Powerful Tools for Dissecting Supernova Remnants Observed with Chandra

Astronomy and Astrophysics – Astronomy

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Scientific paper

We introduce powerful new methods to quantify X-ray morphology of supernova remnants observed with Chandra. We demonstrate application of three techniques -- a power-ratio method, two-point correlation, and wavelet-transform analysis -- to archival ACIS observations of twenty galactic SNRs of all types and a variety of ages to measure chemical segregation and mixing, distribution asymmetries, and local substructure. Detailed comparison between sources provides crucial insights regarding the nature of the explosion, the effects of heating and dense environments, and particle acceleration properties. For each remnant, we have created individual images of observed spectral features (emission lines, thermal and non-thermal emission). Using two-point correlation, we disentangle the thermal and non-thermal emitting regions, and we measure with great accuracy the sizes and locations of thermal and non-thermal clumps with wavelet-transform analysis. The non-thermal continuum is located predominantly around the rim of our sources, and it has great excess power at small scales compared to the thermal component. Application of our methods to radio data reveals how the size of non-thermal emitting regions changes as a function of photon energy, which provides crucial insight to understand the magnetic-field properties and particle acceleration mechanisms. We extract XMM-Newton spectra of the regions with and without line emission as identified by the wavelet-transform analysis. Detailed knowledge of the X-ray substructure enables much more precise ejecta mass estimates than any previous SNR studies, key to constraining the supernova explosion histories. Additionally, we map rigorously the temperature and ion intensity variation within each source. Using these methods, we distinguish whether asymmetric chemical distributions arise from inhomogeneous heating or from an anisotropic explosion. In brief, we present three mathematical techniques that are superbly suited for analysis of high-resolution X-ray images, and we show their use for probing many outstanding questions that are vital to advance SNR understanding.

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