3,162 research outputs found

    Chandra observations of the HII complex G5.89-0.39 and TeV gamma-ray source HESSJ1800-240B

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    We present the results of our investigation, using a Chandra X-ray observation, into the stellar population of the massive star formation region G5.89-0.39, and its potential connection to the coincident TeV gamma-ray source HESSJ1800-240B. G5.89-0.39 comprises two separate HII regions G5.89-0.39A and G5.89-0.39B (an ultra-compact HII region). We identified 159 individual X-ray point sources in our observation using the source detection algorithm \texttt{wavdetect}. 35 X-ray sources are associated with the HII complex G5.89-0.39. The 35 X-ray sources represent an average unabsorbed luminosity (0.3-10\,keV) of 1030.5\sim10^{30.5}\,erg/s, typical of B7-B5 type stars. The potential ionising source of G5.89-0.39B known as Feldt's star is possibly identified in our observation with an unabsorbed X-ray luminosity suggestive of a B7-B5 star. The stacked energy spectra of these sources is well-fitted with a single thermal plasma APEC model with kT\sim5\,keV, and column density NH=2.6×1022_{\rm H}=2.6\times10^{22}\,cm2^{-2} (AV10_{\rm V}\sim 10). The residual (source-subtracted) X-ray emission towards G5.89-0.39A and B is about 30\% and 25\% larger than their respective stacked source luminosities. Assuming this residual emission is from unresolved stellar sources, the total B-type-equivalent stellar content in G5.89-0.39A and B would be 75 stars, consistent with an earlier estimate of the total stellar mass of hot stars in G5.89-0.39. We have also looked at the variability of the 35 X-ray sources in G5.89-0.39. Ten of these sources are flagged as being variable. Further studies are needed to determine the exact causes of the variability, however the variability could point towards pre-main sequence stars. Such a stellar population could provide sufficient kinetic energy to account for a part of the GeV to TeV gamma-ray emission in the source HESSJ1800-240B.Comment: 34 pages, 9 figure

    Using an artificial neural network to classify multicomponent emission lines with integral field spectroscopy from SAMI and S7

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    Integral field spectroscopy (IFS) surveys are changing how we study galaxies and are creating vastly more spectroscopic data available than before. The large number of resulting spectra makes visual inspection of emission line fits an infeasible option. Here, we present a demonstration of an artificial neural network (ANN) that determines the number of Gaussian components needed to describe the complex emission line velocity structures observed in galaxies after being fit with LZIFU. We apply our ANN to IFS data for the S7 survey, conducted using the Wide Field Spectrograph on the ANU 2.3 m Telescope, and the SAMI Galaxy Survey, conducted using the SAMI instrument on the 4 m Anglo-Australian Telescope. We use the spectral fitting code LZIFU (Ho et al. 2016a) to fit the emission line spectra of individual spaxels from S7 and SAMI data cubes with 1-, 2- and 3-Gaussian components. We demonstrate that using an ANN is comparable to astronomers performing the same visual inspection task of determining the best number of Gaussian components to describe the physical processes in galaxies. The advantage of our ANN is that it is capable of processing the spectra for thousands of galaxies in minutes, as compared to the years this task would take individual astronomers to complete by visual inspection

    Modeling Concept Combinations in a Quantum-theoretic Framework

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    We present modeling for conceptual combinations which uses the mathematical formalism of quantum theory. Our model faithfully describes a large amount of experimental data collected by different scholars on concept conjunctions and disjunctions. Furthermore, our approach sheds a new light on long standing drawbacks connected with vagueness, or fuzziness, of concepts, and puts forward a completely novel possible solution to the 'combination problem' in concept theory. Additionally, we introduce an explanation for the occurrence of quantum structures in the mechanisms and dynamics of concepts and, more generally, in cognitive and decision processes, according to which human thought is a well structured superposition of a 'logical thought' and a 'conceptual thought', and the latter usually prevails over the former, at variance with some widespread beliefsComment: 5 pages. arXiv admin note: substantial text overlap with arXiv:1311.605

    Model networks of end‐linked polydimethylsiloxane chains. II. Viscoelastic losses

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71107/2/JCPSA6-68-4-2010-1.pd
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