Tracers of Large-Scale Structure
The cosmic web carries a wealth of information about the cosmological origin and evolution of our Universe. Galaxy redshift surveys aim at reconstructing its large-scale structure, providing powerful means to probe fundamental physics. However, galaxies are biased and stochastic tracers of the dominant dark matter distribution, limiting the attainable accuracy on this reconstruction. A second limitation arises due to cosmic variance, a consequence of the fact that only a finite patch of our Universe is observable.
On the basis of numerical N-body simulations I will present a technique to optimize the information content encoded in the statistics of biased tracers of the dark matter density field. In concert with a multi-tracer approach to evade the cosmic variance limit, an optimal weighting scheme that minimizes the stochasticity of galaxies is presented and applied to halo catalogs.
In the second part of my talk I will discuss the prospects of considering cosmic voids as tracers of large-scale structure. While clusters, filaments and walls have all entered different stages of nonlinear evolution during cosmic history, voids represent structures that are still close to linear and therefore more easily related to the initial conditions of the Universe.