Diffusive models and chaos indicators for non-linear betatron motion in circular hadron accelerators

Understanding the complex dynamics of beam-halo formation and evolution in circular particle accelerators is crucial for the design of current and future rings, particularly those utilizing superconducting magnets such as the CERN Large Hadron Collider (LHC), its luminosity upgrade HL-LHC, and the proposed Future Circular Hadron Collider (FCC-hh). A recent diffusive framework, which describes the evolution of the beam distribution by means of a Fokker-Planck equation, with diffusion coefficient derived from the Nekhoroshev theorem, has been proposed to describe the long-term behaviour of beam dynamics and particle losses. In this thesis, we discuss the theoretical foundations of this framework, and propose the implementation of an original measurement protocol based on collimator scans in view of measuring the Nekhoroshev-like diffusive coefficient by means of beam loss data. The available LHC collimator scan data, unfortunately collected without the proposed measurement protocol, have been successfully analysed using the proposed framework. This approach is also applied to datasets from detailed measurements of the impact on the beam losses of so-called long-range beam-beam compensators also at the LHC. Furthermore, dynamic indicators have been studied as a tool for exploring the phase-space properties of realistic accelerator lattices in single-particle tracking simulations. By first examining the classification performance of known and new indicators in detecting the chaotic character of initial conditions for a modulated Hénon map and then applying this knowledge to study the properties of realistic accelerator lattices, we tried to identify a connection between the presence of chaotic regions in the phase space and Nekhoroshev-like diffusive behaviour, providing new tools to the accelerator physics community.

Spectrum shaping and its application: spread-spectrum clock generator and circuits for ultra wide band

Electromagnetic spectrum can be identified as a resource for the designer, as well as for the manufacturer, from two complementary points of view: first, because it is a good in great demand by many different kind of applications; second, because despite its scarce availability, it may be advantageous to use more spectrum than necessary. This is the case of Spread-Spectrum Systems, those systems in which the transmitted signal is spread over a wide frequency band, much wider, in fact, than the minimum bandwidth required to transmit the information being sent. Part I of this dissertation deals with Spread-Spectrum Clock Generators (SSCG) aiming at reducing Electro Magnetic Interference (EMI) of clock signals in integrated circuits (IC) design. In particular, the modulation of the clock and the consequent spreading of its spectrum are obtained through a random modulating signal outputted by a chaotic map, i.e. a discrete-time dynamical system showing chaotic behavior. The advantages offered by this kind of modulation are highlighted. Three different prototypes of chaos-based SSCG are presented in all their aspects: design, simulation, and post-fabrication measurements. The third one, operating at a frequency equal to 3GHz, aims at being applied to Serial ATA, standard de facto for fast data transmission to and from Hard Disk Drives. The most extreme example of spread-spectrum signalling is the emerging ultra-wideband (UWB) technology, which proposes the use of large sections of the radio spectrum at low amplitudes to transmit high-bandwidth digital data. In part II of the dissertation, two UWB applications are presented, both dealing with the advantages as well as with the challenges of a wide-band system, namely: a chaos-based sequence generation method for reducing Multiple Access Interference (MAI) in Direct Sequence UWB Wireless-Sensor-Networks (WSNs), and design and simulations of a Low-Noise Amplifier (LNA) for impulse radio UWB. This latter topic was studied during a study-abroad period in collaboration with Delft University of Technology, Delft, Netherlands.

In nome della comunità. Analisi dei testi della sicurezza e del terrorismo

The focus of this dissertation is the relationship between the necessity for protection and the construction of cultural identities. In particular, by cultural identities I mean the representation and construction of communities: national communities, religious communities or local communities. By protection I mean the need for individuals and groups to be reassured about dangers and risks. From an anthropological point of view, the relationship between the need for protection and the formation and construction of collective identities is driven by the defensive function of culture. This was recognized explicitly by Claude Lévi-Strauss and Jurij Lotman. To explore the “protective hypothesis,” it was especially useful to compare the immunitarian paradigm, proposed by Roberto Esposito, with a semiotic approach to the problem. According to Esposito, immunity traces borders, dividing Community from what should be kept outside: the enemies, dangers and chaos, and, in general, whatever is perceived to be a threat to collective and individual life. I recognized two dimensions in the concept of immunity. The first is the logic dimension: every element of a system makes sense because of the network of differential relations in which it is inscribed; the second dimension is the social praxis of division and definition of who. We are (or what is inside the border), and who They are (or what is, and must be kept, outside the border). I tested my hypothesis by analyzing two subject areas in particular: first, the security practices in London after 9/11 and 7/7; and, second, the Spiritual Guide of 9/11 suicide bombers. In both cases, one observes the construction of two entities: We and They. The difference between the two cases is their “model of the world”: in the London case, one finds the political paradigms of security as Sovereignty, Governamentality and Biopolitics. In the Spiritual Guide, one observes a religious model of the Community of God confronting the Community of Evil. From a semiotic point view, the problem is the origin of respective values, the origin of respective moral universes, and the construction of authority. In both cases, I found that emotional dynamics are crucial in the process of forming collective identities and in the process of motivating the involved subjects: specifically, the role of fear and terror is the primary factor, and represents the principal focus of my research.

'A Distortion in the mirror of being': verso un modello liquido di personaggio. Da Nabokov alle sperimentazioni contemporanee in ambito slavo

La tesi mira a ridefinire lo statuto del personaggio nell’ambito del self-conscious novel postmoderno, alla luce delle più recenti tendenze narratologiche, con particolare riferimento all’unnatural narratology. Per poter presentare un modello scientificamente valido si è fatto ricorso alla comparazione della produzione letteraria di due macro-aree: quella britannica e quella slava (Russia - Unione Sovietica - e Polonia). Come figura di mediazione tra queste due culture si pone senza dubbio Vladimir V. Nabokov, cardine e personalità di spicco della ricerca. Tra le analisi testuali proposte sono stati presi in considerazione i seguenti autori: Julian Barnes, Vladimir Nabokov, Daniil Charms, Konstantin Vaginov, Andrej Bitov, Saša Sokolov, Bruno Schulz e Tadeusz Kantor.

Antipodal random sequences with prescribed second-order statistics: application to Compressive Sensing and UWB system based on DS-CDMA

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Model reduction of stochastic groundwater flow and transport processes

This work presents a comprehensive methodology for the reduction of analytical or numerical stochastic models characterized by uncertain input parameters or boundary conditions. The technique, based on the Polynomial Chaos Expansion (PCE) theory, represents a versatile solution to solve direct or inverse problems related to propagation of uncertainty. The potentiality of the methodology is assessed investigating different applicative contexts related to groundwater flow and transport scenarios, such as global sensitivity analysis, risk analysis and model calibration. This is achieved by implementing a numerical code, developed in the MATLAB environment, presented here in its main features and tested with literature examples. The procedure has been conceived under flexibility and efficiency criteria in order to ensure its adaptability to different fields of engineering; it has been applied to different case studies related to flow and transport in porous media. Each application is associated with innovative elements such as (i) new analytical formulations describing motion and displacement of non-Newtonian fluids in porous media, (ii) application of global sensitivity analysis to a high-complexity numerical model inspired by a real case of risk of radionuclide migration in the subsurface environment, and (iii) development of a novel sensitivity-based strategy for parameter calibration and experiment design in laboratory scale tracer transport.

"Filosofia dell'ineguaglianza" di Nikolaj Berdjaev

Il nostro lavoro è incentrato su Filosofia dell’ineguaglianza, acceso libello di filosofia sociale in forma epistolare, composto da Nikolaj Berdjaev all’inizio del 1918. Nelle quattordici veementi lettere che costituiscono l’opera, egli critica aspramente l’idea di eguaglianza sociale e metafisica propagandata dai rivoluzionari, schierandosi a favore dell’ineguaglianza gerarchica, da lui considerata l’unica garanzia della libertà e della statura teantropica dell’uomo. Abbiamo suddiviso la nostra indagine in tre parti: il primo capitolo è un’introduzione storico-filosofica al testo, in cui sono evidenziati i concetti fondamentali del pensiero del Nostro; nel secondo capitolo abbiamo messo in luce il legame tra lo “stile filosofico” di Berdjaev e la cultura religiosa a cui egli appartiene, riflettendo poi sui problemi traduttivi che ne derivano; in particolare ci siamo soffermati sull’aforisticità del suo pensiero e sullo spiccato afflato emotivo che pervade la sua esposizione. Infine, abbiamo incluso nel terzo capitolo la traduzione di quattro lettere (Sulla rivoluzione, Sui fondamenti ontologico-religiosi della socialità, Sullo Stato, Sul regno di Dio) e della postfazione aggiunta da Berdjaev a Berlino nel 1923, in occasione della pubblicazione del libro.

Dynamics of coastal aquifers: data-driven forecasting and risk analysis

This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

Dynamic food systems and climate-induced risks transmission for food and nutritional security

Agriculture market instability impedes achieving the global goal of sustainable and resilient food systems. Currently, the support to producers reaches the mammoth USD 540 billion a year and is projected to reach USD 1.8 trillion by 2030. This gigantic increase requires a repurposing agricultural support strategy (RASS), considering the market country-specific circumstances. These circumstances may vary with geographic locations, marketing structures, and product value chains. The fruit production system is crucial for health-conscious consumers and profit-oriented producers for food and nutritional security. Export is one of the main driving forces behind the expansion of the fruit sector, and during the year 2010-2018, trade significantly outpaced production increases. The previous literature states that irregular and unpredictable behaviour — Chaos — can arise from entirely rational economic decision-making within markets. Different markets' direct/indirect linkages through trade create trade hubs, and uncertainty may function as an avenue to transmit adverse shocks and increase vulnerability rather than contribute to resilience. Therefore, distinguishing Chaos into an endogenous and exogenous pattern of behaviour is cradled to formulate an effective RASS for resilient food systems and to understand global food crises. The present research is aimed at studying the market dynamics of three regional trade hubs, i.e., Brazil (South America), Italy (Europe), and Pakistan (Asia), each representing advanced to traditional value chains to control uncertainty (risks). The present research encompasses 1) a systematic review to highlight the research dynamism and identify grey-areas of research. Based on the findings, we have investigated the 2) nonlinear impacts of climate-induced price responsiveness in monopsony markets. Once we highlighted the importance of marketing structures/arrangements, 3) we developed a risk transmission framework to address the co-evolving impacts in complex dynamic interactions.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.