Kari

We present preliminary results of applying a novel analysis method, Smoothed Particle Inference (SPI), to XMM-Newton observations of SNR RCW 103 and Tycho. SPI is a Bayesian modeling process that fits a population of gas blobs (“smoothed particles”) such that their superposed emission reproduces the observed spatial and spectral distribution of photons. Emission-weighted distributions of plasma properties, such as abundances and temperatures, are then extracted from the properties of the individual blobs. This technique has important advantages over analysis techniques which implicitly assume that remnants are two-dimensional objects in which each line of sight encompasses a single plasma. By contrast, SPI allows superposition of as many blobs of plasma as are needed to match the spectrum observed in each direction, without the need to bin the data spatially. The analyses of RCW 103 and Tycho are part of a pilot study for the larger SPIES (Smoothed Particle Inference Exploration of SNRs) project, in which SPI will be applied to a sample of 12 bright SNRs.