The next galactic Core Collapse Supernova (CCSN) may represent one of the most important events in modern astrophysics. The electromagnetic (EM) emission of the explosion is well understood, but we have no information about the inner mechanisms that cause it. Neutrinos (\nu) and gravitational waves (GWs) are the only messengers able to carry information about the inner working mechanisms of a CCSN. Neutrinos from supernova carry thermodynamic informations about the collapse, and GWs may reveal the dynamics involved in the collapse. Via coincident detection and joint analysis of \nu and GWs from the next nearby core collapse event, we will increase the knowledge of the astrophysics, neutrino physics, and nuclear physics involved in these sources. In this thesis work, we studied the detection efficiency and the misidentification of networks of \nu detectors to the same burst event, simulating the detectors background and injecting signals produced using for the emission a general description of an astrophysical burst of low-energy neutrinos with a characteristic temporal structure and quasi-thermal spectral shape. We provide a challenging method to better discriminate under threshold signals from experimental background. With respect to previous search strategies this method, without decreasing the detection efficiency, allows to knockingdown the misidentification probability by a factor of 7, in the worse case, within a distance of D \sim 20 kpc and, in the better case, this improvement can reach a factor \sim 20 till an horizon of \si 75 kpc. After the definition of the methodology to be used to construct the \nu network, we searched for coincident events between GW data (archival data from LIGO and Virgo taken before the upgrade to advanced detectors) and the correponding archival data. We analyzed the obtained results, giving confidence intervals for the observe coincident event.
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