Improving constraints on the neutrino mass using sufficient statistics

Abstract

We use the "Dark Energy and Massive Neutrino Universe" (DEMNUni) simulations to compare the constraining power of "sufficient statistics" with the standard matter power spectrum on the sum of neutrino masses, $M_\nu \equiv \sum m_\nu$. In general, the power spectrum, even supplemented with higher moments of the distribution, captures only a fraction of the available cosmological information due to correlations between the Fourier modes. In contrast, the non-linear transform of sufficient statistics, approximated by a logarithmic mapping A=ln(1+\delta), was designed to capture all the available cosmological information contained in the matter clustering; in this sense it is an optimal observable. Our analysis takes advantage of the recent analytical model developed by Carron et al. 2014 to estimate both the matter power spectrum and the A-power spectrum covariance matrices. Using a Fisher information approach, we find that using sufficient statistics increases up to 8 times the available information on the total neutrino mass at z=0, thus tightening the constraints by almost a factor of 3 compared to the matter power spectrum.