Related papers: Unsupervised Learning of Effective Quantum Impurit…
Quantum embedding methods have become a powerful tool to overcome deficiencies of traditional quantum modelling in materials science. However, while these are systematically improvable in principle, in practice it is rarely possible to…
An acceleration of continuous time quantum Monte Carlo (CTQMC) methods is a potentially interesting branch of work as they are matchless as impurity solvers of a density functional theory in combination with a dynamical mean field theory…
We develop a general approach to the nonequilibrium dynamics of quantum impurity systems for arbitrary coupling strength. The numerical renormalization group is used to generate a complete basis set necessary for the correct description of…
We study a Kondo state that is strongly influenced by its proximity to an w^-1/2 singularity in the metallic host density of states. This singularity occurs at the bottom of the band of a 1D chain, for example. We first analyze the…
An impurity solver based on a continuous-time quantum Monte Carlo method is developed for the Coqblin-Schrieffer model. The Monte Carlo simulation does not encounter a sign problem for antiferromagnetic interactions, and accurately…
A hierarchical equations of motion (HEOM) based numerical approach is developed for accurate and efficient evaluation of dynamical observables of strongly correlated quantum impurity systems. This approach is capable of describing…
We study a generalized multichannel single-impurity Kondo model, in which the impurity spin is described by a representation of the SU(N) group which combines bosonic and fermionic degrees of freedom. The impurity spin states are described…
We show that the low energy behaviour of quite diverse impurity systems can be described by a single renormalized Anderson model, with three parameters, an effective level $\tilde\epsilon_d$, an effective hybridization $\tilde V$, and a…
This course aims to introduce the student to random matrix models for decoherence and fidelity decay. They present a very powerful alternate approach, that emphasizes the disordered character of many environments and uncontrollable…
Identifying an accurate model for the dynamics of a quantum system is a vexing problem that underlies a range of problems in experimental physics and quantum information theory. Recently, a method called quantum Hamiltonian learning has…
We study the low-temperature behavior of a magnetic impurity which is weakly coupled to correlated conduction electrons. To account for conduction electron interactions a diagrammatic approach in the frame of the 1/N expansion is developed.…
The one dimensional dilute Kondo lattice model is investigated by means of bosonization for different dilution patterns of the array of impurity spins. The physical picture is very different if a commensurate or incommensurate doping of the…
The underscreened Kondo effect is studied within a model of two impurities S=1 interacting with the conduction band and via an interimpurity coupling $K\vec{S_1}.\vec{S_2}$. Using a mean-field treatment of the bosonized Hamiltonian, we show…
Impurity four- and six-level Kondo model, in which an ion is tunneling among four- and six-stable points and interacting with surrounding conduction electrons, are investigated by using the perturbative and numerical renormalization group…
We build upon recent work on using Machine Learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning where the…
We study a localized spin coupled to an Anderson impurity to model the situation found in higher transition metal or rare earth compounds like e.g.\ LaMnO$_3$ or Gd monopnictides. We find that, even for large quantum numbers of the…
Most existing learning-based methods for solving imaging inverse problems can be roughly divided into two classes: iterative algorithms, such as plug-and-play and diffusion methods leveraging pretrained denoisers, and unrolled architectures…
Noise is often regarded as a limitation of quantum computers. In this work, we show that in the dynamical mean field theory (DMFT) approach to strongly-correlated systems, it can actually be harnessed to our advantage. Indeed, DMFT maps a…
The most common error models for quantum computers assume the independence of errors on different qubits. However, most noise mechanisms have some correlations in space. We show how to improve quantum information processing for few-qubit…
In this work we study the Kondo impurity problem - at a finite concentration of impurities. We identify two parameter regimes for the Kondo impurity problem. 1) The single impurity limit, where the concentration of Kondo impurities is so…