Spin-orbit-enhanced Wigner localization in quantum dots

We investigate quantum dots with Rashba spin-orbit coupling in the strongly-correlated regime. We show that the presence of the Rashba interaction enhances the Wigner localization in these systems, making it achievable for higher densities than those at which it is observed in Rashba-free quantum dots. Recurring shapes in the pair-correlated densities of the yrast spectrum, which might be associated with rotational and vibrational modes, are also reported.Comment: 5 pages, 4 figure

Local spin fluctuations in iron-based superconductors: 77Se and 87Rb NMR measurements of Tl0.47Rb0.34Fe1.63Se2

We report nuclear magnetic resonance (NMR) studies of the intercalated iron selenide superconductor (Tl, Rb)$_{y}$Fe$_{2-x}$Se$_2$ ($T_c = 32$ K). Single-crystal measurements up to 480 K on both $^{77}$Se and $^{87}$Rb nuclei show a superconducting phase with no magnetic order. The Knight shifts $K$ and relaxation rates $1/T_1T$ increase very strongly with temperature above $T_c$, before flattening at 400 K. The quadratic $T$-dependence and perfect proportionality of both $K$ and $1/T_1T$ data demonstrate their origin in paramagnetic moments. A minimal model for this pseudogap-like response is not a missing density of states but two additive contributions from the itinerant electronic and local magnetic components, a framework unifying the $K$ and $1/T_1 T$ data in many iron-based superconductors

A Comprehensive Survey on Graph Neural Networks

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are typically represented in the Euclidean space. However, there is an increasing number of applications, where data are generated from non-Euclidean domains and are represented as graphs with complex relationships and interdependency between objects. The complexity of graph data has imposed significant challenges on the existing machine learning algorithms. Recently, many studies on extending deep learning approaches for graph data have emerged. In this article, we provide a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields. We propose a new taxonomy to divide the state-of-the-art GNNs into four categories, namely, recurrent GNNs, convolutional GNNs, graph autoencoders, and spatial-temporal GNNs. We further discuss the applications of GNNs across various domains and summarize the open-source codes, benchmark data sets, and model evaluation of GNNs. Finally, we propose potential research directions in this rapidly growing field

Valley Splitting Theory of SiGe/Si/SiGe Quantum Wells

We present an effective mass theory for SiGe/Si/SiGe quantum wells, with an emphasis on calculating the valley splitting. The theory introduces a valley coupling parameter, $v_v$, which encapsulates the physics of the quantum well interface. The new effective mass parameter is computed by means of a tight binding theory. The resulting formalism provides rather simple analytical results for several geometries of interest, including a finite square well, a quantum well in an electric field, and a modulation doped two-dimensional electron gas. Of particular importance is the problem of a quantum well in a magnetic field, grown on a miscut substrate. The latter may pose a numerical challenge for atomistic techniques like tight-binding, because of its two-dimensional nature. In the effective mass theory, however, the results are straightforward and analytical. We compare our effective mass results with those of the tight binding theory, obtaining excellent agreement.Comment: 13 pages, 7 figures. Version submitted to PR

Tomographic measurements on superconducting qubit states

We propose an approach to reconstruct any superconducting charge qubit state by using quantum state tomography. This procedure requires a series of measurements on a large enough number of identically prepared copies of the quantum system. The experimental feasibility of this procedure is explained and the time scales for different quantum operations are estimated according to experimentally accessible parameters. Based on the state tomography, we also investigate the possibility of the process tomography.Comment: 12 pages, 4 figure

Quantum-Mechanical Detection of Non-Newtonian Gravity

In this work the possibility of detecting the presence of a Yukawa term, as an additional contribution to the usual Newtonian gravitational potential, is introduced. The central idea is to analyze the effects at quantum level employing interference patterns (at this respect the present proposal resembles the Colella, Overhauser and Werner experiment), and deduce from it the possible effects that this Yukawa term could have. We will prove that the corresponding interference pattern depends on the phenomenological parameters that define this kind of terms. Afterwards, using the so called restricted path integral formalism, the case of a particle whose position is being continuously monitored, is analyzed, and the effects that this Yukawa potential could have on the measurement outputs are obtained. This allows us to obtain another scheme that could lead to the detection of these terms. This last part also renders new theoretical predictions that could enable us to confront the restricted path integral formalism against some future experiments.Comment: 17 pages, accepted in International Journal of Modern Physics

Quantum Andreev effect in 2D HgTe/CdTe quantum well-superconductor systems

The Andreev reflection (AR) in 2D HgTe/CdTe quantum well-superconductor hybrid systems is studied. A quantized AR with AR coefficient equal to one is predicted, which is due to the multi-Andreev reflection near the interface of the hybrid system. Importantly, this quantized AR is not only universal, i.e., independent of any system parameters and quality of the coupling of the hybrid system, it is also robust against disorder as well. As a result of this quantum Andreev effect, the conductance exhibits a quantized plateau when the external bias is less the superconductor gap.Comment: submit to Phys. Rev. Lett. on Jul. 16, 201