As part of the US federal government’s effort to speed the development of quantum computers, the National Science Foundation (NSF) has awarded the University of California, Berkeley, $25 million over five years to establish a multi-university institute focused on advancing quantum science and engineering and training a future workforce to build and use quantum computers.
The UC Berkeley-led center is one of three Quantum Leap Challenge Institutes (QLCI) announced on July 21, 2020, by NSF and represents a $75 million investment. The initiatives are a central part of the National Quantum Initiative Act of 2018, the White House’s Industries of the Future program and NSF’s ongoing Quantum Leap effort.
The QLCI for Present and Future Quantum Computation connects UC Berkeley, UCLA, UC Santa Barbara and five other universities around the country, harnessing a wealth of experimental and theoretical quantum scientists to improve and determine how best to use today’s rudimentary quantum computers, most of them built by private industry or government labs.
The group plans to focus on three experimental platforms that use different quantum systems as qubits: trapped ions, trapped atoms and superconducting circuits.
The grant will foster interactions among researchers and doctoral students from many fields with the help of fellowships, conferences and workshops. But a major component will be training a future workforce akin to the way computer science training at universities like UC Berkeley and Stanford fueled Silicon Valley’s rise to become a tech giant. UCLA will pilot a master’s degree program in quantum science and technology to train a quantum-smart workforce, while massive online courses, or MOOCs, will help spread knowledge and understanding of quantum computers even for high school students.
The two other $25 million Quantum Leap Challenge Institutes announced today are centered at the University of Colorado, Boulder, and the University of Illinois, Urbana-Champaign, and will focus on quantum sensing and quantum networks, respectively. (SciTechDaily)
