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We study the clustering of Gravitational Wave (GW) merger events andSupernovae IA (SN), as cosmic tracers in Luminosity Distance Space. We modifythe publicly available CAMB code to numerically evaluate auto- and cross- powerspectra for the different sources, including Luminosity Distance Spacedistortion effects generated by peculiar velocities and lensing convergence. Weperform a multitracer Fisher analysis to forecast expected constraints oncosmological and GW bias coefficients, using outputs from hydrodinamical N-bodysimulations to determine the bias fiducial model and considering futureobservations from the Vera Rubin Observatory and Einstein Telescope (ET), bothsingle and in a 3 detector network configuration. We find that adding SN to theGW merger dataset considerably improves the forecast, mostly by breakingsignificant parameter degeneracies, with final constraints comparable to thoseobtainable from a Euclid-like survey. GW merger bias is forecasted to bedetectable with good significance even in the single ET case.

Clustering of Gravitational Wave and Supernovae events: a multitracer analysis in Luminosity Distance Space