What have we learned from Dynamical Mean Field Theory and what lies ahead ?
Invited
Abstract
Dynamical Mean-Field Theory (DMFT) provides both an original perspective on the
physics of strongly correlated electron materials and an efficient computational
framework to understand and predict their properties. In this talk, I will review the
main ideas at the heart of the DMFT construction and physical perspective.
Through select examples, I will outline how the efforts of a whole community
over almost three decades have managed to develop the theory to such a point
that it can successfully be applied to a real material, taking into account its structure
and chemical composition. I will also outline how the theory is being extended
and generalized in many fruitful directions.
physics of strongly correlated electron materials and an efficient computational
framework to understand and predict their properties. In this talk, I will review the
main ideas at the heart of the DMFT construction and physical perspective.
Through select examples, I will outline how the efforts of a whole community
over almost three decades have managed to develop the theory to such a point
that it can successfully be applied to a real material, taking into account its structure
and chemical composition. I will also outline how the theory is being extended
and generalized in many fruitful directions.
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Presenters
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Antoine Georges
College de France, Center for Computational Quantum Physics (CCQ), Flatiron Institute, Collège de France, Paris and Flatiron Institute, New York, Center for Computational Quantum Physics, Flatiron Institute, Flatiron Institute, Center for Computational Quantum Physics
Authors
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Antoine Georges
College de France, Center for Computational Quantum Physics (CCQ), Flatiron Institute, Collège de France, Paris and Flatiron Institute, New York, Center for Computational Quantum Physics, Flatiron Institute, Flatiron Institute, Center for Computational Quantum Physics