvolume.description = "Flux Scoring Plane"
gvolume.make_box(flux_dim * 0.5, flux_dim * 0.5, flux_dx * 0.5)
gvolume.material = "G4_AIR"
gvolume.color = "FAFAD2"
gvolume.set_position(0, 0, flux_z)
gvolume.digitization = "flux"
gvolume.set_identifier("flux_plane", 1)
gvolume.publish(cfg)



Geometry Variations

A detector can be re-used in multiple experiments, with configuration changes such as components shifts, changes of materials, addition or removal of certain volumes. GEMC Supports these geometry versions using variations and/or run numbers to adapt to different simulation setups

Python API example
In the above animation two variations of the CLAS12 Central Detector are shown. The geometries are identical except for the position of the target. They can be selected by specifying a variation string or a run number in the configuration file or command line options.



Status Badges

Gemc is built on several platforms and both arm64, amd64 architectures for every commit and pull request. In addition, nightly releases are built and deployed the Github repository.

Deployment CI
Doxygen Docs
Nightly Nightly
Site Site



Reference


Please make sure to cite the following paper if you use GEMC:

M. Ungaro, Geant4 Monte-Carlo (GEMC) A database-driven simulation program, EPJ Web of Conferences 295, 05005 (2024)

Bibtex:

@INPROCEEDINGS{2024EPJWC.29505005U,
       author = { {Ungaro}, Maurizio,
        title = "{Geant4 Monte-Carlo (GEMC) A database-driven simulation program}",
    booktitle = {European Physical Journal Web of Conferences},
         year = 2024,
       series = {European Physical Journal Web of Conferences},
       volume = {295},
        month = may,
          eid = {05005},
        pages = {05005},
          doi = {10.1051/epjconf/202429505005},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2024EPJWC.29505005U},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Bibitem:

\bibitem{2024EPJWC.29505005U}
{Ungaro}, M.: Geant4 Monte-Carlo (GEMC) A database-driven simulation program.
\newblock European Physical Journal Web of Conferences \textbf{295}, 05005 (2024).
\newblock \doi{10.1051/epjconf/202429505005}



Source Code and Licence

The GEMC source code on GitHub is distributed under an open source license.