5,269 research outputs found

    A pan-chromatic view of the galaxy cluster XMMU J1230.3+1339 at z=0.975 - Observing the assembly of a massive system

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    We present a comprehensive galaxy cluster study of XMMU J1230.3+1339 based on a joint analysis of X-ray data, optical imaging and spectroscopy observations, weak lensing results, and radio properties for achieving a detailed multi-component view of this newly discovered system at z=0.975. We find an optically very rich and massive system with M200≃\simeq(4.2±\pm0.8)×\times10^14 M\sun, Tx≃\simeq5.3(+0.7--0.6)keV, and Lx≃\simeq(6.5±\pm0.7)×\times10^44 erg/s, for which various widely used mass proxies are measured and compared. We have identified multiple cluster-related components including a central fly-through group close to core passage with associated marginally extended 1.4GHz radio emission possibly originating from the turbulent wake region of the merging event. On the cluster outskirts we see evidence for an on-axis infalling group with a second Brightest Cluster Galaxy (BCG) and indications for an additional off-axis group accretion event. We trace two galaxy filaments beyond the nominal cluster radius and provide a tentative reconstruction of the 3D-accretion geometry of the system. In terms of total mass, ICM structure, optical richness, and the presence of two dominant BCG-type galaxies, the newly confirmed cluster XMMU J1230.3+1339 is likely the progenitor of a system very similar to the local Coma cluster, differing by 7.6 Gyr of structure evolution.Comment: 26 pages, 14 color figures, accepted for publication in A&

    Shape: A 3D Modeling Tool for Astrophysics

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    We present a flexible interactive 3D morpho-kinematical modeling application for astrophysics. Compared to other systems, our application reduces the restrictions on the physical assumptions, data type and amount that is required for a reconstruction of an object's morphology. It is one of the first publicly available tools to apply interactive graphics to astrophysical modeling. The tool allows astrophysicists to provide a-priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation. The tool has already been successfully used in a number of astrophysical research projects.Comment: 13 pages, 11 figures, accepted for publication in the "IEEE Transactions on Visualization and Computer Graphics

    The Cosmic Evolution Survey (COSMOS): a large-scale structure at z=0.73 and the relation of galaxy morphologies to local environment

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    We have identified a large-scale structure at z~0.73 in the COSMOS field, coherently described by the distribution of galaxy photometric redshifts, an ACS weak-lensing convergence map and the distribution of extended X-ray sources in a mosaic of XMM observations. The main peak seen in these maps corresponds to a rich cluster with Tx= 3.51+0.60/-0.46 keV and Lx=(1.56+/-0.04) x 10^{44} erg/s ([0.1-2.4] keV band). We estimate an X-ray mass within r500r500 corresponding to M500~1.6 x 10^{14} Msun and a total lensing mass (extrapolated by fitting a NFW profile) M(NFW)=(6+/-3) x 10^15 Msun. We use an automated morphological classification of all galaxies brighter than I_AB=24 over the structure area to measure the fraction of early-type objects as a function of local projected density Sigma_10, based on photometric redshifts derived from ground-based deep multi-band photometry. We recover a robust morphology-density relation at this redshift, indicating, for comparable local densities, a smaller fraction of early-type galaxies than today. Interestingly, this difference is less strong at the highest densities and becomes more severe in intermediate environments. We also find, however, local "inversions'' of the observed global relation, possibly driven by the large-scale environment. In particular, we find direct correspondence of a large concentration of disk galaxies to (the colder side of) a possible shock region detected in the X-ray temperature map and surface brightness distribution of the dominant cluster. We interpret this as potential evidence of shock-induced star formation in existing galaxy disks, during the ongoing merger between two sub-clusters.Comment: 15 pages (emulateapj style), 16 figs (low res.); to appear in the ApJ Supplement COSMOS Special Issue. Low-resolution figures; full resolution version available at: http://www.astro.caltech.edu/~cosmos/publications/files/guzzo_0701482.pd

    Full waveform LiDAR for adverse weather conditions

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    Exploring Motion Signatures for Vision-Based Tracking, Recognition and Navigation

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    As cameras become more and more popular in intelligent systems, algorithms and systems for understanding video data become more and more important. There is a broad range of applications, including object detection, tracking, scene understanding, and robot navigation. Besides the stationary information, video data contains rich motion information of the environment. Biological visual systems, like human and animal eyes, are very sensitive to the motion information. This inspires active research on vision-based motion analysis in recent years. The main focus of motion analysis has been on low level motion representations of pixels and image regions. However, the motion signatures can benefit a broader range of applications if further in-depth analysis techniques are developed. In this dissertation, we mainly discuss how to exploit motion signatures to solve problems in two applications: object recognition and robot navigation. First, we use bird species recognition as the application to explore motion signatures for object recognition. We begin with study of the periodic wingbeat motion of flying birds. To analyze the wing motion of a flying bird, we establish kinematics models for bird wings, and obtain wingbeat periodicity in image frames after the perspective projection. Time series of salient extremities on bird images are extracted, and the wingbeat frequency is acquired for species classification. Physical experiments show that the frequency based recognition method is robust to segmentation errors and measurement lost up to 30%. In addition to the wing motion, the body motion of the bird is also analyzed to extract the flying velocity in 3D space. An interacting multi-model approach is then designed to capture the combined object motion patterns and different environment conditions. The proposed systems and algorithms are tested in physical experiments, and the results show a false positive rate of around 20% with a low false negative rate close to zero. Second, we explore motion signatures for vision-based vehicle navigation. We discover that motion vectors (MVs) encoded in Moving Picture Experts Group (MPEG) videos provide rich information of the motion in the environment, which can be used to reconstruct the vehicle ego-motion and the structure of the scene. However, MVs suffer from high noise level. To handle the challenge, an error propagation model for MVs is first proposed. Several steps, including MV merging, plane-at-infinity elimination, and planar region extraction, are designed to further reduce noises. The extracted planes are used as landmarks in an extended Kalman filter (EKF) for simultaneous localization and mapping. Results show that the algorithm performs localization and plane mapping with a relative trajectory error below 5:1%. Exploiting the fact that MVs encodes both environment information and moving obstacles, we further propose to track moving objects at the same time of localization and mapping. This enables the two critical navigation functionalities, localization and obstacle avoidance, to be performed in a single framework. MVs are labeled as stationary or moving according to their consistency to geometric constraints. Therefore, the extracted planes are separated into moving objects and the stationary scene. Multiple EKFs are used to track the static scene and the moving objects simultaneously. In physical experiments, we show a detection rate of moving objects at 96:6% and a mean absolute localization error below 3:5 meters

    HYPERSPECTRAL LINE-SCANNING MICROSCOPY FOR HIGH-SPEED MULTICOLOR QUANTUM DOT TRACKING

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    One of the challenges in studying protein interactions in live cells lies in the capacity to obtain both spatial and temporal information that is sufficient to extend existing knowledge of the dynamics and interactions, especially when tracking proteins at high density. Here we introduce a high-speed laser line-scanning hyperspectral microscope that is designed to track quantum dot labeled proteins at 27 frames/sec over an area of 28 um2 using 128 spectral channels spanning the range from 500 to 750 nm. This instrument simultaneously excites 8 species of quantum dots and employs a custom prism spectrometer and high speed EMCCD to obtain spectral information that is then used to distinguish and track individual probes at high density. These emitters are localized to within 10s of nm in each frame and reconstructed trajectories yield information of the protein dynamics and interactions. This manuscript describes the design, implementation, characterization, and application of a high-speed laser line-scanning hyperspectral microscope (HSM). The intended primary application is that of investigating the dynamics of transmembrane antibody receptors using quantum dot labeled immunoglobulin E (QD-IgE). Several additional examples demonstrate other advantages and applications of this method, including 3D hyperspectral imaging of live cells and hyperspectral superresolution imaging

    Spatially-Dense, Multi-Spectral, Frequency-Domain Diffuse Optical Tomography of Breast Cancer

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    Diffuse optical tomography (DOT) employs near-infrared light to image the concentration of chromophores and cell organelles in tissue and thereby providing access to functional parameters that can differentiate cancerous from normal tissues. This thesis describes research at the bench and in the clinic that explores and identifies the potential of DOT breast cancer imaging. The bench and clinic instrumentation differ but share important features: they utilize a very large, spatially dense, set of source-detector pairs (10E7) for imaging in the parallel-plate geometry. The bench experiments explored three-dimensional (3D) image resolution and fidelity as a function of numerous parameters and also ascertained the effects of a chest wall phantom. The chest wall is always present but is typically ignored in breast DOT. My experiments clarified chest wall influences and developed schemes to mitigate these effects. Mostly, these schemes involved selective data exclusion, but their efficacy also depended on reconstruction approach. Reconstruction algorithms based on analytic (fast) Fourier inversion and linear algebraic techniques were explored. The clinical experiments centered around a DOT instrument that I designed, constructed, and have begun to test (in-vitro and in-vivo). This instrumentation offers many features new to the field. Specifically, the imager employs spatially-dense, multi-spectral, frequency-domain data; it possesses the world\u27s largest optical source-detector density yet reported, facilitated by highly-parallel CCD-based frequency-domain imaging based on gain-modulation heterodyne detection. The instrument thus measures both phase and amplitude of the diffusive light waves. Other features include both frontal and sagittal breast imaging capabilities, ancillary cameras for measurement of breast boundary profiles, real-time data normalization, and mechanical improvements for patient comfort. The instrument design and construction is my most significant contribution, but first imaging experiments with tissue phantoms and of cancer bearing breasts were also carried out. A parallel effort with simulated data has yielded important information about new reconstruction regularization issues that arise when phase and amplitude are measured. With these gains in device implementation and DOT reconstruction, my research takes valuable steps towards bringing this novel imaging technique closer to clinical utilization

    Ultrashort filaments of light in weakly-ionized, optically-transparent media

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    Modern laser sources nowadays deliver ultrashort light pulses reaching few cycles in duration, high energies beyond the Joule level and peak powers exceeding several terawatt (TW). When such pulses propagate through optically-transparent media, they first self-focus in space and grow in intensity, until they generate a tenuous plasma by photo-ionization. For free electron densities and beam intensities below their breakdown limits, these pulses evolve as self-guided objects, resulting from successive equilibria between the Kerr focusing process, the chromatic dispersion of the medium, and the defocusing action of the electron plasma. Discovered one decade ago, this self-channeling mechanism reveals a new physics, widely extending the frontiers of nonlinear optics. Implications include long-distance propagation of TW beams in the atmosphere, supercontinuum emission, pulse shortening as well as high-order harmonic generation. This review presents the landmarks of the 10-odd-year progress in this field. Particular emphasis is laid to the theoretical modeling of the propagation equations, whose physical ingredients are discussed from numerical simulations. Differences between femtosecond pulses propagating in gaseous or condensed materials are underlined. Attention is also paid to the multifilamentation instability of broad, powerful beams, breaking up the energy distribution into small-scale cells along the optical path. The robustness of the resulting filaments in adverse weathers, their large conical emission exploited for multipollutant remote sensing, nonlinear spectroscopy, and the possibility to guide electric discharges in air are finally addressed on the basis of experimental results.Comment: 50 pages, 38 figure
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