A deep learning model via thermodynamics and condensed matter physics

Deep Learning architectures give brilliant results in a large variety of fields, but a comprehensive theoretical description of their inner functioning is still lacking. In this work, we try to understand the behavior of neural networks by modelling in the frameworks of Thermodynamics and Condensed Matter Physics. We approach neural networks as in a real laboratory and we measure the frequency spectrum and the entropy of the weights of the trained model. The stochasticity of the training occupies a central role in the dynamics of the weights and makes it difficult to assimilate neural networks to simple physical systems. However, the analogy with Thermodynamics and the introduction of a well defined temperature leads us to an interesting result: if we eliminate from a CNN the "hottest" filters, the performance of the model remains the same, whereas, if we eliminate the "coldest" ones, the performance gets drastically worst. This result could be exploited in the realization of a training loop which eliminates the filters that do not contribute to loss reduction. In this way, the computational cost of the training will be lightened and more importantly this would be done by following a physical model. In any case, beside important practical applications, our analysis proves that a new and improved modeling of Deep Learning systems can pave the way to new and more efficient algorithms.

Ab-initio determination of x-ray absorption near edge structure (xanes) spectra in an ultrasoft and norm conserving pseudopotentials scheme

X-ray absorption spectroscopy (XAS) is a powerful means of investigation of structural and electronic properties in condensed -matter physics. Analysis of the near edge part of the XAS spectrum, the so – called X-ray Absorption Near Edge Structure (XANES), can typically provide the following information on the photoexcited atom: - Oxidation state and coordination environment. - Speciation of transition metal compounds. - Conduction band DOS projected on the excited atomic species (PDOS). Analysis of XANES spectra is greatly aided by simulations; in the most common scheme the multiple scattering framework is used with the muffin tin approximation for the scattering potential and the spectral simulation is based on a hypothetical, reference structure. This approach has the advantage of requiring relatively little computing power but in many cases the assumed structure is quite different from the actual system measured and the muffin tin approximation is not adequate for low symmetry structures or highly directional bonds. It is therefore very interesting and justified to develop alternative methods. In one approach, the spectral simulation is based on atomic coordinates obtained from a DFT (Density Functional Theory) optimized structure. In another approach, which is the object of this thesis, the XANES spectrum is calculated directly based on an ab – initio DFT calculation of the atomic and electronic structure. This method takes full advantage of the real many-electron final wavefunction that can be computed with DFT algorithms that include a core-hole in the absorbing atom to compute the final cross section. To calculate the many-electron final wavefunction the Projector Augmented Wave method (PAW) is used. In this scheme, the absorption cross section is written in function of several contributions as the many-electrons function of the finale state; it is calculated starting from pseudo-wavefunction and performing a reconstruction of the real-wavefunction by using a transform operator which contains some parameters, called partial waves and projector waves. The aim of my thesis is to apply and test the PAW methodology to the calculation of the XANES cross section. I have focused on iron and silicon structures and on some biological molecules target (myoglobin and cytochrome c). Finally other inorganic and biological systems could be taken into account for future applications of this methodology, which could become an important improvement with respect to the multiscattering approach.

Dynamical Casimir effect and the structure of vacuum in quantum field theory

Some of the most interesting phenomena that arise from the developments of the modern physics are surely vacuum fluctuations. They appear in different branches of physics, such as Quantum Field Theory, Cosmology, Condensed Matter Physics, Atomic and Molecular Physics, and also in Mathematical Physics. One of the most important of these vacuum fluctuations, sometimes called "zero-point energy", as well as one of the easiest quantum effect to detect, is the so-called Casimir effect. The purposes of this thesis are: - To propose a simple retarded approach for dynamical Casimir effect, thus a description of this vacuum effect when we have moving boundaries. - To describe the behaviour of the force acting on a boundary, due to its self-interaction with the vacuum.

Mobile TuCSoN: theoretical and technological requirements for TuCSoN's porting over Android mobile devices

Communication and coordination are two key-aspects in open distributed agent system, being both responsible for the system’s behaviour integrity. An infrastructure capable to handling these issues, like TuCSoN, should to be able to exploit modern technologies and tools provided by fast software engineering contexts. Thesis aims to demonstrate TuCSoN infrastructure’s abilities to cope new possibilities, hardware and software, offered by mobile technology. The scenarios are going to configure, are related to the distributed nature of multi-agent systems where an agent should be located and runned just on a mobile device. We deal new mobile technology frontiers concerned with smartphones using Android operating system by Google. Analysis and deployment of a distributed agent-based system so described go first to impact with quality and quantity considerations about available resources. Engineering issue at the base of our research is to use TuCSoN against to reduced memory and computing capability of a smartphone, without the loss of functionality, efficiency and integrity for the infrastructure. Thesis work is organized on two fronts simultaneously: the former is the rationalization process of the available hardware and software resources, the latter, totally orthogonal, is the adaptation and optimization process about TuCSoN architecture for an ad-hoc client side release.

Learning and accepting quantum physics. Re-analysis of a teaching proposal

Nella tesi è analizzata nel dettaglio una proposta didattica sulla Fisica Quantistica elaborata dal gruppo di ricerca in Didattica della Fisica dell’Università di Bologna, in collaborazione con il gruppo di ricerca in Fisica Teorica e con ricercatori del CNR di Bologna. La proposta è stata sperimentata in diverse classi V di Liceo scientifico e dalle sperimentazioni sono emersi casi significativi di studenti che non sono riusciti ad accettare la teoria quantistica come descrizione convincente ad affidabile della realtà fisica (casi di non accettazione), nonostante sembrassero aver capito la maggior parte degli argomenti e essersi ‘appropriati’ del percorso per come gli era stato proposto. Da questa evidenza sono state formulate due domande di ricerca: (1) qual è la natura di questa non accettazione? Rispecchia una presa di posizione epistemologica o è espressione di una mancanza di comprensione profonda? (2) Nel secondo caso, è possibile individuare precisi meccanismi cognitivi che possono ostacolare o facilitare l’accettazione della fisica quantistica? L’analisi di interviste individuali degli studenti ha permesso di mettere in luce tre principali esigenze cognitive (cognitive needs) che sembrano essere coinvolte nell’accettazione e nell’apprendimento della fisica quantistica: le esigenze di visualizzabilità, comparabilità e di ‘realtà’. I ‘cognitive needs’ sono stati quindi utilizzati come strumenti di analisi delle diverse proposte didattiche in letteratura e del percorso di Bologna, al fine di metterne in luce le criticità. Sono state infine avanzate alcune proposte per un suo miglioramento.

Theoretical and experimental studies of gold catalysts for glucose oxidation

The glucaric acid (GLA) has been identified as a “top value-added chemical from biomass” that can be employed for many uses; for instance, it could be a precursor of adipic acid, a monomer of Nylon-6,6. GLA can be synthetized by the oxidation of glucose (GLU), passing through the intermediate gluconic acid (GLO). In recent years, a new process has been sought to obtain GLA in an economic and environmental sustainable way, in order to replace the current use of HNO3 as a stoichiometric oxidant, or electrocatalysis and biochemical synthesis, which show several disadvantages. Thereby, this work is focused on the study of catalysts based on gold nanoparticles supported on activated carbon for the oxidation reaction of GLU to GLA using O2 as an oxidant agent and NaOH as base. The sol-immobilization method leads us to obtain small and well dispersed nanoparticles, characterized by UV-Vis, XRD and TEM techniques. Repeating the reaction on different batches of catalyst, both the synthesis and the reaction were confirmed to be reproducible. The effect of the reaction time feeding GLO as reagent was studied: the results show that the conversion of GLO increases as the reaction time increases; however, the yields of GLA and others increase up to 1 hour, and then they remain constant. In order to obtain information on the catalytic mechanism at the atomistic level, a computational study based on density functional theory and atomistic modeling of the gold nano-catalyst were performed. Highly symmetric (icosahedral and cubo-octahedral) and distorted Au55 nanoparticles have been optimized along with Au(111) and Au(100) surfaces. Distorted structures were found to be more stable than symmetrical ones due to relativistic effects. On these various models the adsorptions of various species involved in the catalysis have been studied, including OH- species, GLU and GLO. The study carried out aims to provide a method for approaching to the study of nanoparticellary catalytic systems.

Theoretical and experimental investigations on homologation of ethanol to butanol using a ruthenium-based catalyst

The mechanism of homologation of bioethanol to butanol and higher alcohols via the Guerbet reaction was computationally and experimentally investigated. The catalytic pathway involves a ruthenium-based complex and a base co-catalyst which work simultaneously. Due to selectivity issues, secondary products were formed and high competition between main pathway and side reactions was recorded. Herein, the overall catalytic mechanism for all the processes involved in was investigated, also considering the principal side reactions, using density functional theory (DFT) methods and experiments to confirm theoretical outcomes. Due to the complexity of the reaction network, kinetic simulations were established from DFT results, confirming experimental products distribution and giving insights into the factors governing the reaction mechanism.

Factors affecting the mission time of an autonomous mobile robot: a theoretical and experimental investigation

I vantaggi dell’Industria 4.0 hanno stravolto il manufacturing. Ma cosa vuol dire "Industria 4.0"? Essa è la nuova frontiera del manufacturing, basata su princìpi che seguono i passi avanti dei sistemi IT e della tecnologia. Dunque, i suoi pilastri sono: integrazione, verticale e orizzontale, digitalizzazione e automazione. L’Industria 4.0 coinvolge molte aree della supply chain, dai flussi informativi alla logistica. In essa e nell’intralogistica, la priorità è sviluppare dei sistemi di material handling flessibili, automatizzati e con alta prontezza di risposta. Il modello ideale è autonomo, in cui i veicoli fanno parte di una flotta le cui decisioni sono rese decentralizzate grazie all'alta connettività e alla loro abilità di collezionare dati e scambiarli rapidamente nel cloud aziendale.Tutto ciò non sarebbe raggiungibile se ci si affidasse a un comune sistema di trasporto AGV, troppo rigido e centralizzato. La tesi si focalizza su un tipo di material handlers più flessibile e intelligente: gli Autonomous Mobile Robots. Grazie alla loro intelligenza artificiale e alla digitalizzazione degli scambi di informazioni, interagiscono con l’ambiente per evitare ostacoli e calcolare il percorso ottimale. Gli scenari dell’ambiente lavorativo determinano perdite di tempo nel tragitto dei robot e sono queste che dovremo studiare. Nella tesi, i vantaggi apportati dagli AMR, come la loro decentralizzazione delle decisioni, saranno introdotti mediante una literature review e poi l’attenzione verterà sull’analisi di ogni scenario di lavoro. Fondamentali sono state le esperienze nel Logistics 4.0 Lab di NTNU, per ricreare fisicamente alcuni scenari. Inoltre, il software AnyLogic sarà usato per riprodurre e simulare tutti gli scenari rilevanti. I risultati delle simulazioni verranno infine usati per creare un modello che associ ad ogni scenario rilevante una perdita di tempo, attraverso una funzione. Per questo saranno usati software di data analysis come Minitab e MatLab.

Many-body approach to the BCS-BEC crossover for an imbalanced ultra-cold Fermi gas

The aim of this thesis is the study of the normal phase of a mass imbalanced and polarized ultra-cold Fermi gas in the context of the BCS-BEC crossover, using a diagrammatic approach known as t-matrix approximation. More specifically, the calculations are implemented using the fully self-consistent t-matrix (or Luttinger- Ward) approach, which is already experimentally and numerically validated for the balanced case. An imbalance (polarization) between the two spin populations works against pairing and superfluidity. For sufficiently large polarization (and not too strong attraction) the system remains in the normal phase even at zero temperature. This phase is expected to be well described by the Landau’s Fermi liquid theory. By reducing the spin polarization, a critical imbalance is reached where a quantum phase transition towards a superfluid phase occurs and the Fermi liquid description breaks down. Depending on the strength of the interaction, the exotic superfluid phase at the quantum critical point (QCP) can be either a FFLO phase (Fulde-Ferrell-Larkin-Ovchinnikov) or a Sarma phase. In this regard, the presence of mass imbalance can strongly influence the nature of the QCP, by favouring one of these two exotic types of pairing over the other, depending on whether the majority of the two species is heavier or lighter than the minority. The analysis of the system is made by focusing on the temperature-coupling-polarization phase diagram for different mass ratios of the two components and on the study of different thermodynamic quantities at finite temperature. The evolution towards a non-Fermi liquid behavior at the QCP is investigated by calculating the fermionic quasi-particle residues, the effective masses and the self-energies at zero temperature.

Theoretical and experimental study on the role of benzoquinone in the Guerbet reaction catalyzed by a ruthenium complex

The benzoquinone was found as an effective co-catalyst in the ruthenium/NaOEt-catalyzed Guerbet reaction. The co-catalyst behavior has therefore been investigated through experimental and computational methods. The reaction products distribution shows that the reaction speed is improved by the benzoquinone supplement since the beginning of the process, having a minimal effect on the selectivity toward alcoholic species. DFT calculations were performed to investigate two hypotheses for the kinetic effects: i) a hydrogen storage mechanism or ii) a basic co-catalysis of 4-hydroxiphenolate. The most promising results were found for the latter hypothesis, where a new mixed mechanism for the aldol condensation step of the Guerbet process involves the hydroquinone (i.e. the reduced form of benzoquinone) as proton source instead of ethanol. This mechanism was found to be energetically more favorable than an aldol condensation in absence of additive, suggesting that the hydroquinone derived from benzoquinone could be the key species affecting the kinetics of the overall process. To verify this theoretical hypothesis, new phenol derivatives were tested as additives in the Guerbet reaction. The outcomes confirmed that an aromatic acid (stronger than ethanol) could improve the reaction kinetics. Lastly, theoretical products distributions were simulated and compared to the experimental one, using the DFT computations to build the kinetic models.