The Centaurus Group and the Outer Halo of NGC 5128: Are they Dynamically Connected?

NGC 5128, a giant elliptical galaxy only $\sim 4$ Mpc away, is the dominant member of a galaxy group of over 80 probable members. The Centaurus group provides an excellent sample for a kinematic comparison between the halo of NGC 5128 and its surrounding satellite galaxies. A new study, presented here, shows no kinematic difference in rotation amplitude, rotation axis, and velocity dispersion between the halo of NGC 5128, determined from over $\sim340$ of its globular clusters, and those of the Centaurus group as a whole. These results suggest NGC 5128 could be behaving in part as the inner component to the galaxy group, and could have begun as a large initial seed galaxy, gradually built up by minor mergers and satellite accretions, consistent with simple cold dark matter models. The mass and mass-to-light ratios in the B-band, corrected for projection effects, are determined to be $(1.3\pm0.5) \times 10^{12}$ M_{\sun} and $52\pm22$ M_{\sun}/L_{\sun} for NGC 5128 out to a galactocentric radius of 45 kpc, and $(9.2\pm3.0) \times 10^{12}$ M_{\sun} and $153\pm50$ M_{\sun}/L_{\sun} for the Centaurus group, consistent with previous studies.Comment: 14 pages, 3 tables, 7 figures, Accepted for publication in A

A Circuit Model for Domain Walls in Ferromagnetic Nanowires: Application to Conductance and Spin Transfer Torques

We present a circuit model to describe the electron transport through a domain wall in a ferromagnetic nanowire. The domain wall is treated as a coherent 4-terminal device with incoming and outgoing channels of spin up and down and the spin-dependent scattering in the vicinity of the wall is modelled using classical resistances. We derive the conductance of the circuit in terms of general conductance parameters for a domain wall. We then calculate these conductance parameters for the case of ballistic transport through the domain wall, and obtain a simple formula for the domain wall magnetoresistance which gives a result consistent with recent experiments. The spin transfer torque exerted on a domain wall by a spin-polarized current is calculated using the circuit model and an estimate of the speed of the resulting wall motion is made.Comment: 10 pages, 5 figures; submitted to Physical Review

Theory of scanning gate microscopy

A systematic theory of the conductance measurements of non-invasive (weak probe) scanning gate microscopy is presented that provides an interpretation of what precisely is being measured. A scattering approach is used to derive explicit expressions for the first and second order conductance changes due to the perturbation by the tip potential in terms of the scattering states of the unperturbed structure. In the case of a quantum point contact, the first order correction dominates at the conductance steps and vanishes on the plateaus where the second order term dominates. Both corrections are non-local for a generic structure. Only in special cases, such as that of a centrally symmetric quantum point contact in the conductance quantization regime, can the second order correction be unambiguously related with the local current density. In the case of an abrupt quantum point contact we are able to obtain analytic expressions for the scattering eigenfunctions and thus evaluate the resulting conductance corrections.Comment: 19 pages, 7 figure

Inclination-Independent Galaxy Classification

We present a new method to classify galaxies from large surveys like the Sloan Digital Sky Survey using inclination-corrected concentration, inclination-corrected location on the color-magnitude diagram, and apparent axis ratio. Explicitly accounting for inclination tightens the distribution of each of these parameters and enables simple boundaries to be drawn that delineate three different galaxy populations: Early-type galaxies, which are red, highly concentrated, and round; Late-type galaxies, which are blue, have low concentrations, and are disk dominated; and Intermediate-type galaxies, which are red, have intermediate concentrations, and have disks. We have validated our method by comparing to visual classifications of high-quality imaging data from the Millennium Galaxy Catalogue. The inclination correction is crucial to unveiling the previously unrecognized Intermediate class. Intermediate-type galaxies, roughly corresponding to lenticulars and early spirals, lie on the red sequence. The red sequence is therefore composed of two distinct morphological types, suggesting that there are two distinct mechanisms for transiting to the red sequence. We propose that Intermediate-type galaxies are those that have lost their cold gas via strangulation, while Early-type galaxies are those that have experienced a major merger that either consumed their cold gas, or whose merger progenitors were already devoid of cold gas (the ``dry merger'' scenario).Comment: Accepted for publication in ApJ. 7 pages in emulateap

TCR-Signaling Events in Cellular Metabolism and Specialization

Engaging the T cell receptor (TCR) with peptide:MHC complexes initiates a cascade of signaling events that activates T cells in an antigen specific manner. It is now clear that multiple inputs, including the strength of TCR signaling, co-stimulation, and the cytokine environment, impact T cell specialization decisions in the context of specific pathogenic encounters. Additionally, it is now appreciated that these same stimuli direct cellular metabolism programs. In this review, we will discuss how TCR-signaling events coordinate cellular metabolism and specialization gene programs in T cells

Voxel-Based Indoor Reconstruction From HoloLens Triangle Meshes

Current mobile augmented reality devices are often equipped with range sensors. The Microsoft HoloLens for instance is equipped with a Time-Of-Flight (ToF) range camera providing coarse triangle meshes that can be used in custom applications. We suggest to use the triangle meshes for the automatic generation of indoor models that can serve as basis for augmenting their physical counterpart with location-dependent information. In this paper, we present a novel voxel-based approach for automated indoor reconstruction from unstructured three-dimensional geometries like triangle meshes. After an initial voxelization of the input data, rooms are detected in the resulting voxel grid by segmenting connected voxel components of ceiling candidates and extruding them downwards to find floor candidates. Semantic class labels like 'Wall', 'Wall Opening', 'Interior Object' and 'Empty Interior' are then assigned to the room voxels in-between ceiling and floor by a rule-based voxel sweep algorithm. Finally, the geometry of the detected walls and their openings is refined in voxel representation. The proposed approach is not restricted to Manhattan World scenarios and does not rely on room surfaces being planar.Comment: 8 pages, 4 figure

Normal classification of 3D occupancy grids for voxel-based indoor reconstruction from point clouds

In this paper, we present an automated method for classification of binary voxel occupancy grids of discretized indoor mapping data such as point clouds or triangle meshes according to normal vector directions. Filled voxels get assigned normal class labels distinguishing between horizontal and vertical building structures. The horizontal building structures are further differentiated into those with normal directions pointing upwards or downwards with respect to the building interior. The derived normal grids can be deployed in the context of an existing voxel-based indoor reconstruction pipeline, which so far was only applicable to indoor mapping triangle meshes that already contain normal vectors consistently oriented with respect to the building interior. By means of quantitative evaluation against reference data, we demonstrate the performance of the proposed method and its applicability in the context of voxel-based indoor reconstruction from indoor mapping point clouds without normal vectors. The code of our implementation is made available to the public at https://github.com/huepat/voxir

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation

Length-dependent oscillations of the conductance through atomic chains: The importance of electronic correlations

We calculate the conductance of atomic chains as a function of their length. Using the Density Matrix Renormalization Group algorithm for a many-body model which takes into account electron-electron interactions and the shape of the contacts between the chain and the leads, we show that length-dependent oscillations of the conductance whose period depends on the electron density in the chain can result from electron-electron scattering alone. The amplitude of these oscillations can increase with the length of the chain, in contrast to the result from approaches which neglect the interactions.Comment: 7 pages, 4 figure