Vector Fields in a Rindler Space

In questo lavoro ci si propone di studiare la quantizzazione del campo vettoriale, massivo e non massivo, in uno spazio-tempo di Rindler, considerando in particolare i gauge di Feynman e assiale. Le equazioni del moto vengono risolte esplicitamente in entrambi i casi; sotto opportune condizioni, è stato inoltre possibile trovare una base completa e ortonormale di soluzioni delle equazioni di campo in termini di modi normali di Fulling. Si è poi analizzata la quantizzazione dei campi vettoriali espressi in questa base.

Climatological analysis of temperature and salinity fields in the Mediterranean sea

A climatological field is a mean gridded field that represents the monthly or seasonal trend of an ocean parameter. This instrument allows to understand the physical conditions and physical processes of the ocean water and their impact on the world climate. To construct a climatological field, it is necessary to perform a climatological analysis on an historical dataset. In this dissertation, we have constructed the temperature and salinity fields on the Mediterranean Sea using the SeaDataNet 2 dataset. The dataset contains about 140000 CTD, bottles, XBT and MBT profiles, covering the period from 1900 to 2013. The temperature and salinity climatological fields are produced by the DIVA software using a Variational Inverse Method and a Finite Element numerical technique to interpolate data on a regular grid. Our results are also compared with a previous version of climatological fields and the goodness of our climatologies is assessed, according to the goodness criteria suggested by Murphy (1993). Finally the temperature and salinity seasonal cycle for the Mediterranean Sea is described.

Radio relics and magnetic fields in galaxy clusters

Radio relics are diffuse synchrotron sources generally located in the peripheries of galaxy clusters in merging state. According to the current leading scenario, relics trace gigantic cosmological shock waves that cross the intra-cluster medium where particle acceleration occurs. The relic/shock connection is supported by several observational facts, including the spatial coincidence between relics and shocks found in the X-rays. Under the assumptions that particles are accelerated at the shock front and are subsequently deposited and then age downstream of the shock, Markevitch et al. (2005) proposed a method to constrain the magnetic field strength in radio relics. Measuring the thickness of radio relics at different frequencies allows to derive combined constraints on the velocity of the downstream flow and on the magnetic field, which in turns determines particle aging. We elaborate this idea to infer first constraints on magnetic fields in cluster outskirts. We consider three models of particle aging and develop a geometric model to take into account the contribution to the relic transverse size due to the projection of the shock-surface on the plane of the sky. We selected three well studied radio relics in the clusters A 521, CIZA J2242.8+5301 and 1RXS J0603.3+4214. These relics have been chosen primarily because they are almost seen edge-on and because the Mach number of the shock that is associated with these relics is measured by X-ray observations, thus allowing to break the degeneracy between magnetic field and downstream velocity in the method. For the first two clusters, our method is consistent with a pure radiative aging model allowing us to derive constraints on the relics magnetic field strength. In the case of 1RXS J0603.3+4214 we find that particle life-times are consistent with a pure radiative aging model under some conditions, however we also collect evidences for downstream particle re-acceleration in the relic W-region and for a magnetic field decaying downstream in its E-region. Our estimates of the magnetic field strength in the relics in A 521 and CIZA J2242.8+5301 provide unique information on the field properties in cluster outskirts. The constraints derived for these relics, together with the lower limits to the magnetic field that we derived from the lack of inverse Compton X-ray emission from the sources, have been combined with the constraints from Faraday rotation studies of the Coma cluster. Overall results suggest that the spatial profile of the magnetic field energy density is broader than that of the thermal gas, implying that the ε_th /ε_B ratio decreases with cluster radius. Alternatively, radio relics could trace dynamically active regions where the magnetic field strength is biased high with respect to the average value in the cluster volume.

Ricerca di AGN oscurati nei Chandra Deep Fields

La forma spettrale dell’X-ray background richiede l’esistenza di un grande numero di AGN mediamente oscurati, oltre alla presenza di AGN fortemente oscurati, la cui densità di colonna supera il limite Compton (Nh>10^24 cm^(-2)). A causa della loro natura, questi oggetti risultano di difficile osservazione, per cui è necessario adottare un approccio multi-banda per riuscire a rivelarli. In questo lavoro di tesi abbiamo studiato 29 sorgenti osservate nel CDF-S e 10 nel CDF-N a 0.0710^23, spettro piatto, riga del ferro): a seguito di questa analisi sono state individuate 9 sorgenti che presentano indicazioni di forte oscuramento. Dallo studio del rapporto tra la luminosità X (2-10 keV) e quella MIR (12.3um) dedotta dal SED-fitting, si è ottenuta una conferma della possibile presenza di forte oscuramento nelle 9 sorgenti selezionate a seguito dell’analisi spettrale. Abbiamo inoltre confrontato il tasso di formazione stellare dedotto dalla banda X (0.5-8 keV) e da quella IR (8-1000um) per identificare le sorgenti nelle quali l’emissione da AGN risulta essere dominante. A seguito di questa analisi abbiamo identificato 9 sorgenti (le stesse di cui sopra) con indicazione di forte oscuramento; di queste, 3 mostrano chiare indicazioni della presenza di un AGN Compton Thick (Nh>10^24 cm^(-2), riga del ferro intensa, basso rapporto LX/MIR).

Aggregate Programming in Scala: a Core Library and Actor-Based Platform for Distributed Computational Fields

La programmazione aggregata è un paradigma che supporta la programmazione di sistemi di dispositivi, adattativi ed eventualmente a larga scala, nel loro insieme -- come aggregati. L'approccio prevalente in questo contesto è basato sul field calculus, un calcolo formale che consente di definire programmi aggregati attraverso la composizione funzionale di campi computazionali, creando i presupposti per la specifica di pattern di auto-organizzazione robusti. La programmazione aggregata è attualmente supportata, in modo più o meno parziale e principalmente per la simulazione, da DSL dedicati (cf., Protelis), ma non esistono framework per linguaggi mainstream finalizzati allo sviluppo di applicazioni. Eppure, un simile supporto sarebbe auspicabile per ridurre tempi e sforzi d'adozione e per semplificare l'accesso al paradigma nella costruzione di sistemi reali, nonché per favorire la ricerca stessa nel campo. Il presente lavoro consiste nello sviluppo, a partire da un prototipo della semantica operazionale del field calculus, di un framework per la programmazione aggregata in Scala. La scelta di Scala come linguaggio host nasce da motivi tecnici e pratici. Scala è un linguaggio moderno, interoperabile con Java, che ben integra i paradigmi ad oggetti e funzionale, ha un sistema di tipi espressivo, e fornisce funzionalità avanzate per lo sviluppo di librerie e DSL. Inoltre, la possibilità di appoggiarsi, su Scala, ad un framework ad attori solido come Akka, costituisce un altro fattore trainante, data la necessità di colmare l'abstraction gap inerente allo sviluppo di un middleware distribuito. Nell'elaborato di tesi si presenta un framework che raggiunge il triplice obiettivo: la costruzione di una libreria Scala che realizza la semantica del field calculus in modo corretto e completo, la realizzazione di una piattaforma distribuita Akka-based su cui sviluppare applicazioni, e l'esposizione di un'API generale e flessibile in grado di supportare diversi scenari.

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

Estimation of the ephemerides and gravity fields of the Galilean moons through orbit determination of the JUICE mission

Jupiter and its moons are a complex dynamical system that include several phenomenon like tides interactions, moon's librations and resonances. One of the most interesting characteristics of the Jovian system is the presence of the Laplace resonance, where the orbital periods of Ganymede, Europa and Io maintain a 4:2:1 ratio respectively. It is interesting to study the role of the Laplace Resonance in the dynamic of the system, especially regarding the dissipative nature of the tidal interaction between Jupiter and its closest moon, Io. Numerous theories have been proposed regarding the orbital evolution of the Galilean satellites, but they disagree about the amount of dissipation of the system, therefore about the magnitude and the direction of the evolution of the system, mainly because of the lack of experimental data. The future JUICE space mission is a great opportunity to solve this dispute. JUICE is an ESA (European Space Agency) L-class mission (the largest category of missions in the ESA Cosmic Vision) that, at the beginning of 2030, will be inserted in the Jovian system and that will perform several flybys of the Galilean satellites, with the exception of Io. Subsequently, during the last part of the mission, it will orbit around Ganymede for nine months, with a possible extension of the mission. The data that JUICE will collect during the mission will have an exceptional accuracy, allowing to investigate several aspects of the dynamics the system, especially, the evolution of Laplace Resonance of the Galilean moons and its stability. This thesis will focus on the JUICE mission, in particular in the gravity estimation and orbit reconstruction of the Galilean satellites during the Jovian orbital phase using radiometric data. This is accomplished through an orbit determination technique called multi-arc approach, using the JPL's orbit determination software MONTE (Mission-analysis, Operations and Navigation Tool-kit Environment).

A next-to-leading order calculation of the impact of primordial magnetic fields into cosmological observables

In this thesis, we perform a next-to-leading order calculation of the impact of primordial magnetic fields (PMF) into the evolution of scalar cosmological perturbations and the cosmic microwave background (CMB) anisotropy. Magnetic fields are everywhere in the Universe at all scales probed so far, but their origin is still under debate. The current standard picture is that they originate from the amplification of initial seed fields, which could have been generated as PMFs in the early Universe. The most robust way to test their presence and constrain their features is to study how they impact on key cosmological observables, in particular the CMB anisotropies. The standard way to model a PMF is to consider its contribution (quadratic in the magnetic field) at the same footing of first order perturbations, under the assumptions of ideal magneto-hydrodynamics and compensated initial conditions. In the perspectives of ever increasing precision of CMB anisotropies measurements and of possible uncounted non-linear effects, in this thesis we study effects which go beyond the standard assumptions. We study the impact of PMFs on cosmological perturbations and CMB anisotropies with adiabatic initial conditions, the effect of Alfvén waves on the speed of sound of perturbations and possible non-linear behavior of baryon overdensity for PMFs with a blue spectral index, by modifying and improving the publicly available Einstein-Boltzmann code SONG, which has been written in order to take into account all second-order contributions in cosmological perturbation theory. One of the objectives of this thesis is to set the basis to verify by an independent fully numerical analysis the possibility to affect recombination and the Hubble constant.

Mitigating non-Lambertian surfaces issues in Stereo Matching with Neural Radiance Fields

Depth estimation from images has long been regarded as a preferable alternative compared to expensive and intrusive active sensors, such as LiDAR and ToF. The topic has attracted the attention of an increasingly wide audience thanks to the great amount of application domains, such as autonomous driving, robotic navigation and 3D reconstruction. Among the various techniques employed for depth estimation, stereo matching is one of the most widespread, owing to its robustness, speed and simplicity in setup. Recent developments has been aided by the abundance of annotated stereo images, which granted to deep learning the opportunity to thrive in a research area where deep networks can reach state-of-the-art sub-pixel precision in most cases. Despite the recent findings, stereo matching still begets many open challenges, two among them being finding pixel correspondences in presence of objects that exhibits a non-Lambertian behaviour and processing high-resolution images. Recently, a novel dataset named Booster, which contains high-resolution stereo pairs featuring a large collection of labeled non-Lambertian objects, has been released. The work shown that training state-of-the-art deep neural network on such data improves the generalization capabilities of these networks also in presence of non-Lambertian surfaces. Regardless being a further step to tackle the aforementioned challenge, Booster includes a rather small number of annotated images, and thus cannot satisfy the intensive training requirements of deep learning. This thesis work aims to investigate novel view synthesis techniques to augment the Booster dataset, with ultimate goal of improving stereo matching reliability in presence of high-resolution images that displays non-Lambertian surfaces.

The molecular gas content of star-forming galaxies in the ALPINE fields.

In this thesis, I aim to study the evolution with redshift of the gas mass fraction of a sample of 53 sources (from z ∼ 0.5 to z > 5) serendipitously detected in ALMA band 7 as part of the ALMA Large Program to INvestigate C II at Early Times (ALPINE). First, I used SED-fitting software CIGALE, which is able to implement energy balancing between the optical and the far infrared part, to produce a best-fit template of my sources and to have an estimate of some physical properties, such as the star formation rate (SFR), the total infrared luminosity and the total stellar mass. Then, using the tight correlation found by Scoville et al. (2014) between the ISM molecular gas mass and the rest-frame 850 μm luminosity, I used the latter, extrapolating it from the best-fit template using a code that I wrote in Python, as a tracer for the molecular gas. For my sample, I then derived the most important physical properties, such as molecular gas mass, gas mass fractions, specific star formation rate and depletion timescales, which allowed me to better categorize them and find them a place within the evolutionary history of the Universe. I also fitted our sources, via another code I wrote again in Python, with a general modified blackbody (MBB) model taken from the literature (Gilli et al. (2014), D’Amato et al. (2020)) to have a direct method of comparison with similar galaxies. What is evident at the end of the paper is that the methods used to derive the physical quantities of the sources are consistent with each other, and these in turn are in good agreement with what is found in the literature.

Neural Radiance Fields for Relighting and View Synthesis

Neural scene representation and neural rendering are new computer vision techniques that enable the reconstruction and implicit representation of real 3D scenes from a set of 2D captured images, by fitting a deep neural network. The trained network can then be used to render novel views of the scene. A recent work in this field, Neural Radiance Fields (NeRF), presented a state-of-the-art approach, which uses a simple Multilayer Perceptron (MLP) to generate photo-realistic RGB images of a scene from arbitrary viewpoints. However, NeRF does not model any light interaction with the fitted scene; therefore, despite producing compelling results for the view synthesis task, it does not provide a solution for relighting. In this work, we propose a new architecture to enable relighting capabilities in NeRF-based representations and we introduce a new real-world dataset to train and evaluate such a model. Our method demonstrates the ability to perform realistic rendering of novel views under arbitrary lighting conditions.