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

Geant4 objects are uploaded to databases using the python API. Running simulations looks like this:

  1. GEMC reads databases (ASCII, SQLite, GDML, CAD files) to create the Geant4 volumes, materials, surfaces, etc.
  2. Generated particle are transported through the geometry by Geant4.
  3. The resulting hits are processed, collected and digitized.
  4. Outputs are streamed to the desired formats.
Database-driven architecture

Typical gemc workflow: detectors can be loaded from several databases sources.
Users can add run time conditions by moving detectors, changing materials, etc.



Python API

Python is used to create and upload to databases the geometry, materials, mirrors, etc. GEMC does not need to be re-compiled when the geometry is changed. 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
	gvolume = GVolume('flux_box')
	gvolume.description = 'carbon fiber box'
	gvolume.make_box(40.0, 40.0, 2.0)
	gvolume.material    = 'carbonFiber'
	gvolume.color       = '3399FF'
	gvolume.digitization = 'flux'
	gvolume.set_position(0, 0, 100)
	gvolume.style       = 1
	gvolume.set_identifier('box', 2)  # identifier for this box
	gvolume.publish(configuration)



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


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.