A Survey of Computational Tools in Solar Physics

Monica G. Bobra, Stuart J. Mumford, Russell J. Hewett, Steven D. Christe, Kevin Reardon, Sabrina Savage, Jack Ireland, Tiago M.D. Pereira, Bin Chen, David Pérez-Suárez

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


The SunPy Project developed a 13-question survey to understand the software and hardware usage of the solar-physics community. Of the solar-physics community, 364 members across 35 countries responded to our survey. We found that 99 ± 0.5 % of respondents use software in their research and 66% use the Python scientific-software stack. Students are twice as likely as faculty, staff scientists, and researchers to use Python rather than Interactive Data Language (IDL). In this respect, the astrophysics and solar-physics communities differ widely: 78% of solar-physics faculty, staff scientists, and researchers in our sample uses IDL, compared with 44% of astrophysics faculty and scientists sampled by Momcheva and Tollerud (2015). 63 ± 4 % of respondents have not taken any computer-science courses at an undergraduate or graduate level. We also found that most respondents use consumer hardware to run software for solar-physics research. Although 82% of respondents work with data from space-based or ground-based missions, some of which (e.g. the Solar Dynamics Observatory and Daniel K. Inouye Solar Telescope) produce terabytes of data a day, 14% use a regional or national cluster, 5% use a commercial cloud provider, and 29% use exclusively a laptop or desktop. Finally, we found that 73 ± 4 % of respondents cite scientific software in their research, although only 42 ± 3 % do so routinely.

Original languageEnglish (US)
Article number57
JournalSolar Physics
Issue number4
StatePublished - Apr 1 2020

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • Instrumentation and data management


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