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

Cosmic voids are large underdense regions of the Universe that, together with galaxy clusters, filaments and walls, characterise the large-scale structure of the Universe, the so-called cosmic web. Since voids in biased tracers are systematically larger than those identified in the dark matter field, a correction to the dark matter void size function is necessary. The scientific goals of this thesis work are the following: (i) to test the algorithm to clean void catalogues on Λ-cold dark matter (ΛCDM) N-body simulations, (ii) to quantify the accuracy of the theoretical void size function model with dark matter catalogues, (iii) to re-parametrise the theoretical model of the void size function for biased tracers, and (iv) to investigate the cosmological constraining power of cosmic void statistics. For these purposes, we made use of large, high-resolution halo catalogues extracted from ΛCDM N-body simulations. From these catalogues of biased tracers we extracted void catalogues with the Void IDentification and Examination toolkit (VIDE). Then a cleaning procedure is applied to the VIDE void catalogues. In our analyses we found that the theoretical void number density is systematically underpredicted if the effective bias is used to assess the density threshold in the model. We verified this phenomenon by estimating the bias from the ratio between the averaged void density profiles traced by dark matter and biased tracers. In particular, the bias computed with this technique is systematically larger than the linear effective bias of the tracers used to identify the voids. Thus, we used the former to re-parameterise the theoretical size function. Thanks to this new parameterisation, the theoretical void size function is now fully consistent with the result of numerical simulations. Finally, we investigate the effect of varying some of the cosmological parameters used to compute the theoretical void size function

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, $\Omega_{\rm M}$, 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

Cosmological constraints from the BOSS DR12 void size function

We present the first cosmological constraints derived from the analysis of the void size function. This work relies on the final BOSS DR12 data set, a large spectroscopic galaxy catalog, ideal for the identification of cosmic voids. We extract a sample of voids from the distribution of galaxies and we apply a cleaning procedure aimed at reaching high levels of purity and completeness. We model the void size function by means of an extension of the popular volume-conserving model, based on two additional nuisance parameters. Relying on mock catalogs specifically designed to reproduce the BOSS DR12 galaxy sample, we calibrate the extended size function model parameters and validate the methodology. We then apply a Bayesian analysis to constrain the $\Lambda$CDM model and one of its simplest extensions, featuring a constant dark energy equation of state parameter, $w$. Following a conservative approach, we put constraints on the total matter density parameter and the amplitude of density fluctuations, finding $\Omega_{\rm m}=0.29 \pm 0.06$ and $\sigma_8=0.79^{+0.09}_{-0.08}$. Testing the alternative scenario, we derive $w=-1.1\pm 0.2$, in agreement with the $\Lambda$CDM model. These results are independent and complementary to those derived from standard cosmological probes, opening up new ways to identify the origin of potential tensions in the current cosmological paradigm.Comment: 24 pages, 13 figures, 3 tables, accepted by Ap

Exploring the cosmological synergy between galaxy cluster and cosmic void number counts

Galaxy clusters and cosmic voids are the most extreme objects of our Universe in terms of mass and size, tracing two opposite sides of the large-scale matter density field. By studying their abundance as a function of their mass and radius, respectively, i.e. the halo mass function (HMF) and void size function (VSF), it is possible to achieve fundamental constraints on the cosmological model. While the HMF has already been extensively exploited providing robust constraints on the main cosmological model parameters (e.g. $\Omega_{\rm m}$, $\sigma_8$ and $S_8$), the VSF is still emerging as a viable and effective cosmological probe. Given the expected complementarity of these statistics, in this work we aim at estimating the costraining power deriving from their combination. To achieve this goal, we exploit realistic mock samples of galaxy clusters and voids extracted from state-of-the-art large hydrodynamical simulations, in the redshift range $0.2 \leq z \leq 1$. We perform an accurate calibration of the free parameters of the HMF and VSF models, needed to take into account the differences between the types of mass tracers used in this work and those considered in previous literature analyses. Then, we obtain constraints on $\Omega_{\rm m}$ and $\sigma_8$ by performing a Bayesian Markov Chain Monte Carlo analysis. We find that cluster and void counts represent powerful independent and complementary probes to test the cosmological framework. In particular, we found that the constraining power of the HMF on $\Omega_{\rm m}$ and $\sigma_8$ improves drastically with the VSF contribution, increasing the $S_8$ constraint precision by a factor of about $60\%$.Comment: 12 pages, 7 figures, submitted to MNRA

The role of immune suppression in COVID-19 hospitalization: clinical and epidemiological trends over three years of SARS-CoV-2 epidemic

Specific immune suppression types have been associated with a greater risk of severe COVID-19 disease and death. We analyzed data from patients >17 years that were hospitalized for COVID-19 at the “Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico” in Milan (Lombardy, Northern Italy). The study included 1727 SARS-CoV-2-positive patients (1,131 males, median age of 65 years) hospitalized between February 2020 and November 2022. Of these, 321 (18.6%, CI: 16.8–20.4%) had at least one condition defining immune suppression. Immune suppressed subjects were more likely to have other co-morbidities (80.4% vs. 69.8%, p < 0.001) and be vaccinated (37% vs. 12.7%, p < 0.001). We evaluated the contribution of immune suppression to hospitalization during the various stages of the epidemic and investigated whether immune suppression contributed to severe outcomes and death, also considering the vaccination status of the patients. The proportion of immune suppressed patients among all hospitalizations (initially stable at <20%) started to increase around December 2021, and remained high (30–50%). This change coincided with an increase in the proportions of older patients and patients with co-morbidities and with a decrease in the proportion of patients with severe outcomes. Vaccinated patients showed a lower proportion of severe outcomes; among non-vaccinated patients, severe outcomes were more common in immune suppressed individuals. Immune suppression was a significant predictor of severe outcomes, after adjusting for age, sex, co-morbidities, period of hospitalization, and vaccination status (OR: 1.64; 95% CI: 1.23–2.19), while vaccination was a protective factor (OR: 0.31; 95% IC: 0.20–0.47). However, after November 2021, differences in disease outcomes between vaccinated and non-vaccinated groups (for both immune suppressed and immune competent subjects) disappeared. Since December 2021, the spread of the less virulent Omicron variant and an overall higher level of induced and/or natural immunity likely contributed to the observed shift in hospitalized patient characteristics. Nonetheless, vaccination against SARS-CoV-2, likely in combination with naturally acquired immunity, effectively reduced severe outcomes in both immune competent (73.9% vs. 48.2%, p < 0.001) and immune suppressed (66.4% vs. 35.2%, p < 0.001) patients, confirming previous observations about the value of the vaccine in preventing serious disease

Emissione non termica in ammassi di galassie: analisi di radiosorgenti diffuse

Gli ammassi di galassie (galaxy clusters) sono aggregati di galassie legate dalla forza di attrazione gravitazionale. Essi sono le più grandi strutture virializzate dell’Universo e la loro luminosità è dovuta alle galassie che li compongono e al cosiddetto intracluster medium (ICM), gas intergalattico in grado di raggiungere temperature di milioni di gradi. L’ICM è caratterizzato da emissioni sia di tipo termico che non termico, rispettivamente nella banda X e nella banda Radio, dovute soprattutto al meccanismo di bremsstrahlung termica e all’emissione di sincrotrone. Lo studio delle radiazioni emesse da questo gas primordiale ha permesso di studiare alcuni processi caratteristici nella dinamica degli ammassi di galassie, come i fenomeni di merger e cooling flow , e di ottenere quindi una maggiore comprensione della formazione ed evoluzione degli ammassi. Essendo le più grandi strutture dell’Universo che abbiano raggiunto l’equilibrio viriale, il loro studio risulta infatti molto importante, in quanto fornisce un valido strumento per la formulazione di un Modello Cosmologico. Lo scopo di questo lavoro di tesi consiste in particolare nell'analisi di Aloni e Relitti radio, con maggiore approfondimento sui primi, e sulla ricerca di una correlazione della potenza Radio dei clusters sia con la loro luminosità nella banda X, che con la loro dimensione spaziale. La raccolta e l’elaborazione dei dati è stata svolta presso l’osservatorio di radioastronomia (ORA) situato nel CNR di Bologna

Towards a full cosmological exploitation of cosmic voids

A stately fraction of the Universe volume is dominated by almost empty space. Alongside the luminous filamentary structures that make it up, there are vast and smooth regions that have remained outside the Cosmology spotlight during the past decades: cosmic voids. Although essentially devoid of matter, voids enclose fundamental information about the cosmological framework and have gradually become an effective and competitive cosmological probe. In this Thesis work we present fundamental results about the cosmological exploitation of voids. We focused on the number density of voids as a function of their radius, known as void size function, developing an effective pipeline for its cosmological usage. We proposed a new parametrisation of the most used theoretical void size function to model voids identified in the distribution of biased tracers (i.e. dark matter haloes, galaxies and galaxy clusters), a step of fundamental importance to extend the analysis to real data surveys. We then applied our built methodology to study voids in alternative cosmological scenarios. Firstly we exploited voids with the aim of breaking the degeneracies between cosmological scenarios characterised by modified gravity and the inclusion of massive neutrinos. Secondly we analysed voids in the perspective of the Euclid survey, focusing on the void abundance constraining power on dynamical dark energy models with massive neutrinos. Moreover we explored other void statistics like void profiles and clustering (i.e. the void-galaxy and the void-void correlation), providing cosmological forecasts for the Euclid mission. We finally focused on the probe combination, highlighting the incredible potential of the joint analysis of multiple void statistics and of the combination of the void size function with different cosmological probes. Our results show the fundamental role of the void analysis in constraining the fundamental parameters of the cosmological model and pave the way for future studies on this topic