Fabio Fontanot

RESEARCH

My main research interest lies in the understanding of the complex network of physical processes responsible for the formation and redshift evolution of the various galaxy populations. I privilege a theoretical approach based on numerical techniques such as numerical simulations and semi-analytical models (SAMs), but I am also involved in observational efforts. In particular, the computational flexibility of SAMs allows for a comparison of their predictions over cosmological volumes, with a variety of observational constraints (mainly coming from multiwavelength surveys covering a wide range of the electromagnetic spectrum). A particular aspect of my research lies in the focus on the join evolution of Active Galactic Nuclei (AGNs) and their host galaxies, and it can be broadly divided into two main, strongly connected, approaches.

First, I am actively involved in the development of two state-of-the-art SAMs, i.e. MORGANA (Monaco, Fontanot & Taffoni, 2007) and GAEA (Hirschmann, De Lucia & Fontanot 2016), but I usually handle the predictions of a variety of such models (including De Lucia & Blaizot 2007; Wang et al., 2008; Somerville et al., 2008; Kang et al., 2008; Guo et al., 2011), as a result of a scientific web built up during my post-doctoral experiences. The comparison of the predictions of different models is nowadays a key asset for a deeper understanding of theoretical models, as it allows to highlight common trends, successes and failures among the different formulations for the key physical processes adopted by different approaches. Indeed, the quantitative comparison between predictions of different SAMs covers a relevant part of my scientific outcome (e.g. Kim et al., 2009; Maccio' et al., 2009; De Lucia et al. 2010; Henriquez et al., 2011). My main contribution concerns the study of the redshift evolution of stellar mass, star formation rate and black hole accretion in model galaxies, with detailed comparisons with the many evidences for the so-called "downsizing" trend of galaxy formation. In Fontanot et al. (2009b), I show, for the first time, that models of galaxy evolution have a common drawback in a too efficient formation of galaxies below the knee of the mass function, which leads to tensions in reproducing the evolution of the low-mass-end of the stellar mass function. Conversely, in Fontanot et al. 2011a, I point out that the different prescriptions of radio-mode AGN feedback currently implemented in several models of galaxy formation are not able to reproduce the distribution of galaxies into different activity classes (star forming, AGN and radio active). Both results stress the need for a revision in the modeling of the relevant physical processes in SAMs. I am currently involved in a number of international collaborations trying to characterize the effect of different prescriptions for the main physical processes on model predictions (Knebe et al., 2015). In particular, we focus on the study of cooling and merger rates (De Lucia et al., 2010, Monaco et al., 2014), of star formation and stellar feedback (Fontanot et al., 2013a), and on the description of the different theoretical channels of bulge formation, as a mean to understand the processes responsible for the morphological type of galaxies as a function of their stellar mass and environment (De Lucia et al., 2011; Fontanot et al., 2011b; De Lucia et al., 2012; Fontanot et al., 2015c).

As a natural complementary theme, the comparison of the photometric properties of galaxies, as predicted by theoretical models, with observational data provides the framework for constraining the main physical mechanisms responsible for galaxy evolution. I develop codes for interfacing spectrophotometric codes with SAMs predictions, generating synthetic spectra of model galaxies and evaluating their expected magnitudes/fluxes in different photometric systems. I build mock catalogues covering a large spectral range (from the UV to the Radio) and I develop algorithms to reproduce the properties of different surveys (both wide area and "light cones") and to predict number counts and luminosity functions (plus their redshift evolution) for different galaxy populations at different wavelengths. I typically compare synthetic photometry with multiwavelength surveys, with the aim of understanding the physical processes responsible for the joint evolution of AGNs and their host galaxies (using X-ray, optical and radio data), the assembly of different galaxy populations (using UV-to-optical bands and colors) and the redshift evolution of the obscured and unobscured star formation rate and black hole accretion (using optical-to-infrared fluxes). In particular, the focus on the joint evolution of AGNs and host galaxies led to interesting constraints on the interplay between AGN and stellar feedback, showing that the former is responsible to set the conditions for the triggering of a galactic wind (Monaco & Fontanot 2005). This model for AGN-triggered winds allow me to study the evolution of the AGN luminosity function (Fontanot et al., 2006), and, more recently, to propose a first physical explanation for the bended shape of the local Black Hole-Bulge relation (Fontanot, Monaco & Shankar 2015). Multiwavelength data have been relevant also in other projects, for example in Fontanot et al., (2007b), where I discuss the assembly of massive galaxies and, for the first time, show that SAMs are able to reproduce the number density of sub-millimeter galaxies using an universal stellar initial mass function, or in Fontanot & Monaco (2010), where I discuss the origin of the different galaxy populations which contributes to the Extremely Red Objects (ERO) selection, showing that there is no simple evolutionary sequence for the formation of z=0 massive galaxies, going through a sub-mm-bright phase and then an ERO phase, or, more recently, in Fontanot et al. (2016), where I discuss the impact of a variable (SFR dependent) stellar Initial Mass Function on the physical properties, chemical enrichment and mass assembly of model galaxies. These skills result of fundamental importance also for my contribution to a number of ongoing collaborations (see e.g., Pasquali et al., 2010; Skibba et al., 2010; Wilman et al, 2013; Fossati et al., 2015; Gruppioni et al., 2015). In the field of synthetic photometry, I am involved in the quantitative comparison between the predictions of radiative transfer codes (such as GRASIL) and analytical prescriptions for dust attenuation. The emphasis of my work is on the prediction of optical (Fontanot et al., 2009a) and infrared (Fontanot & Somerville 2011) fluxes and on their impact on statistical quantities like the luminosity functions. The results are of great interest to better understand and quantify the level of theoretical uncertainty connected with the modeling of dust absorption and re-emission. This has a huge impact for the interpretation of the evolution of the star formation history as inferred by data coming from current and future (SPICA) infrared missions. Moreover, I am currently working on the relative contribution of AGNs and galaxies to the cosmic Reionization of neutral hydrogen (Fontanot, Cristiani & Vanzella, 2012), using the observed cosmic ionizing background as a constrain to the Lyman continuum photon escape fraction of the sources responsible for reionization (Fontanot et al., 2014). Our work clearly favors a relevant contribution of both AGNs and galaxies to the total

My research experience is not limited to the theoretical modeling of galaxy evolution, but also includes observational programs. I joined the GOODS Team and I led a small research unit, aimed at the observational determination of the QSO luminosity function at 3.5 < z < 5.2 (Fontanot et al., 2007a). I gained experience in handling multicolour photometry of large observational datasets, in matching broad-band observations coming from different instruments, and in tailoring different colour selection criteria. I developed algorithms for cloning QSO colours, starting from low-redshift complete spectral samples. These synthetic colours were used to implement a Monte Carlo algorithm for the estimate of the QSO luminosity function, which takes into account the expected colour distribution, K-correction distribution, spectroscopic incompleteness, and selection function. I also collaborated to other projects, helping with the interpretation of multiwavelength data, using both semi-analytical and semi-empirical techniques (Fontana et al., 2006; Santini et al., 2009; Fontanot et al., 2012a). I joined the PanSTARRS Team, with the duty of defining the expected colours of z > 5 QSO in the proposed photometric system (Fontanot et al., 2007b). I am currently part of the EUCLID collaboration (Legacy Science Team and the Operational Unit - Level 3) and I also joined the Galaxy Evolution Working Group responsible for setting the scientific case for the proposed SPICA mission. In both cases, my contribution to the project is related to the development of theoretical tools to foresee the scientific achievements of the survey (thus including the development and testing of selection/luminosity/mass function algorithms and the comparison of foreseen data with the predictions of theoretical models of galaxy evolution). In particular, I have an ongoing program aimed at characterizing the impact of modified Dark Energy cosmologies to the predictions of galaxy formation models. This project involves the realization of a suite of N-body cosmological simulations relying on different Dark Energy cosmologies, the definition of merger trees for the evolution of the Large Scale Structure as traced by Dark Matter Haloes, and the implementation of consistent SAMs to follow the evolution of the baryonic content of haloes (Fontanot et al., 2013b, 2012c, 2015a, 2015b). This project has relevant implications for future missions like EUCLID, as it allows me to quantify the expected deviations from a concordance cosmological scenario of the statistical properties of large galaxy samples and to select the observational test best suited to discriminate between the different cosmological models. I am also involved in the VANDELS survey, aimed at obtaining a deep spectroscopic survey of high-redshift galaxies.