5 research outputs found
Cosmic voids uncovered -- first-order statistics of depressions in the biased density field
Cosmic voids are the major volume component in the matter distribution of the
Universe. They posses great potential for constraining dark energy as well as
for testing theories of gravity. Nevertheless, in spite of their growing
popularity as cosmological probes, a gap of knowledge between cosmic void
observations and theory still persists. In particular, the void size function
models proposed in literature have been proven unsuccessful in reproducing the
results obtained from cosmological simulations in which cosmic voids are
detected from biased tracers of the density field, undermining the possibility
of using them as cosmological probes. The goal of this work is to cover this
gap. In particular, we make use of the findings of a previous work in which we
have improved the void selection procedure, presenting an algorithm that
redefines the void ridges and, consequently, their radius. By applying this
algorithm, we validate the volume conserving model of the void size function on
a set of unbiased simulated density field tracers. We highlight the difference
in the internal structure between voids selected in this way and those
identified by the popular VIDE void finder. We also extend the validation of
the model to the case of biased tracers. We find that a relation exists between
the tracer used to sample the underlying dark matter density field and its
unbiased counterpart. Moreover, we demonstrate that, as long as this relation
is accounted for, the size function is a viable approach for studying cosmology
with cosmic voids.Comment: 11 pages, 6 figures, 3 tables, submitted to MNRA
Cosmological exploitation of the size function of cosmic voids identified in the distribution of biased tracers
Cosmic voids are large underdense regions that, together with galaxy
clusters, filaments and walls, build up the large-scale structure of the
Universe. The void size function provides a powerful probe to test the
cosmological framework. However, to fully exploit this statistics, the void
sample has to be properly cleaned from spurious objects. Furthermore, the bias
of the mass tracers used to detect these regions has to be taken into account
in the size function model. In our work we test a cleaning algorithm and a new
void size function model on a set of simulated dark matter halo catalogues,
with different mass and redshift selections, to investigate the statistics of
voids identified in a biased mass density field. We then investigate how the
density field tracers' bias affects the detected size of voids. The main result
of this analysis is a new model of the size function, parameterised in terms of
the linear effective bias of the tracers used, which is straightforwardly
inferred from the large-scale two-point correlation function. This represents a
crucial step to exploit the method on real data catalogues. The proposed size
function model has been accurately calibrated on mock catalogues, and used to
validate the possibility to provide forecasts on the cosmological constraints,
namely on the matter density contrast, , and on the
normalisation of the linear matter power spectrum, , at different
redshifts.Comment: 17 pages, 11 figures, 4 tables, accepted by MNRA
Relazione di Storia del Console Tommaso Contarini letta in Senato l'11 decembre 1593
Pagination: 792-796Text Genre:Pros