Researchers across the world have already amassed tons of info about COVID-19, and learn more every day. Now, Berkeley Lab experts are developing a platform that puts all this valuable knowledge in one place, and leverages machine learning to make new discoveries.
New simulations led by researchers working at the Berkeley Lab and UC Berkeley combine decades-old theories to provide new insight about the driving mechanisms in plasma jets that allow them to steal energy from black holes’ powerful gravitational fields and propel it far from their gaping mouths.
The U.S. Department of Energy announced today that the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab has signed a $146 million contract with Cray for the facility’s next-generation supercomputer, a pre-exascale machine slated to be delivered in 2020. Named “Perlmutter” in honor of Nobel Prize-winning astrophysicist Saul Perlmutter, it is the first NERSC system specifically designed to meet the needs of large-scale simulations as well as data analysis from experimental and observational facilities.
Researchers at Berkeley Lab are developing an “optimization algorithm” toolset that pinpoints which variables of a “black box” simulation model will churn out the most realistic data in less time.
The U.S. Department of Energy announced today that Berkeley Lab will receive $30 million over five years to build and operate an Advanced Quantum Testbed. Researchers will use the testbed to explore superconducting quantum processors and evaluate how these emerging quantum devices can be utilized to advance scientific research. As part of this effort, Berkeley Lab will collaborate with MIT Lincoln Laboratory to deploy different quantum processor architectures.
Scientists have decoded faint distortions in the patterns of the universe’s earliest light to map huge tubelike structures invisible to our eyes – known as filaments – that serve as superhighways for delivering matter to dense hubs such as galaxy clusters.
A team of researchers from the Department of Energy’s Berkeley Lab and Joint Genome Institute took one of the most popular clustering algorithms in modern biology and modified it to run quickly, efficiently and at scale on distributed-memory supercomputers.