Account
First Name | Sumit |
Last Name | Sarbadhicary |
Institution | Univerity of Pittsburgh |
Country | USA |
1st Abstract
Title (1st Abstract) | Statistical modelling of supernova remnant populations in the Local Group |
First Author | Sumit Sarbadhicary |
Affiliation | University of Pittsburgh |
Additional Authors | Carlos Badenes, Laura Chomiuk, Damiano Caprioli, Daniel Huizenga |
Presentation options | |
Session | 7. SNRs as probes and drivers of galaxy structure |
1st Abstract | Supernova remnants (SNRs) in the Local Group offer unique insights into the origin of different types of supernovae. However, the intrinsic diversity and environment-driven evolution of SNRs require the use of statistical methods to model SNR populations in the context of their host galaxy. We introduce a semi-analytic model for SNR radio light curves that uses the physics of shock propagation through the ISM, the resultant particle acceleration and the range of kinetic energies observed in supernovae. We use this model to reproduce the fundamental properties of observed SNR populations, taking into account the detection limits of radio surveys and the wealth of observational constraints on the stellar distribution and ISM structure of the host galaxy from radio, optical, and IR images. We can reproduce the observed radio luminosity function of SNRs in M33 with a SN rate of $(3.5 – 4.3) times 10^{-3}$ SN per year and an electron acceleration efficiency, $epsilon_{rm{e}} sim 0.01$.This is the first measurement of $epsilon_{rm{e}}$ using a large sample of SNRs. We show that dim Galactic SNRs like SN1006 would have been missed by archival radio surveys at the distance of M33, and we predict that most SNRs in M33 have radio visibility times of 20-80 kyrs that are correlated with the measured ISM column densities $N_H$: $t_{rm{vis}} propto N_H^a$ with $alpha = -0.36 pm 0.01$, whereas a small fraction of SNRs have visibility times< 10 kyrs that appear uncorrelated with column density. This observationally-anchored approach to the visibility time of SNRs will allow us to use SNR catalogs as 'SN surveys' to calculate SN rates and delay time distributions in the Local Group. |