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X-ORIGINAL-URL:https://iqus.uw.edu/
X-WR-CALNAME:IQuS
X-WR-CALDESC:InQubator for Quantum Simulation
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UID:MEC-45f31d16b1058d586fc3be7207b58053@iqus.uw.edu
DTSTART:20220815T070000Z
DTEND:20220820T070000Z
DTSTAMP:20220208T175000Z
CREATED:20220208
LAST-MODIFIED:20220914
PRIORITY:5
SEQUENCE:0
TRANSP:OPAQUE
SUMMARY:Next-Generation Computing for Low-Energy Nuclear Physics: from Machine Learning to Quantum Computing
DESCRIPTION:\n\n\n\nOrganizers: Zohreh Davoudi (U. of Maryland), Ubirajara van Kolck (U. of Arizona and Université Paris-Saclay), Silas Beane (UW), and Maria Piarulli (Washington U.)\n\n\n\nAn important goal of modern nuclear physics is to accurately predict nuclear phenomena directly from quantum chromodynamics. One strategy to achieve this is to perform lattice QCD simulations of few-nucleon systems and match them to effective field theories, which in turn can serve as an input to “ab initio” many-body methods  for computing nuclear properties. Both lattice QCD and ab initio many-body methods generally require beyond-exascale classical computation, and are expected to be facilitated by machine learning and quantum computing techniques. Ideas in quantum information science , such as the role of entanglement in nuclear processes, can impact our understanding of nuclear phenomena. Such approaches to computation will prove essential in advancing this critical area of the nuclear-physics mission in the coming decade.\n\n\n\n\n \n\n \n \n\n
URL:https://iqus.uw.edu/events/next-generation-computing-for-low-energy-nuclear-physics-from-machine-leaning-to-quantum-computing/
ORGANIZER;CN=Next-Gen Team - Bira van Kolck, Silas Beane, Zohreh Davoudi and Maria Piarulli:MAILTO:
CATEGORIES:Workshops
LOCATION:University of Washington PHYS/ASTR Building, Seattle, WA 98195
ATTACH;FMTTYPE=image/png:https://iqus.uw.edu/wp-content/uploads/2021/01/many-body.png
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