Abstract :
Study of Supernova Remnant (SNR) demographics and their physical properties (density, temperature, shock velocities) is very important in order to understand their role in galaxies. Many photometric and spectroscopic studies of SNRs, have been carried out in our Galaxy but also in extragalactic environments. The most common means for the SNR identification in the optical regime, is the use of the flux ratio of the [S II] (λλ6717, 6731) to Hα (λ6563) emission lines. However, this diagnostic is biased against low excitation SNRs. For this reason, we have developed new diagnostics that combine 2 and 3 emission line ratios along with a Support Vector Machine model, that efficiently differentiate SNRs from HII regions. These diagnostics recover up to 35% of the SNRs that we miss using the traditional diagnostic tool, which is very important in order to obtain more complete samples of SNRs (i.e. SNRs of different physical properties) and consequently to more efficiently explore the feedback processes to the host galaxy. We present the application of these diagnostics on Integral Field Unit (IFU) data of the galaxy NGC 7793. We identify new SNR populations, we construct the distributions of their physical properties and their luminosity functions. Finally, we explore possible correlations between properties of SNRs and those of their environment.
