Cosmological exploitation of the size function of cosmic voids identified in the distribution of biased tracers

Abstract

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 method is a crucial step in exploiting real surveys. The proposed size function model has been accurately calibrated on halo catalogues, and used to validate the possibility to provide forecasts on the cosmological constraints, namely on the matter density contrast, Ω M , and on the normalisation of the linear matter power spectrum, σ 8 , at different redshifts.

Euclid: Forecasts from redshift-space distortions and the Alcock–Paczynski test with cosmic voids

“…Based on simulation studies, it has been demonstrated that a linear relation of the form ξ(r) = bδ(r) with a proportionality constant b serves that purpose with sufficiently high accuracy. Moreover, it has been shown that the value of b is linearly related to the large-scale linear galaxy bias of the tracer distribution, and coincides with it for sufficiently large voids (Sutter et al 2014c;Pollina et al 2017Pollina et al , 2019Contarini et al 2019;Ronconi et al 2019). With this, Eq.…”

Dark Energy Survey year 1 results: the relationship between mass and light around cosmic voids

“…Understanding the tracer bias around voids is crucial for many other cosmological tests involving voids, for example when modeling their abundance (Jennings et al 2013;Chan et al 2014;Pisani et al 2015;Achitouv et al 2015;Ronconi & Marulli 2017;Ronconi et al 2019;Contarini et al 2019;Verza et al 2019), or RSDs (Hamaus et al 2015(Hamaus et al , 2016(Hamaus et al , 2017Cai et al 2016;Chuang et al 2017;Achitouv et al 2017;Hawken et al 2017;Achitouv 2019;Correa et al 2019). Thanks to the state-of-the-art DES Year 1 (Y1) shear catalogue (Zuntz et al 2018), we have access to the lensing signal by both 2D and 3D voids with unprecedented accuracy.…”

Redshift-space effects in voids and their impact on cosmological tests. Part I: the void size function

“…Two of the most important cosmological statistics in void studies are the void size function, that describes the abundance of voids (Sheth & van de Weygaert 2004;Furlanetto & Piran 2006;Jennings et al 2013;Achitouv et al 2015;Pisani et al 2015;Ronconi & Marulli 2017;Contarini et al 2019;Ronconi et al 2019;Verza et al 2019), and the void-galaxy cross-correlation function, that characterises the density and peculiar velocity fields around them (Paz et al 2013;Hamaus et al 2015;Cai et al 2016;Hamaus et al 2016;Achitouv 2017;Achitouv et al 2017;Chuang et al 2017;Hamaus et al 2017;Hawken et al 2017;Achitouv 2019;Nadathur & Percival 2019;Nadathur et al 2019a,b;Hawken et al 2020;Hamaus et al 2020;Nadathur et al 2020;Paillas et al 2021). Both statistics are affected by distortions in the observed spatial distribution of the galaxies, which translate into anisotropic patterns.…”