Observability and diagnostics in the X-ray band of shock-cloud interactions in supernova remnants

Details Observability and diagnostics in the X-ray band of shock-cloud interactions in supernova remnants Observability and diagnostics in the X-ray band of shock-cloud interactions in supernova remnants

2010-01-13

arxiv.org/abs/1001.2240v1

Astronomy and Astrophysics

Astrophysics

High Energy Astrophysical Phenomena

9 pages, 7 Figures; accepted for publication on A&A. Version with full resolution images can be found at http://www.astropa.

Scientific paper

X-ray emitting features originating from the interaction of supernova shock waves with small interstellar gas clouds are revealed in many X-ray observations of evolved supernova remnants (e.g. Cygnus Loop and Vela), but their interpretation is not straightforward. We develop a self-consistent method for the analysis and interpretation of shock-cloud interactions in middle-aged supernova remnants, which can provide the key parameters of the system and the role of relevant physical effects like the thermal conduction, without the need to run ad-hoc numerical simulations and to bother of morphology details. We explore all the possible values of the shock speed and cloud density contrast relevant to middle-aged SNRs with a set of hydrodynamic simulations of shock-cloud interaction, including the effects of thermal conduction and radiative cooling. From the simulations, we synthesize spatially and spectrally resolved focal-plane data as they would be collected with XMM-Newton/EPIC, an X-ray instrument commonly used in these studies. We devise and tune up two diagnostic tools, the first based on the mean-photon energy vs. count rate scatter plot and the second on the spectral analysis of the interaction region, that can be used to highlight the effects of thermal conduction and to derive the shock speed in case of efficient conduction at work. These tools can be used to ascertain information from X-ray observations, without the need to develop detailed and ad-hoc numerical models for the interpretation of the data.

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