Lensed galaxies in Abell 370 I. Modeling the number counts and redshift distribution of background sources

We present new observations of the cluster-lens Abell 370: a deep HST/WFPC2 F675W image and ESO 3.6m spectroscopy of faint galaxies. These observations shade new lights on the statistical properties of faint lensed galaxies. In particular, we spectroscopically confirm the multiple image nature of the B2--B3 gravitational pair (Kneib et al. 1993), and determine a redshift of z=0.806 which is in very good agreement with earlier predictions. A refined mass model of the cluster core (that includes cluster galaxy halos) is presented, based on a number of newly identified multiple images. Following Bezecourt et al. (1998a), we combine the new cluster mass model with a spectrophotometric prescription for galaxy evolution to predict the arclets number counts and redshift distribution in the HST image. In particular, the ellipticity distribution of background sources is taken into account, in order to properly estimate the statistical number and redshift distribution of arclets. We show that the redshift distribution of arclets, and particularly its high redshift tail can be used as a strong constraint to disentangle different galaxy evolution scenario. A hierarchical model which includes a number density evolution is favored by our analysis. Finally, we compute the depletion curves in the faint galaxies number counts and discuss its wavelength dependence.Comment: 10 pages, Astronomy and Astrophysics in pres

The Iray Light Transport Simulation and Rendering System

While ray tracing has become increasingly common and path tracing is well understood by now, a major challenge lies in crafting an easy-to-use and efficient system implementing these technologies. Following a purely physically-based paradigm while still allowing for artistic workflows, the Iray light transport simulation and rendering system allows for rendering complex scenes by the push of a button and thus makes accurate light transport simulation widely available. In this document we discuss the challenges and implementation choices that follow from our primary design decisions, demonstrating that such a rendering system can be made a practical, scalable, and efficient real-world application that has been adopted by various companies across many fields and is in use by many industry professionals today

Towards multiple 3D bone surface identification and reconstruction using few 2D X-ray images for intraoperative applications

This article discusses a possible method to use a small number, e.g. 5, of conventional 2D X-ray images to reconstruct multiple 3D bone surfaces intraoperatively. Each bone’s edge contours in X-ray images are automatically identified. Sparse 3D landmark points of each bone are automatically reconstructed by pairing the 2D X-ray images. The reconstructed landmark point distribution on a surface is approximately optimal covering main characteristics of the surface. A statistical shape model, dense point distribution model (DPDM), is then used to fit the reconstructed optimal landmarks vertices to reconstruct a full surface of each bone separately. The reconstructed surfaces can then be visualised and manipulated by surgeons or used by surgical robotic systems

Multiple spiral patterns in the transitional disk of HD 100546

Protoplanetary disks around young stars harbor many structures related to planetary formation. Of particular interest, spiral patterns were discovered among several of these disks and are expected to be the sign of gravitational instabilities leading to giant planets formation or gravitational perturbations caused by already existing planets. In this context, the star HD100546 presents some specific characteristics with a complex gas and dusty disk including spirals as well as a possible planet in formation. The objective of this study is to analyze high contrast and high angular resolution images of this emblematic system to shed light on critical steps of the planet formation. We retrieved archival images obtained at Gemini in the near IR (Ks band) with the instrument NICI and processed the data using advanced high contrast imaging technique taking advantage of the angular differential imaging. These new images reveal the spiral pattern previously identified with HST with an unprecedented resolution, while the large-scale structure of the disk is mostly erased by the data processing. The single pattern at the southeast in HST images is now resolved into a multi-armed spiral pattern. Using two models of a gravitational perturber orbiting in a gaseous disk we attempted to bring constraints on the characteristics of this perturber assuming each spiral being independent and we derived qualitative conclusions. The non-detection of the northeast spiral pattern observed in HST allows to put a lower limit on the intensity ratio between the two sides of the disk, which if interpreted as forward scattering yields a larger anisotropic scattering than derived in the visible. Also, we found that the spirals are likely spatially resolved with a thickness of about 5-10AU. Finally, we did not detect the candidate forming planet recently discovered in the Lp band, with a mass upper limit of 16-18 MJ.Comment: Accepted for publication in Astronomy and Astrophysics, 10 pages, 8 figure

Mapping the radial structure of AGN tori

We present mid-IR interferometric observations of 6 type 1 AGNs at multiple baseline lengths of 27--130m, reaching high angular resolutions up to lambda/B~0.02 arcseconds. For two of the targets, we have simultaneous near-IR interferometric measurements as well. The multiple baseline data directly probe the radial distribution of the material on sub-pc scales. Within our sample, which is small but spans over ~2.5 orders of magnitudes in the UV/optical luminosity L of the central engine, the radial distribution clearly and systematically changes with luminosity. First, we show that the brightness distribution at a given mid-IR wavelength seems to be rather well described by a power law, which makes a simple Gaussian or ring size estimation quite inadequate. Here we instead use a half-light radius R_1/2 as a representative size. We then find that the higher luminosity objects become more compact in normalized half-light radii R_1/2 /R_in in the mid-IR, where R_in is the dust sublimation radius empirically given by the L^1/2 fit of the near-IR reverberation radii. This means that, contrary to previous studies, the physical mid-IR emission size (e.g. in pc) is not proportional to L^1/2, but increases with L much more slowly, or in fact, nearly constant at 13 micron. Combining the size information with the total flux specta, we infer that the radial surface density distribution of the heated dust grains changes from a steep ~r^-1 structure in high luminosity objects to a shallower ~r^0 structure in those of lower luminosity. The inward dust temperature distribution does not seem to smoothly reach the sublimation temperature -- on the innermost scale of ~R_in, a relatively low temperature core seems to co-exist with a slightly distinct brightness concentration emitting roughly at the sublimation temperature.Comment: accepted for publication in A&

Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.Air Force Office of Scientific Research (F49620-01-1-0397, F49620-01-1-0423); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624