Redshift-space distortions of galaxies, clusters and AGN: testing how the accuracy of growth rate measurements depends on scales and sample selections

Redshift-space clustering anisotropies caused by cosmic peculiar velocities provide a powerful probe to test the gravity theory on large scales. However, to extract unbiased physical constraints, the clustering pattern has to be modelled accurately, taking into account the effects of non-linear dynamics at small scales, and properly describing the link between the selected cosmic tracers and the underlying dark matter field. We use a large hydrodynamic simulation to investigate how the systematic error on the linear growth rate, $f$, caused by model uncertainties, depends on sample selections and comoving scales. Specifically, we measure the redshift-space two-point correlation function of mock samples of galaxies, galaxy clusters and Active Galactic Nuclei, extracted from the Magneticum simulation, in the redshift range 0.2 < z < 2, and adopting different sample selections. We estimate $f\sigma_8$ by modelling both the monopole and the full two-dimensional anisotropic clustering, using the dispersion model. We find that the systematic error on $f\sigma_8$ depends significantly on the range of scales considered for the fit. If the latter is kept fixed, the error depends on both redshift and sample selection, due to the scale-dependent impact of non-linearities, if not properly modelled. On the other hand, we show that it is possible to get unbiased constraints on $f\sigma_8$ provided that the analysis is restricted to a proper range of scales, that depends non trivially on the properties of the sample. This can have a strong impact on multiple tracers analyses, and when combining catalogues selected at different redshifts.Comment: 17 pages, 14 figures. Accepted for publication in Astronomy & Astrophysic

Clustering of Clusters as a Cosmological Probe

Galaxy clusters play a leading role in both present and planned cosmological investigations. They represent the biggest collapsed structure of the Universe, sitting on top of the highest peaks of the dark matter density field. These objects are considered from long time as cosmological probes; the possibility to link their observed properties to the fundamental quantities of their host haloes, modelled as a function of cosmological parameters, is in fact very concrete. The advantage in using these objects for this kind of studies comes from a) the presence of multiple independent methods covering the whole spectrum to determine the total halo mass: this helps in understanding the systematics that affect different procedures and then provide a robust mass estimate; b) the less sophisticated modelling required to link the observations with cosmologically relevant quantities, as for these masses the baryon physics has only a marginal influence; the same cannot be exploited with e.g. galaxies, as the link between the total mass and observable quantities is much more influenced by baryon physics. These positive aspects apply also to the case of clustering of galaxy clusters. Moreover, clusters have a large clustering signal, due to the high bias and a very negligible contribution from non-linear redshift-space distortions caused by peculiar motions of objects in virialized haloes. All of these advantages counterbalance the larger measurement uncertainties due to the paucity of cluster sample with respect to galaxy clustering analyses. Moreover, the possibility to combine all the probes the galaxy clusters can provide gives us an unique instrument to address the fundamental puzzles in the present-day cosmology. In this Thesis we will exploit the clustering of an optically selected sample of galaxy clusters, focusing in particular on the two-point correlation function

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, $\Omega_{\rm M}$, and on the normalisation of the linear matter power spectrum, $\sigma_8$, at different redshifts.Comment: 17 pages, 11 figures, 4 tables, accepted by MNRA

Validating the methodology for constraining the linear growth rate from clustering anisotropies

Redshift-space clustering distortions provide one of the most powerful probes to test the gravity theory on the largest cosmological scales. We perform a systematic validation study of the state-of-the-art statistical methods currently used to constrain the linear growth rate from redshift-space distortions in the galaxy two-point correlation function. The numerical pipelines are tested on mock halo catalogues extracted from large N-body simulations of the standard cosmological framework. We consider both the monopole and quadrupole multipole moments of the redshift-space two-point correlation function, as well as the radial and transverse clustering wedges, in the comoving scale range $10<r[$\Mpch$]<55$. Moreover, we investigate the impact of redshift measurement errors on the growth rate and linear bias measurements due to the assumptions in the redshift-space distortion model. Considering both the dispersion model and two widely-used models based on perturbation theory, we find that the linear growth rate is underestimated by about $5-10\%$ at $z30$ \Mpch, the discrepancy is reduced below $5\%$. At higher redshifts, we find instead an overall good agreement between measurements and model predictions. Though this accuracy is good enough for clustering analyses in current redshift surveys, the models have to be further improved not to introduce significant systematics in RSD constraints from next generation galaxy surveys. The effect of redshift errors is degenerate with the one of small-scale random motions, and can be marginalised over in the statistical analysis, not introducing any statistically significant bias in the linear growth constraints, especially at $z\geq1$.Comment: 17 pages, 14 figures, 1 tabl

The XXL survey: XLVI. Forward cosmological analysis of the C1 cluster sample

We present the forward cosmological analysis of an $XMM$ selected sample of galaxy clusters out to a redshift of unity. Following our previous 2018 study based on the dn/dz quantity alone, we perform an upgraded cosmological analysis of the same XXL C1 cluster catalogue (178 objects), with a detailed account of the systematic errors. We follow the ASpiX methodology: the distribution of the observed X-ray properties of the cluster population is analysed in a 3D observable space (count rate, hardness ratio, redshift) and modelled as a function of cosmology. Compared to more traditional methods, ASpiX allows the inclusion of clusters down to a few tens of photons. We obtain an improvement by a factor of 2 compared to the previous analysis by letting the normalisation of the M-T relation and the evolution of the L-T relation free. Adding constraints from the XXL cluster 2-point correlation function and the BAO from various surveys decreases the uncertainties by 23 and 53 % respectively, and 62% when adding both. Switching to the scaling relations from the Subaru analysis, and letting free more parameters, our final constraints are $\sigma_8$ = $0.99^{+0.14}_{-0.23}$, $\Omega_m$ = 0.296 $\pm$ 0.034 ($S_8 = 0.98^{+0.11}_{-0.21}$) for the XXL sample alone. Finally, we combine XXL ASpiX, the XXL cluster 2-point correlation function and the BAO, with 11 free parameters, allowing for the cosmological dependence of the scaling relations in the fit. We find $\sigma_8$ = $0.793^{+0.063}_{-0.12}$, $\Omega_m$ = 0.364 $\pm$ 0.015 ($S_8 = 0.872^{+0.068}_{-0.12}$), but still compatible with Planck CMB at 2.2$\sigma$. The results obtained by the ASpiX method are promising; further improvement is expected from the final XXL cosmological analysis involving a cluster sample twice as large. Such a study paves the way for the analysis of the eROSITA and future Athena surveys.Comment: 20 pages, 10 figures, accepted for publication in A&A, A&A version has the unabridged abstrac

Clustering di ammassi di galassie con cataloghi otticamente selezionati

In questo lavoro di tesi si è studiato il clustering degli ammassi di galassie e la determinazione della posizione del picco BAO per ottenere vincoli sui parametri cosmologici. A tale scopo si è implementato un codice per la stima dell'errore tramite i metodi di jackknife e bootstrap. La misura del picco BAO confrontata con i modelli cosmologici, grazie all'errore stimato molto piccolo, è risultato in accordo con il modelli LambdaCDM, e permette di ottenere vincoli su alcuni parametri dei modelli cosmologici