Computer Science – Learning
Scientific paper
Oct 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009xmm..prop..104t&link_type=abstract
XMM-Newton Proposal ID #06526901
Computer Science
Learning
Supernovae, Supernova Remnants, Diffuse (Galactic) Emission And Isolated Neutron Stars, Igr J17448-3232
Scientific paper
The study of young supernova remnants (SNRs) is important for understanding the particle acceleration that leads to cosmic ray production, for learning about supernova explosions, and for using energetic pulsars to constrain high energy emission mechanisms. IGR J17448-3232 is a SNR candidate that would be one of only three SNRs that have been discovered by the INTEGRAL satellite in the hard X-ray band. The evidence that the source is a SNR comes from short Chandra and Swift exposures. The evidence that it is young comes from its very hard X-ray spectrum and the presence of an X-ray point source that may be a pulsar. We propose for XMM observations to search for pulsations, and obtain a high statistics image and spectrum of the extended emission.
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