asca and xmm-newton observations of the galactic supernova remnant g311.5−0.3

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2017
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Ranked #8 of 10 articles by views in saner 2019 - proceedings of the 2019 ieee 26th international conference on software analysis, evolution, and reengineering

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Abstract
We present an analysis of X-ray observations made with ASCA and XMM-Newton of the Galactic supernova remnant (SNR) G311.5−0.3. Prior infrared and radio observations of this SNR have revealed a shell-like morphology at both wavelengths. The spectral index of the radio emission is consistent with synchrotron emission, while the infrared colors are consistent with emission from shocked molecular hydrogen. Also previous CO observations have indicated an interaction between G311.5−0.3 and an adjacent molecular cloud. Our previous analysis of the pointed ASCA observation made of this SNR detected X-ray emission from the source for the first time but lacked the sensitivity and the angular resolution to rigorously investigate its X-ray properties. We have analyzed an archival XMM-Newton observation that included G311.5−0.3 in the field of view: this is the first time that XMM-Newton data has been used to probe the X-ray properties of this SNR. The XMM-Newton observation confirms that the X-ray emission from G311.5−0.3 is centrally concentrated and supports the classification of this source as a mixed-morphology SNR. In addition, our joint fitting of extracted ASCA and XMM-Newton spectra favor a thermal origin for the X-ray emission over a non-thermal origin. The spectral fitting parameters for our TBABS×APEC fit to the extracted spectra are NH = 4.63+1.87 −0.85×1022 cm −2 and kT = 0.68+0.20−0.24 keV. From these fit parameters, we derive the following values for physical parameters of the SNR: ne = 0.20 cm −3, np = 0.17 cm −3, MX = 21.4 M· and P/k = 3.18×106 K cm −3.
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t.g.2017serbianasca Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Pannuti T.G.;Filipović M.D.;Luken K.;Wong G.F.;Manojlović P.;Maxted N.;Roper Q.
Journal saner 2019 - proceedings of the 2019 ieee 26th international conference on software analysis, evolution, and reengineering
Year 2017
DOI
10.2298/SAJ1795023P
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