SH010-0001
A Survey of Computational Tools in Solar Physics

Tuesday, 8 December 2020
Poster
Monica Bobra, Stanford University, W.W Hansen Experimental Physics Laboratory, Stanford, CA, United States, Stuart Mumford, University of Sheffield, SP2RC, School of Mathematics and Statistics, Sheffield, United Kingdom, Russell J. Hewett, Virginia Polytechnic Institute and State University, Department of Mathematics, Blacksburg, VA, United States, Steven Christe, NASA GSFC, Solar Physics Lab, Greenbelt, MD, United States, Kevin Reardon, National Solar Observatory, Tucson, AZ, United States, Sabrina L Savage, NASA Marshall Space Flght Ctr, Madison, AL, United States, Jack Ireland, ADNET Systems Inc. Greenbelt, Greenbelt, MD, United States, Tiago Mendes Domingos Pereira, University of Oslo, Oslo, Norway, Bin Chen, New Jersey Institute of Technology, Center for Solar-Terrestrial Research, Edison, NJ, United States and David Pérez-Suárez, University College London, Mullard Space Science Laboratory, Dorking, United Kingdom
Abstract:
The SunPy project is happy to announce the results of the solar physics community survey!

For six months last year, between February and July 2019, the SunPy Project asked members of the solar physics community to fill out a 13-question survey about computational software and hardware. A total of 364 community members, across 35 countries, took 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. 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).

We also found that most respondents (63±4%) have not taken any computer science courses at an undergraduate or graduate level. We found that a small fraction of respondents use the commercial cloud (5%) or a regional or national cluster (14%) for their research. Finally, we found that 73±4% of respondents cite scientific software in their research, although only 42±3% do so routinely.

Our survey results are published in the journal Solar Physics and available via open access at the following URL: https://doi.org/10.1007/s11207-020-01622-2.

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