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Seizing Electron Energies and Dynamics: a seed for the future (SEED)
Date du début: 1 févr. 2013, Date de fin: 31 janv. 2018 PROJET  TERMINÉ 

Electronic correlation causes a wide range of interesting phenomena, such as superconductivity or the fractional quantum hall effect. It strongly impacts our surroundings – think about defect creation through a self-trapped exciton, or, in the animal world, the adhesion of a gecko on a surface (through the van der Waals attraction). Although the underlying Coulomb interaction is « simple » and well understood, a unifying framework is still missing that would allow us to describe, analyze, understand and predict all those phenomena on the same footing. In this project we will introduce and establish a completely new method for the calculation of properties of correlated electron systems including ground state total energies, excitation spectra, electron-phonon coupling and non-equilibrium dynamics. The method is based on a non-perturbative solution of a multidimensional functional differential equation. This equation is the SEED from which distinct sub-lines of research will be grown.Based on my widely recognized experience in the field of many-body physics and starting from recent results of an exploratory study, the project will encircle the problem working on different levels of approximation, each of them introducing new physics. Thus every step along the project will allow us to tackle challenging questions, such as: “Does strong coupling in a material lead to new or exotic elementary excitations?” or “What can we say about multi - exciton generation, and how could it be tuned?”. These questions and our theoretical answers will be embedded in a tangible context through the study of emerging topics including Mott insulators and materials for photovoltaic applications. Each of these theoretical steps and planned applications carries the potential for breakthrough; together, they promise a seismic shift in our understanding of correlated processes and in our capability to predict new materials properties.