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Advances in many-body theories: from first principle methods to quantum computing and machine learning


Ines Campo
+39 0461 314721
Monday, 18 November, 2019 - 08:00 to Friday, 22 November, 2019 - 14:00
ECT* meeting room

Quantum computing and machine learning are two of the most promising approaches for studying complex physical systems where several length and energy scales are involved. Traditional many-particle methods, either quantum mechanical or classical ones, face huge dimensionality problems when applied to studies of systems with many interacting particles. By bringing together experts from these fields, this workshop will explore the links between these exciting new approaches and traditional many-particle methods in order to map out future research paths.

Registration period: 
02 Sep 2019 to 28 Oct 2019


David Jarvis Dean Oak Ridge National Laboratory
Stefano Gandolfi Los Alamos National Laboratory
Gaute Hagen Oak Ridge National Laboratory/The University of Tennessee
Morten Hjorth-Jensen Michigan State University (USA)
Jason Holt TRIUMF - Vancouver
Thomas Papenbrock University of Tennessee & Oak Ridge National Laboratory
Martin Savage INT & University of Washington


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