Robustness of the covariance matrix for galaxy clustering measurements

We present a study on the robustness of the covariance matrix estimation for galaxy clustering measurements depending on the cosmological parameters and galaxy bias. To this end, we have produced 9000 galaxy mock catalogues relying on the effective Zel'dovich approximation implemented in the Ezmock computer code, using different input cosmological models and bias parameters. The reference catalogue has also been produced with this code, making our study insensitive to the approximation, at least on a relative-qualitative level. Our findings indicate that the covariance matrix is insensitive to the input power spectrum (e.g. different as), as long as the two- and three-point galaxy clustering measurements agree with the given data. In fact, the covariance matrix shows a bias at small scales (r less than or similar to 40 h(-1) Mpc) when the chosen galaxy bias parameters yield three-point statistics, which is not compatible with the reference one within the error bars, even though the two-point statistics agree within 1 per cent. Nevertheless, the error becomes negligible at large scales, making the covariance matrix still reliable for data analysis using only measurements in that regime (e.g. measuring baryon acoustic oscillations). High precision in cosmological parameter estimation is expected for covariance matrices extracted from mock galaxy catalogues, which accurately take into account both the two- and three-point statistics. This is independent of whether this is achieved by using the right cosmology and galaxy bias (which are not a priori known) or just any combination of both fitting the net observed galaxy clustering.