Improving constraints on the neutrino mass using sufficient statistics
  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.
