100,537 research outputs found

    Chandra detection of extended X-ray emission from the recurrent nova RS Ophiuchi

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    Radio, infrared, and optical observations of the 2006 eruption of the symbiotic recurrent nova RS Ophiuchi (RS Oph) showed that the explosion produced non-spherical ejecta. Some of this ejected material was in the form of bipolar jets to the east and west of the central source. Here we describe Xray observations taken with the Chandra X-ray Observatory one and a half years after the beginning of the outburst that reveal narrow, extended structure with a position angle of approximately 300 degrees (east of north). Although the orientation of the extended feature in the X-ray image is consistent with the readout direction of the CCD detector, extensive testing suggests that the feature is not an artifact. Assuming it is not an instrumental effect, the extended X-ray structure shows hot plasma stretching more than 1,900 AU from the central binary (taking a distance of 1.6 kpc). The X-ray emission is elongated in the northwest direction - in line with the extended infrared emission and some minor features in the published radio image. It is less consistent with the orientation of the radio jets and the main bipolar optical structure. Most of the photons in the extended X-ray structure have energies of less than 0.8 keV. If the extended X-ray feature was produced when the nova explosion occurred, then its 1".2 length as of 2007 August implies that it expanded at an average rate of more than 2 mas/d, which corresponds to a flow speed of greater than 6,000 km/s (d/1.6 kpc) in the plane of the sky. This expansion rate is similar to the earliest measured expansion rates for the radio jets.Comment: accepted in Ap

    The Local Structure of Space-Variant Images

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    Local image structure is widely used in theories of both machine and biological vision. The form of the differential operators describing this structure for space-invariant images has been well documented (e.g. Koenderink, 1984). Although space-variant coordinates are universally used in mammalian visual systems, the form of the operators in the space-variant domain has received little attention. In this report we derive the form of the most common differential operators and surface characteristics in the space-variant domain and show examples of their use. The operators include the Laplacian, the gradient and the divergence, as well as the fundamental forms of the image treated as a surface. We illustrate the use of these results by deriving the space-variant form of corner detection and image enhancement algorithms. The latter is shown to have interesting properties in the complex log domain, implicitly encoding a variable grid-size integration of the underlying PDE, allowing rapid enhancement of large scale peripheral features while preserving high spatial frequencies in the fovea.Office of Naval Research (N00014-95-I-0409

    Real-Time Anisotropic Diffusion using Space-Variant Vision

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    Many computer and robot vision applications require multi-scale image analysis. Classically, this has been accomplished through the use of a linear scale-space, which is constructed by convolution of visual input with Gaussian kernels of varying size (scale). This has been shown to be equivalent to the solution of a linear diffusion equation on an infinite domain, as the Gaussian is the Green's function of such a system (Koenderink, 1984). Recently, much work has been focused on the use of a variable conductance function resulting in anisotropic diffusion described by a nonlinear partial differential equation (PDF). The use of anisotropic diffusion with a conductance coefficient which is a decreasing function of the gradient magnitude has been shown to enhance edges, while decreasing some types of noise (Perona and Malik, 1987). Unfortunately, the solution of the anisotropic diffusion equation requires the numerical integration of a nonlinear PDF which is a costly process when carried out on a fixed mesh such as a typical image. In this paper we show that the complex log transformation, variants of which are universally used in mammalian retino-cortical systems, allows the nonlinear diffusion equation to be integrated at exponentially enhanced rates due to the non-uniform mesh spacing inherent in the log domain. The enhanced integration rates, coupled with the intrinsic compression of the complex log transformation, yields a seed increase of between two and three orders of magnitude, providing a means of performing real-time image enhancement using anisotropic diffusion.Office of Naval Research (N00014-95-I-0409

    A Spectral Network Model of Pitch Perception

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    A model of pitch perception, called the Spatial Pitch Network or SPINET model, is developed and analyzed. The model neurally instantiates ideas front the spectral pitch modeling literature and joins them to basic neural network signal processing designs to simulate a broader range of perceptual pitch data than previous spectral models. The components of the model arc interpreted as peripheral mechanical and neural processing stages, which arc capable of being incorporated into a larger network architecture for separating multiple sound sources in the environment. The core of the new model transforms a spectral representation of an acoustic source into a spatial distribution of pitch strengths. The SPINET model uses a weighted "harmonic sieve" whereby the strength of activation of a given pitch depends upon a weighted sum of narrow regions around the harmonics of the nominal pitch value, and higher harmonics contribute less to a pitch than lower ones. Suitably chosen harmonic weighting functions enable computer simulations of pitch perception data involving mistuned components, shifted harmonics, and various types of continuous spectra including rippled noise. It is shown how the weighting functions produce the dominance region, how they lead to octave shifts of pitch in response to ambiguous stimuli, and how they lead to a pitch region in response to the octave-spaced Shepard tone complexes and Deutsch tritones without the use of attentional mechanisms to limit pitch choices. An on-center off-surround network in the model helps to produce noise suppression, partial masking and edge pitch. Finally, it is shown how peripheral filtering and short term energy measurements produce a model pitch estimate that is sensitive to certain component phase relationships.Air Force Office of Scientific Research (F49620-92-J-0225); American Society for Engineering Educatio

    Width of percolation transition in complex networks

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    It is known that the critical probability for the percolation transition is not a sharp threshold, actually it is a region of non-zero width Δpc\Delta p_c for systems of finite size. Here we present evidence that for complex networks Δpc∼pcl\Delta p_c \sim \frac{p_c}{l}, where l∼Nνoptl \sim N^{\nu_{opt}} is the average length of the percolation cluster, and NN is the number of nodes in the network. For Erd\H{o}s-R\'enyi (ER) graphs νopt=1/3\nu_{opt} = 1/3, while for scale-free (SF) networks with a degree distribution P(k)∼k−λP(k) \sim k^{-\lambda} and 3<λ<43<\lambda<4, νopt=(λ−3)/(λ−1)\nu_{opt} = (\lambda-3)/(\lambda-1). We show analytically and numerically that the \textit{survivability} S(p,l)S(p,l), which is the probability of a cluster to survive ll chemical shells at probability pp, behaves near criticality as S(p,l)=S(pc,l)⋅exp[(p−pc)l/pc]S(p,l) = S(p_c,l) \cdot exp[(p-p_c)l/p_c]. Thus for probabilities inside the region ∣p−pc∣<pc/l|p-p_c| < p_c/l the behavior of the system is indistinguishable from that of the critical point

    The signature of a double quantum-dot structure in the I-V characteristics of a complex system

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    We demonstrate that by carefully analyzing the temperature dependent characteristics of the I-V measurements for a given complex system it is possible to determine whether it is composed of a single, double or multiple quantum-dot structure. Our approach is based on the orthodox theory for a double-dot case and is capable of simulating I-V characteristics of systems with any resistance and capacitance values and for temperatures corresponding to thermal energies larger than the dot level spacing. We compare I-V characteristics of single-dot and double-dot systems and show that for a given measured I-V curve considering the possibility of a second dot is equivalent to decreasing the fit temperature. Thus, our method allows one to gain information about the structure of an experimental system based on an I-V measurement.Comment: 12 pages 7 figure
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