Related papers: Embedding Dynamical Mean-Field Theory for Supercon…
The Fermi surfaces of Fe-pnictide superconductors are fairly two-dimensional (2D), and it has thus come as a surprise that recent penetration depth and thermal conductivity measurements on systems of the 122 type have reported c-axis…
Ferromagnetic substrates can significantly influence the electromagnetic response of a coated conductor to an external magnetic field and transport current. This study analyzes this response theoretically using the thin shell…
Multicomponent superconductivity is a novel quantum phenomenon in many different superconducting materials, such as multiband ones in which different superconducting gaps open in different Fermi surfaces, films engineered at the atomic…
We use the dynamical mean field method to investigate electronic properties of heterostructures in which finite number of Mott-insulator layers are embedded in a spatially infinite band-insulator. The evolution of the correlation effects…
We present a semi-analytical model to analyze multi-tile metasurface antennas consisting of a set of metasurface tiles and a practical power-dividing network that excites the tiles. The metasurface tiles consist of arrays of rectangular…
Heterostructures between two-dimensional quantum spin Hall insulators (QSHI) and superconducting materials can allow for the presence of Majorana Fermions at their conducting edge states. Although a strong interface hybridization helps…
Network-structured data becomes ubiquitous in daily life and is growing at a rapid pace. It presents great challenges to feature engineering due to the high non-linearity and sparsity of the data. The local and global structure of the…
Materials engineering using atomistic modeling is an essential tool for the development of qubits and quantum sensors. Traditional density-functional theory (DFT) does however not adequately capture the complete physics involved, including…
We theoretically consider superconducting proximity effect, using the Bogoliubov-de Gennes theory, in heterostructure sandwich-type geometries involving a normal s-wave superconductor and a non-superconducting material with the proximity…
As a prototypical example for a heterostructure combining a weakly and a strongly interacting quantum many-body system, we study the interface between a semiconductor and a Mott insulator. Via the hierarchy of correlations, we derive and…
We introduce DMET, a new quantum embedding theory for predicting ground-state properties of infinite systems. Like dynamical mean-field theory (DMFT), DMET maps the the bulk interacting system to a simpler impurity model and is exact in the…
The superconducting proximity effect is investigated for SN double layers in a regime where the resulting transition temperature T_{c} does not depend on the mean free paths of the films and, within limits, not on the transparency of the…
A method is presented for approximating the effective conductivity of composite media with thin interphase regions, which is exact to first order in the interphase thickness. The approximations are computationally efficient in the sense the…
Semi-supervised learning algorithms typically construct a weighted graph of data points to represent a manifold. However, an explicit graph representation is problematic for neural networks operating in the online setting. Here, we propose…
We investigate the possibility of inducing superconductivity in a graphite layer by electronic correlation effects. We use a phenomenological microscopic Hamiltonian which includes nearest neighbor hopping and an interaction term which…
We calculate a low-frequency surface impedance of a dirty, s-wave superconductor with an imperfect surface incorporating either a thin layer with a reduced pairing constant or a thin, proximity-coupled normal layer. Such structures model…
Compared to common density functionals, ab initio wave function methods can provide greater reliability and accuracy, which could prove useful when modeling adsorbates or defects of otherwise periodic systems. However, the breaking of…
The conception of new metamaterials showing unorthodox behaviors with respect to elastic wavepropagation has become possible in recent years thanks to powerful dynamical homogenization techniques. Such methods effectively allow to describe…
Autoencoding is a popular method in representation learning. Conventional autoencoders employ symmetric encoding-decoding procedures and a simple Euclidean latent space to detect hidden low-dimensional structures in an unsupervised way.…
Different classes of low-dimensional superconducting systems exhibit an inhomogeneous filamentary superconducting condensate whose macroscopic coherence still needs to be fully investigated and understood. Here we present a thorough…