Cosmology with zero bias tracers of the Large Scale Structure (LSS)

​The clustering of the LSS is of the most promising way of extracting cosmological information about dark energy, massive neutrinos, inflationary physics etc...
On small scales the analysis is limited by the poor knowledge of non linearity and galaxy biasing, whereas on large scales by the small number of modes availabe, i.e. by cosmic variance.
In this talk I will discuss a new approach where the sampling variance is minimized by canceling the clustering signal itself. I will present simple analytical calculations showing how unclustered tracers can be selected using environmental properties of halos and galaxies.
I'll then show results from N-body simulations we used to validate our method. Finally I will discuss applications to measurements of the growth rate using redshift space distortions at low redshift and measurements of Primordial non-Gaussianities at high redshift.