Advances in Many-Body Theories: from First Principle Methods to Quantum Computing and Machine Learning

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:  2 Sep 2020 to 10 Oct 2020

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