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DOE Funds Project to Apply Supercomputers in Nuclear Physics Research

Funding opportunity

announcement

DOE Funds Project to Apply Supercomputers in Nuclear Physics Research

The Department of Energy has earmarked $35 million in funding for efforts to increase understanding of nuclear physics concepts such as the nucleon structure, nuclear matter and strong force.

The funding is available through the Scientific Discovery through Advanced Computing program, which is focused on maximizing the utility of high-performance computing resources for scientific research, DOE said.

DOE added that it expects the SciDAC Partnership in Nuclear Physics to bring together experts from key disciplines like software development, applied mathematics and computer science.

Timothy Hallman, associate director of science for nuclear physics, said that high-performance computing has changed how scientists solve problems in nuclear physics.

“Large scale simulations and calculations are critical in studying nuclear matter due to the nonlinear and quantum nature of strong interactions,” Hallman added.

DOE said that the funding will support work at nuclear physics laboratories such as the Continuous Electron Beam Accelerator Facility, the Relativistic Heavy Ion Collider, the Facility for Rare Isotope Beams and the planned Electron-Ion Collider.

The department noted that the FRIB, which was only recently completed, is expected to unlock new insights into rare isotopes, nuclear astrophysics, medicine, homeland security and industry.

The funding round includes $7 million in anticipated fiscal year 2022 funding as well as funding contingent on congressional appropriations,

DOE encouraged its national laboratories to engage with universities and to submit collaborative proposals for the SciDAC funding opportunity.

The effort is sponsored by the DOE Office of Sciences’ Nuclear Physics and Advanced Scientific Computing Research program offices.

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Category: Federal Civilian

Tags: computer science Department of Energy federal civilian funding opportunity high-performance computing nuclear physics SciDAC