Monte Carlo algorithm for strongly interacting non-equilibrium quantum systems in nanoelectronics

Non-equilibrium quantum many-body problems are attracting increasingly more attention in condensed matter physics. For instance, systems of interacting electrons submitted to an external (constant or varying) electric field are studied in nanoelectronics, and more recently in materials, for the search of novel non-equilibrium states of matter. In this thesis, we developed a new numerical generic method for these problems, and apply it to the Anderson impurity model. This model is a good representation of a quantum dot coupled to one or several leads, and gives rise at equilibrium to the Kondo effect --- a manifestation of Coulomb interactions within the dot. We apply our method to compute the collapse of the Kondo effect when the quantum dot is driven out of equilibrium by a voltage bias. Our method is based on a diagrammatic Quantum Monte Carlo (QMC) algorithm. The QMC is an optimized version of the algorithm of Profumo et al. [Phys. Rev. B 91, 245154 (2015)], which computes time-dependent observables or correlation functions as perturbation series in the interaction strength U. To address the problem of diverging series at large U, we constructed a robust resummation scheme which analyses the analytical structure of the series in the U complex plane, for proposing a tailor-made regularization method using a conformal transform of the complex plane. As a post-treatment, a Bayesian technique allows to introduce non-perturbative information to tame the exacerbation of error bars caused by the resummation. We emphasize the potential application to study non-equilibrium materials through "quantum embedding" schemes, such as the Dynamical Mean Field Theory (DMFT), which allow to study lattice models through solving a self-consistent impurity model.