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In this work, we investigate the spectra in an Aharonov-Bohm quantum-ring interferometer forming a Josephson junction between two topological superconductors (TSC) nanowires. The TSCs host Majorana bound states at their edges, and both the magnetic flux and the superconducting phase difference between the TSCs are used as control parameters. We use a tight-binding approach to model the quantum ring coupled to both TSCs, described by the Kitaev effective Hamiltonian. We solve the problem by means of exact numerical diagonalization of the Bogoliubov-de Gennes (BdG) Hamiltonian and obtain the spectra for two sizes of the quantum ring as a function of the magnetic flux and the phase difference between the TSCs. Depending on the size of the quantum ring and the coupling, the spectra display several patterns. Those are denoted as line, point and undulated nodes, together with flat bands, which are topologically protected. The first three patterns can be possibly detected by means of persistent and Josephson currents. Hence, our results could be useful to understand the spectra and their relation with the behavior of the current signals., Comment: 14 pages, 10 figures, 2 tables

LiDAR point clouds contain measurements of complicated natural scenes and can be used to update digital elevation models, glacial monitoring, detecting faults and measuring uplift detecting, forest inventory, detect shoreline and beach volume changes, landslide risk analysis, habitat mapping, and urban development, among others. A very important application is the classification of the 3D cloud into elementary classes. For example, it can be used to differentiate between vegetation, man-made structures, and water. Our goal is to present a preliminary comparison study for the classification of 3D point cloud LiDAR data that includes several types of feature engineering. In particular, we demonstrate that providing context by augmenting each point in the LiDAR point cloud with information about its neighboring points can improve the performance of downstream learning algorithms. We also experiment with several dimension reduction strategies, ranging from Principal Component Analysis (PCA) to neural network-based auto-encoders, and demonstrate how they affect classification performance in LiDAR point clouds. For instance, we observe that combining feature engineering with a dimension reduction a method such as PCA, there is an improvement in the accuracy of the classification with respect to doing a straightforward classification with the raw data., Comment: 21 pages, 12 figures

In this work, we investigate a quantum-ring coupled to a topological superconductor, hosting Majorana bound states (MBSs). We study the MBSs effects over the spectrum and persistent current along the quantum-ring. To obtain physical quantities, we employ the Green's function formalism. We found that the presence of MBSs leads to dramatic changes in the quantum-ring spectrum by inducing particle-hole symmetry. On the other hand, we have obtained a substantial reduction of the persistent current in the strong coupling limit between ring and MBSs depending on the ring parity. These behaviors provide a measurable signature of MBSs. Our findings could be used as additional information on MBSs presence in these quantum systems.

When analyzing empirical data, we often find that global linear models overestimate the number of parameters required. In such cases, we may ask whether the data lies on or near a manifold or a set of manifolds (a so-called multi-manifold) of lower dimension than the ambient space. This question can be phrased as a (multi-) manifold hypothesis. The identification of such intrinsic multiscale features is a cornerstone of data analysis and representation and has given rise to a large body of work on manifold learning. In this work, we review key results on multi-scale data analysis and intrinsic dimension followed by the introduction of a heuristic, multiscale framework for testing the multi-manifold hypothesis. Our method implements a hypothesis test on a set of spline-interpolated manifolds constructed from variance-based intrinsic dimensions. The workflow is suitable for empirical data analysis as we demonstrate on two use cases., Comment: Workshop paper (Women in Data Science and Mathematics Research Collaboration Workshop (WiSDM); ICERM, July 2017)

The low frequency oscillatory relaxation of zonal potential perturbations is studied numerically in the TJ-II stellarator (where it was experimentally detected for the first time). It is studied in full global gyrokinetic simulations of multi-species plasmas. The oscillation frequency obtained is compared with predictions based on single-species simulations using simplified analytical relations. It is shown that the frequency of this oscillation for a multi-species plasma can be accurately obtained from single-species calculations using extrapolation formulas. The damping of the oscillation and the influence of the different inter-species collisions is studied in detail. It is concluded that taking into account multiple kinetic ions and electrons with impurity concentrations realistic for TJ-II plasmas allows to account for the values of frequency and damping rate in zonal flows relaxations observed experimentally., Comment: 11 figures, 22 pages

We consider kinetic systems and prove their stability working in weighted spaces in which the systems are symmetric. We prove stability for various explicit and implicit semi-discrete and fully discrete schemes. The applications include advective and diffusive transport coupled to the accumulation of immobile components governed by non-equilibrium relationships. We also discuss extensions to nonlinear relationships and multiple species., Comment: 27 pages, 5 figures

Achieving impurity and helium ash control is a crucial issue in the path towards fusion-grade magnetic confinement devices, and this is particularly the case of helical reactors, whose low-collisionality ion-root operation scenarios usually display a negative radial electric field which is expected to cause inwards impurity pinch. In these work we discuss, based on experimental measurements and standard predictions of neoclassical theory, how plasmas of very low ion collisionality, similar to those observed in the impurity hole of the Large Helical Device, can be an exception to this general rule, and how a negative radial electric field can coexist with an outward impurity flux. This interpretation is supported by comparison with documented discharges available in the International Stellarator-Heliotron Profile Database, and it can be extrapolated to show that achievement of high ion temperature in the core of helical devices is not fundamentally incompatible with low core impurity content.

We review in a tutorial fashion some of the causes of impurity density variations along field lines and radial impurity transport in the moment approach framework. An explicit and compact form of the parallel inertia force valid for arbitrary toroidal geometry and magnetic coordinates is derived and shown to be non-negligible for typical TJ-II plasma conditions. In the second part of the article, we apply the fluid model including main ion-impurity friction and inertia to observations of asymmetric emissivity patterns in neutral beam heated plasmas of the TJ-II stellarator. The model is able to explain qualitatively several features of the radiation asymmetry, both in stationary and transient conditions, based on the calculated in-surface variations of the impurity density.

We study radial particle transport in stellarator plasmas using cryogenic pellet injection. By means of perturbative experiments, we estimate the experimental particle flux and compare it with neoclassical simulations. Experimental evidence is obtained of the fact that core depletion in helical devices can be slowed-down even by pellets that do not reach the core region. This phenomenon is well captured by neoclassical predictions with DKES and FORTEC-3D.