Article 6ARAN Open Source is Fueling the Future of Nuclear Physics

Open Source is Fueling the Future of Nuclear Physics

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hubie
from SoylentNews on (#6ARAN)

upstart writes:

This once secretive scientific field is embracing openness in a big way:

The words "nuclear physics" tend to conjure images of heavily guarded laboratories or trench-coated spies whispering to each other on park benches and exchanging briefcases full of file folders stamped "Classified: Top Secret." But despite this reputation for secrecy, today's nuclear scientists embrace openness. And it's paying off.

[...] Many nuclear science organizations have released open source software in recent years, which is a big change from business as usual in the field. Though CERN, which focuses on fundamental particle physics rather than energy generation, is the birthplace of the web and has long embraced open source, other institutions have historically been less open. "There's a history of secrecy in the field. Most fusion and fission software used to be proprietary," says Paul Romano, the project lead for OpenMC and a computational scientist working in nuclear fusion at Argonne National Laboratory. "But as open source has exploded over the past decade, it plays an increasingly important role in research, both in the public and private sectors."

Despite open source's many benefits, it took time for the nuclear science field to adopt the open source ethos. Using open source tools was one thing-Python's vast ecosystem of mathematical and scientific computing tools is widely used for data analysis in the field-but releasing open source code was quite another.

[...] Many of these projects that started with nuclear science in mind are applicable to just about any field that benefits from using supercomputers. MFEM, for example, is also used in LLNL's cardiac simulation toolkit Cardioid, its crystal plasticity application ExaConstit, and its thermomechanical simulation code Serac. It is also heavily used by the broader scientific community, including industry and academia, in applications such as MRI research at Harvard Medical School, and quantum computing hardware simulation at Amazon. MOOSE is widely used outside of the nuclear field, with applications in areas such as groundwater modeling and other geoscience use cases. During the early days of the Covid-19 pandemic, researchers at LLNL used Merlin to anticipate outbreaks and Maestro for antibody modeling.

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