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

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

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

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

Modeling Luminosity-Dependent Galaxy Clustering Through Cosmic Time

We employ high-resolution dissipationless simulations of the concordance LCDM cosmology to model the observed luminosity dependence and evolution of galaxy clustering through most of the age of the universe, from z~5 to z~0. We use a simple, non-parametric model which monotonically relates galaxy luminosities to the maximum circular velocity of dark matter halos (V_max) by preserving the observed galaxy luminosity function in order to match the halos in simulations with observed galaxies. The novel feature of the model is the use of the maximum circular velocity at the time of accretion, V_max,acc, for subhalos, the halos located within virial regions of larger halos. We argue that for subhalos in dissipationless simulations, V_max,acc reflects the luminosity and stellar mass of the associated galaxies better than the circular velocity at the epoch of observation, V_max,now. The simulations and our model L-V_max relation predict the shape, amplitude, and luminosity dependence of the two-point correlation function in excellent agreement with the observed galaxy clustering in the SDSS data at z~0 and in the DEEP2 samples at z~1 over the entire probed range of projected separations, 0.1<r_p/(Mpc/h)<10.0. In particular, the small-scale upturn of the correlation function from the power-law form in the SDSS and DEEP2 luminosity-selected samples is reproduced very well. At z~3-5, our predictions also match the observed shape and amplitude of the angular two-point correlation function of Lyman-break galaxies (LBGs) on both large and small scales, including the small-scale upturn.Comment: 16 pages 11 figures, ApJ in pres

Observational Evidence for an Age Dependence of Halo Bias

We study the dependence of the cross-correlation between galaxies and galaxy groups on group properties. Confirming previous results, we find that the correlation strength is stronger for more massive groups, in good agreement with the expected mass dependence of halo bias. We also find, however, that for groups of the same mass, the correlation strength depends on the star formation rate (SFR) of the central galaxy: at fixed mass, the bias of galaxy groups decreases as the SFR of the central galaxy increases. We discuss these findings in light of the recent findings by Gao et al (2005) that halo bias depends on halo formation time, in that halos that assemble earlier are more strongly biased. We also discuss the implication for galaxy formation, and address a possible link to galaxy conformity, the observed correlation between the properties of satellite galaxies and those of their central galaxy.Comment: 4 pages, 4 figures, Accepted for publication in ApJ Letters. Figures 3 and 4 replaced. The bias dependence on the central galaxy luminosity is omitted due to its sensitivity to the mass mode

Groups of Galaxies in the Two Micron All-Sky Redshift Survey

We present the results of applying a percolation algorithm to the initial release of the Two Micron All-Sky Survey Extended Source Catalog, using subsequently measured redshifts for almost all of the galaxies with K < 11.25 mag. This group catalog is based on the first near-IR all-sky flux-limited survey that is complete to |b| = 5 deg. We explore the dependence of the clustering on the length and velocity scales involved. The paper describes a group catalog, complete to a limiting redshift of 10,000 km/s, created by maximizing the number of groups containing 3 or more members. A second catalog is also presented, created by requiring a minimum density contrast of 80 to identify groups. We identify known nearby clusters in the catalogs and contrast the groups identified in the two catalogs. We examine and compare the properties of the determined groups and verify that the results are consistent with the UZC-SSRS2 and northern CfA redshift survey group catalogs. The all-sky nature of the catalog will allow the development of a flow-field model based on the density field inferred from the estimated cluster masses.Comment: Accepted for publication in ApJ (29 pages including 13 figures). A version with high-resolution figures is available at http://www.cfa.harvard.edu/~acrook/preprints

Properties of Galaxy Groups in the SDSS: II.- AGN Feedback and Star Formation Truncation

Successfully reproducing the galaxy luminosity function and the bimodality in the galaxy distribution requires a mechanism that can truncate star formation in massive haloes. Current models of galaxy formation consider two such truncation mechanisms: strangulation, which acts on satellite galaxies, and AGN feedback, which predominantly affects central galaxies. The efficiencies of these processes set the blue fraction of galaxies as function of galaxy luminosity and halo mass. In this paper we use a galaxy group catalogue extracted from the Sloan Digital Sky Survey (SDSS) to determine these fractions. To demonstrate the potential power of this data as a benchmark for galaxy formation models, we compare the results to the semi-analytical model for galaxy formation of Croton et al. (2006). Although this model accurately fits the global statistics of the galaxy population, as well as the shape of the conditional luminosity function, there are significant discrepancies when the blue fraction of galaxies as a function of mass and luminosity is compared between the observations and the model. In particular, the model predicts (i) too many faint satellite galaxies in massive haloes, (ii) a blue fraction of satellites that is much too low, and (iii) a blue fraction of centrals that is too high and with an inverted luminosity dependence. In the same order, we argue that these discrepancies owe to (i) the neglect of tidal stripping in the semi-analytical model, (ii) the oversimplified treatment of strangulation, and (iii) improper modeling of dust extinction and/or AGN feedback. The data presented here will prove useful to test and calibrate future models of galaxy formation and in particular to discriminate between various models for AGN feedback and other star formation truncation mechanisms.Comment: 16 pages, 5 figures, submitted to MNRA