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To leverage emerging computing capabilities and prepare for future exascale systems, the Argonne Leadership Computing Facility, a DOE Office of Science User Facility, is expanding its scope beyond traditional simulation-based research to include data science and machine learning approaches.
A collaboration between the University of Cambridge and Argonne has developed a unique method of generating automatic databases to support specific fields of science using AI and high-performance computing.
Scientists are investigating how to equip quantum computers with artificial intelligence and machine learning approaches.
A new artificial neural network model, created by Argonne scientists, handles both static and dynamic features of a power system with a relatively high degree of accuracy.
As part of the Department of Energy’s Office of Science Graduate Student Research (SCGSR) Program, 62 graduate students were chosen to conduct thesis research across the national laboratory complex, including 12 students at Argonne.
Designing a new type of nuclear reactor is a complicated endeavor requiring billions of dollars and years of development. Because of the high cost, Argonne researchers are running a broad suite of computational codes on supercomputers that offer power available at only a few sites worldwide.
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