• DOI:10.3389/fspas.2022.1058810
• Corpus ID: 252683811

Solar-MACH: An open-source tool to analyze solar magnetic connection configurations

@article{Gieseler2022SolarMACHAO,
  title={Solar-MACH: An open-source tool to analyze solar magnetic connection configurations},
  author={Jan Gieseler and Nina Dresing and Christian Palmroos and Johan L. Freiherr von Forstner and Daniel J. Price and Rami Vainio and Athanasios Kouloumvakos and L. Rodr'iguez-Garc'ia and Domenico Trotta and Vincent G'enot and Arnaud Masson and Markus Roth and Astrid Veronig},
  journal={Frontiers in Astronomy and Space Sciences},
  year={2022}
}

• J. Gieseler, N. Dresing, +10 authors A. Veronig
• Published 3 October 2022
• Physics
• Frontiers in Astronomy and Space Sciences

The Solar MAgnetic Connection HAUS1 tool (Solar-MACH) is an open-source tool completely written in Python that derives and visualizes the spatial configuration and solar magnetic connection of different observers (i.e., spacecraft or planets) in the heliosphere at different times. For doing this, the magnetic connection in the interplanetary space is obtained by the classic Parker Heliospheric Magnetic Field (HMF). In close vicinity of the Sun, a Potential Field Source Surface (PFSS) model can be applied to connect the HMF to the solar photosphere. Solar-MACH is especially aimed at providing publication-ready figures for the analyses of Solar Energetic Particle events (SEPs) or solar transients such as Coronal Mass Ejections (CMEs). It is provided as an installable Python package (listed on PyPI and conda-forge), but also as a web tool at solar-mach.github.io that completely runs in any web browser and requires neither Python knowledge nor installation. The development of Solar-MACH is open to everyone and takes place on GitHub, where the source code is publicly available under the BSD 3-Clause License. Established Python libraries like sunpy and pfsspy are utilized to obtain functionalities when possible. In this article, the Python code of Solar-MACH is explained, and its functionality is demonstrated using real science examples. In addition, we introduce the overarching SERPENTINE project, the umbrella under which the recent development took place.