A detection of a core-collapse supernova (CCSN) gravitational-wave (GW) signal with an Advanced LIGO and Virgo detector network may allow us to measure astrophysical parameters of the dying massive star. GWs are emitted from deep inside the core, and, as such, they are direct probes of the CCSN explosion mechanism. In this study, we show how we can determine the CCSN explosion mechanism from a GW supernova detection using a combination of principal component analysis and Bayesian model selection. We use simulations of GW signals from CCSN exploding via neutrino-driven convection and rapidly rotating core collapse. Previous studies have shown that the explosion mechanism can be determined using one LIGO detector and simulated Gaussian noise. As real GW detector noise is both nonstationary and non-Gaussian, we use real detector noise from a network of detectors with a sensitivity altered to match the advanced detectors design sensitivity. For the first time, we carry out a careful selection of the number of principal components to enhance our model selection capabilities. We show that with an advanced detector network we can determine if the CCSN explosion mechanism is driven by neutrino convection for sources in our Galaxy and rapidly-rotating core collapse for sources out to the Large Magellanic Cloud.
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