Early-type galaxies as probes of galaxy formation and cosmology

The goal of this thesis is to analyze the possibility of using early-type galaxies to place evolutionary and cosmological constraints, by both disentangling what is the main driver of ETGs evolution between mass and environment, and developing a technique to constrain H(z) and the cosmological parameters studying the ETGs age-redshift relation. The (U-V) rest-frame color distribution is studied as a function of mass and environment for two sample of ETGs up to z=1, extracted from the zCOSMOS survey with a new selection criterion. The color distributions and the slopes of the color-mass and color-environment relations are studied, finding a strong dependence on mass and a minor dependence on environment. The spectral analysis performed on the D4000 and Hδ features gives results validating the previous analysis. The main driver of galaxy evolution is found to be the galaxy mass, the environment playing a subdominant but non negligible role. The age distribution of ETGs is also analyzed as a function of mass, providing strong evidences supporting a downsizing scenario. The possibility of setting cosmological constraints studying the age-redshift relation is studied, discussing the relative degeneracies and model dependencies. A new approach is developed, aiming to minimize the impact of systematics on the “cosmic chronometer” method. Analyzing theoretical models, it is demonstrated that the D4000 is a feature correlated almost linearly with age at fixed metallicity, depending only minorly on the models assumed or on the SFH chosen. The analysis of a SDSS sample of ETGs shows that it is possible to use the differential D4000 evolution of the galaxies to set constraints to cosmological parameters in an almost model-independent way. Values of the Hubble constant and of the dark energy EoS parameter are found, which are not only fully compatible, but also with a comparable error budget with the latest results.

Improvement of photon transport model by including coupled photon-electron transport and kernel refinement

The first part of this work deals with the inverse problem solution in the X-ray spectroscopy field. An original strategy to solve the inverse problem by using the maximum entropy principle is illustrated. It is built the code UMESTRAT, to apply the described strategy in a semiautomatic way. The application of UMESTRAT is shown with a computational example. The second part of this work deals with the improvement of the X-ray Boltzmann model, by studying two radiative interactions neglected in the current photon models. Firstly it is studied the characteristic line emission due to Compton ionization. It is developed a strategy that allows the evaluation of this contribution for the shells K, L and M of all elements with Z from 11 to 92. It is evaluated the single shell Compton/photoelectric ratio as a function of the primary photon energy. It is derived the energy values at which the Compton interaction becomes the prevailing process to produce ionization for the considered shells. Finally it is introduced a new kernel for the XRF from Compton ionization. In a second place it is characterized the bremsstrahlung radiative contribution due the secondary electrons. The bremsstrahlung radiation is characterized in terms of space, angle and energy, for all elements whit Z=1-92 in the energy range 1–150 keV by using the Monte Carlo code PENELOPE. It is demonstrated that bremsstrahlung radiative contribution can be well approximated with an isotropic point photon source. It is created a data library comprising the energetic distributions of bremsstrahlung. It is developed a new bremsstrahlung kernel which allows the introduction of this contribution in the modified Boltzmann equation. An example of application to the simulation of a synchrotron experiment is shown.

Model selection and the vectorial misspecification-resistant information criterion in multivariate time series

The thesis deals with the problem of Model Selection (MS) motivated by information and prediction theory, focusing on parametric time series (TS) models. The main contribution of the thesis is the extension to the multivariate case of the Misspecification-Resistant Information Criterion (MRIC), a criterion introduced recently that solves Akaike’s original research problem posed 50 years ago, which led to the definition of the AIC. The importance of MS is witnessed by the huge amount of literature devoted to it and published in scientific journals of many different disciplines. Despite such a widespread treatment, the contributions that adopt a mathematically rigorous approach are not so numerous and one of the aims of this project is to review and assess them. Chapter 2 discusses methodological aspects of MS from information theory. Information criteria (IC) for the i.i.d. setting are surveyed along with their asymptotic properties; and the cases of small samples, misspecification, further estimators. Chapter 3 surveys criteria for TS. IC and prediction criteria are considered for: univariate models (AR, ARMA) in the time and frequency domain, parametric multivariate (VARMA, VAR); nonparametric nonlinear (NAR); and high-dimensional models. The MRIC answers Akaike’s original question on efficient criteria, for possibly-misspecified (PM) univariate TS models in multi-step prediction with high-dimensional data and nonlinear models. Chapter 4 extends the MRIC to PM multivariate TS models for multi-step prediction introducing the Vectorial MRIC (VMRIC). We show that the VMRIC is asymptotically efficient by proving the decomposition of the MSPE matrix and the consistency of its Method-of-Moments Estimator (MoME), for Least Squares multi-step prediction with univariate regressor. Chapter 5 extends the VMRIC to the general multiple regressor case, by showing that the MSPE matrix decomposition holds, obtaining consistency for its MoME, and proving its efficiency. The chapter concludes with a digression on the conditions for PM VARX models.