Dissertations / Theses on the topic 'Modèle de Kuramoto'

Dans cette thèse, on étudie des systèmes de particules en interaction dont le comportement est lié à certaines équations aux dérivées partielles lorsque le nombre de particules tend vers l'infini. L'équation de Kuramoto-Sivashinsky modélise par exemple la propagation de certains fronts de flamme, la topographie de la surface d'une couche mince en cours de croissance, et fait apparaître des structures macroscopiques. Un modèle de particules en interaction par un couplage harmonique des vitesses, attractif aux premières vitesses voisines, répulsive aux secondes voisines, associée à des collisions élastiques, produit des profils de vitesses analogues aux fronts de flamme. On observe également la création et l'annihilation d'agrégats de particules. Un autre modèle, où les particules fusionnent lors des collisions en préservant masse et quantité de mouvement, et avec uniquement attraction au plus proche voisin, permet de retrouver un modèle de type gaz sans pression avec viscosité. Ces modèles sont étudiés théoriquement, en particulier les facteurs de mise à l'échelle des forces d'interaction sont précisés pour obtenir les équations correctes dans la limite du grand nombre de particules. Des simulations numériques confirment la validité et la pertinence des modèles.

Cette thèse porte sur les propriétés fondamentales d'un modèle simplifié de système d'alimentation dynamique. Ces modèles permettent d'étudier l'influence des propriétés géométriques du réseau décrivant le système électrique. Ces modèles et certaines propriétés importantes des modèles sont présentés au chapitre 1. L'un des principaux défis de la recherche sur les systèmes électriques est la complexité du système. Nous voulons utiliser la théorie du graphique spectral pour décomposer le système en différents modes, qui peuvent être étudiés individuellement. Le deuxième chapitre présente le contexte mathématique de la théorie des graphes spectraux et les applications aux systèmes d'alimentation. Un exemple simple d'application de la théorie des graphes spectraux à la recherche sur les systèmes d'alimentation est donné au chapitre 3, où l'on étudie le système d'alimentation statique. Nous pouvons voir que les valeurs propres et les vecteurs propres de la matrice d'admission nodale du système électrique peuvent être utilisés pour calculer les phases et les flux dans un système statique. Les propriétés dynamiques sont ensuite étudiées plus en profondeur dans le chapitre suivant. Ici, un problème de valeur propre quadratique doit être utilisé pour étudier le système. Nous présentons les propriétés fondamentales du problème de la valeur propre quadratique et son application à la recherche sur les systèmes d'alimentation. Une étude approfondie des propriétés spectrales d'un système de puissance dynamique utilisant le problème des valeurs propres quadratiques est ensuite réalisée. Nous observons des interactions à courte et longue portée dans le système et constatons que les interactions à courte portée sont plus sensibles aux paramètres de la machine et sont importantes pour la stabilité du système électrique, car elles sont liées aux modes locaux de la centrale. L'émergence de ce comportement localisé est étudiée au chapitre 5. Nous dérivons deux limites de vecteurs propres qui peuvent être utilisées pour prédire et décrire la localisation dans un réseau. Ces limites sont ensuite appliquées à des exemples simples de graphiques et à un cas de test de système électrique, pour montrer comment ils peuvent prédire, expliquer et décrire avec succès la localisation
This thesis investigates the fundamental properties of a simplified dynamical power system model. These models can be used to study the influence of the geometrical properties of the network describing the power system. These models and some important properties of the models are presented in chapter 1. One of the main challenges in power system research is the complexity of the system. We want to use spectral graph theory to decompose the system into different modes, which can be studied individually. The second chapter introduces the mathematical background of spectral graph theory and the applications to power systems. A simple example for the application of spectral graph theory in power system research is given in chapter 3, where the static power flow system is investigated. We can see that the eigenvalues and eigenvectors of the nodal admittance matrix of the power system can be used to calculate the phases and flows in a static system. The dynamical properties are then deeper investigated in the next chapter. Here, a quadratic eigenvalue problem has to be used to investigate the system. We introduce the fundamental properties of the quadratic eigenvalue problem and the application to power system research. An extensive investigation of the spectral properties of a dynamical power system using the quadratic eigenvalue problem is then performed. We observe short and long range interactions in the system and see that the short range interactions are more sensitive to the machine parameters and are important for the stability of the power system, as they are related to local plant modes. The emergence of this localised behaviour is investigated in chapter 5. We derive two eigenvector bounds which can be used to predict and describe localisation in a network. These bounds are then applied to simple example graphs and a power system test case, to show how they can successfully predict, explain and describe localisation

On s’intéresse dans cette thèse à des systèmes couplés de type champ moyen en étudiant l’existence de l’état de synchronisation qui se caractérise par une distance uniformément bornée dans le temps entre chaque paire de composantes d’une solution. L’étude se base sur une méthode perturbative. Néanmoins les résultats obtenus ne sont pas évidents dans le cas non-perturbé. En outre dans le cas où le système couplé est périodique et grâce au Théorème du point fixe on montre l’existence d’une solution périodique sur le tore. L’étude de stabilité et de stabilité exponentielle est établie dans le cas linéaire et appliquée à ce type de systèmes couplés
We study in this thesis a class of a perturbed interconnected mean-field system, also known as a coupled systems. Under some assumptions we prove the existence of an invariant open set by the flow of the perturbed system ; in other word, we prove that the distance between the components of an orbit is uniformly bounded, this property is also called synchronization. We use the perturbation method to obtain the result. However the result is not trivial for the not perturbed system. We use the fixed point theorem to prove the existence of a periodic orbit in the torus. We study in addition the stability and the exponential stability of such systems by studying the stability of a linear systems

Cette thèse porte sur l'analyse de la synchronisation des grands réseaux d'oscillateurs non linéaires et hétérogènes à l'aide d'outils et de méthodes issues de la théorie du contrôle. Nous considérons deux modèles de réseaux; à savoir, le modèle de Kuramoto qui considère seulement les coordonnées de phase des oscillateurs et des réseaux composés d'oscillateurs non linéaires de Stuart-Landau connectés par un couplage linéaire.Pour le modèle de Kuramoto nous construisons un système linéaire qui conserve les informations sur les fréquences naturelles et sur les gains d'interconnexion du modèle original de Kuramoto. Nous montrons en suite que l'existence de solutions à verrouillage de phase du modèle de Kuramoto est équivalente à l'existence d'un tel système linéaire avec certaines propriétés. Ce système est utilisé pour formuler les conditions d'existence de solutions à verrouillage de phase et de leur stabilité pour des structures particulières de l'interconnexion. Ensuite, cette analyse s'est étendue au cas où des interactions attractives et répulsives sont présentes dans le réseau. Nous considérons cette situation lorsque les gains d'interconnexion peuvent être à la fois positif et négatif. Dans le cadre de réseaux d'oscillateurs de Stuart-Landau, nous présentons une nouvelle transformation de coordonnées du réseau qui permet de réécrire le modèle du réseau en deux parties: une décrivant le comportement de l'oscillateur « moyenne » du réseau et la seconde partie présentant les dynamiques des erreurs de synchronisation par rapport à cet oscillateur « moyenne ». Cette transformation nous permet de caractériser les propriétés du réseau en termes de la stabilité des erreurs de synchronisation et du cycle limite de l'oscillateur « moyenne ». Pour ce faire, nous reformulons ce problème en un problème de stabilité de deux ensembles compacts et nous utilisons des outils issus de la stabilité de Lyapunov pour montrer la stabilité pratique de ces derniers pour des valeurs suffisamment grandes du gain d'interconnexion
This thesis is devoted to the analysis of synchronization in large networks of heterogeneous nonlinear oscillators using tools and methods issued from control theory. We consider two models of networks; namely, the Kuramoto model which takes into account only phase coordinates of the oscillators and networks composed of nonlinear Stuart-Landau oscillators interconnected by linear coupling. For the Kuramoto model we construct an auxiliary linear system that preserves information on the natural frequencies and interconnection gains of the original Kuramoto model. We show next that existence of phase locked solutions of the Kuramoto model is equivalent to the existence of such a linear system with certain properties. This system is used to formulate conditions that ensure existence of phase-locked solutions and their stability for particular structures of network interconnections. Next, this analysis is extended to the case where both attractive and repulsive interactions are present in the network that is we consider the situation where some of the interconnection gains are allowed to be negative. In the context of networks of Stuart-Landau oscillators, we present a new coordinate transformation of the network which allows to split the network model into two parts, one describing behaviour of an "averaged" network oscillator and the second one, describing dynamics of the synchronization errors relative to this "averaged" oscillator. This transformation allows us to characterize properties of the network in terms of stability of synchronization errors and limit cycle of the "averaged" oscillator. To do so, we recast this problem as a problem of stability of compact sets and use Lyapunov stability tools to ensure practical stability of both sets for sufficiently large values of the coupling strength

On s’intéresse dans cette thèse à des systèmes couplés de type champ moyen en étudiant l’existence de l’état de synchronisation qui se caractérise par une distance uniformément bornée dans le temps entre chaque paire de composantes d’une solution. L’étude se base sur une méthode perturbative. Néanmoins les résultats obtenus ne sont pas évidents dans le cas non-perturbé. En outre dans le cas où le système couplé est périodique et grâce au Théorème du point fixe on montre l’existence d’une solution périodique sur le tore. L’étude de stabilité et de stabilité exponentielle est établie dans le cas linéaire et appliquée à ce type de systèmes couplés
We study in this thesis a class of a perturbed interconnected mean-field system, also known as a coupled systems. Under some assumptions we prove the existence of an invariant open set by the flow of the perturbed system ; in other word, we prove that the distance between the components of an orbit is uniformly bounded, this property is also called synchronization. We use the perturbation method to obtain the result. However the result is not trivial for the not perturbed system. We use the fixed point theorem to prove the existence of a periodic orbit in the torus. We study in addition the stability and the exponential stability of such systems by studying the stability of a linear systems

Dissertação (mestrado)—Universidade de Brasília, Instituto de Física, 2011.
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Uma vasta gama de fenômenos na natureza exibe comportamento de sincronização. Muitas características de sincronização podem ser obtidas por meio de osciladores de fase acoplados. O estudo de osciladores acoplados foi impulsionado por Winfree e posteriormente simplificado por Kuramoto. Neste trabalho estuda-se a transição de fase no modelo de Kuramoto com e sem ruído, considerando as influências dos efeitos de tamanho finito e das distribuições de frequências naturais dos osciladores. Variando o número de osciladores interagentes, é verificada a maneira como propriedades importantes para caracterizar o regime sincronizado convergem para os valores teóricos obtidos no limite termodinâmico. É mostrado que o modo como as frequências naturais são distribuidas define o tipo de transição do modelo. O cálculo da flutuação do parâmetro de ordem na região de transição é proposto para obtenção do acoplamento crítico em grande grupos de osciladores interagentes; este método é útil pois permite estimar o acoplamento crítico de modelos cujas soluções analíticas não são possíveis. ________________________________________________________________________________ ABSTRACT
A broad range of phenomena shows synchronization behavior. Many features of the synchronization can be obtained on phase coupled oscillators. The studying of coupled oscillators was started by Winfree and later simpli ed by Kuramoto. In this work is studied the phase transition in the Kuramoto's model with and without noise, considering in uences from nite-size e ects and natural frequencies distributions of the oscillators. By changing the number of interacting oscillators, it is veri ed how important properties that characterize synchronized states converge towards the theoretical values, which are obtained in the thermodynamical limit. It is also shown how natural frequencies distributions de ne the transition type of the model. It is proposed the use of the order parameter uctuation calculation for obtaining the critical coupling on large groups of interacting oscillators; this method is useful since it allows an estimation of the critical coupling coefficient of models in which analytical solutions are not possible.

Le modele considere dans cette these comporte une equation aux derivees partielles spatio-temporelles (d'ordre quatre en espace, parabolique non lineaire) caracterisee en outre par un terme de diffusion negative. Il apparait dans divers contextes physico-chimiques (phenomenes d'instabilites interfaciales, turbulence de phase, front de flamme. . . ). Depuis douze ans, ce modele a ete tres etudie dans sa version unidimensionnelle. Pour l'analyse du modele multidimensionnel, la question d'existence de slution rstait encore ouverte: la presente these y repond en developpant l'indispensable recherche d'inegalites a priori. La memoire est divisee en deux parties: la premiere pour etudier le modele stabilise par l'introductin d'un terme d'ordre zero, nous y obtenons des theoremes d'existence globale pourvu que les conditions initiales soient de taille petite; la seconde partie analyse le probleme non stabilise, nous y obtenons des theoremes d'existence locale. Il s'agit de solutions fortes construites par une analyse du point fixe fondee sur des resultats classiques de semi-groupe, et une technique de majoration probablement innovante

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Este texto é dedicado ao estudo do fenômeno de sincronização no modelo de Kuramoto. Na primeira parte o foco reside na formulação original do modelo no limite termodinâmico de infinitos osciladores e na descrição da transição para a sincronização e estabilidade das soluções em sistemas com número finito de elementos. Mostra-se também que o acoplamento crítico de sincronização 'K IND s' é determinado por um par de equações, e a solução para um caso especial com simetria na configuração de frequências naturais é obtida de forma perturbativa. A segunda parte do texto é focada na descrição do modelo de Kuramoto com acoplamento local em 1 dimensão com condições periódicas de contorno. A estrutura de árvores de sincronização média é descrita, onde ocorrem transições entre regimes caóticos e periódicos dos movimentos individuais dos osciladores. A iminência da sincronização é explorada através uma série de aproximações que mostram o comportamento crítico característico de uma bifurcação sela-nó responsável pela sincronização. A partir da definição de uma função na região sincronizada é mostrado que o acoplamento crítico de sincronização é obtido exatamente através da minimização dessa função. Através de uma sequência de exemplos de configurações com simetria é mostrado que a região sincronizada do sistema apresenta uma estrutura de múltiplas soluções estáveis, sendo a sua caracterização, análise de estabilidade e descrição das bifurcações realizada para o caso com frequências aleatórias arbitrariamente distribuídas
This text is devoted to the study of the synchronization phenomena in the Kuramoto model. In its first part the focus lies on its original formulation of infinitely many oscillators and on the description of the synchronization transition and solutions’ stability for systems with a finite number of elements. It is shown that a pair of equations characterize the critical synchronization coupling Ks, and the solution for a special case with symmetry on its natural frequencies configuration is obtained in a perturbatively way. The second part of the text is focused on the 1-dimensional Kuramoto model with periodic boundary conditions. The synchronization tree structure is described, where it is observed several transitions between chaotic and periodic regimes among the individual oscillators. The onset on synchronization is explored through a series of approximations that show the characteristic critical behavior of a saddle node bifurcation, which is responsible for the synchronization. By defining a function on the synchronized region it is shown that the critical synchronization coupling is exactly determined by the function’s minimization process. Through a sequence of examples with symmetry on its configurations it is shown that the synchronized region presents a structure of multiple stable solutions. Its complete characterization, stability analysis and bifurcations’ description is carried through for the case with randomly distributed natural frequencies

Orientador: Gerson Francisco
Coorientador: Fernando Fagundes Ferreira
Banca: Mauro Copelli
Banca: Ricardo Luiz Viana
Banca: Paulo Laerte Natti
Banca: Tiago Pereira da Silva
Resumo: Este texto é dedicado ao estudo do fenômeno de sincronização no modelo de Kuramoto. Na primeira parte o foco reside na formulação original do modelo no limite termodinâmico de infinitos osciladores e na descrição da transição para a sincronização e estabilidade das soluções em sistemas com número finito de elementos. Mostra-se também que o acoplamento crítico de sincronização 'K IND s' é determinado por um par de equações, e a solução para um caso especial com simetria na configuração de frequências naturais é obtida de forma perturbativa. A segunda parte do texto é focada na descrição do modelo de Kuramoto com acoplamento local em 1 dimensão com condições periódicas de contorno. A estrutura de árvores de sincronização média é descrita, onde ocorrem transições entre regimes caóticos e periódicos dos movimentos individuais dos osciladores. A iminência da sincronização é explorada através uma série de aproximações que mostram o comportamento crítico característico de uma bifurcação sela-nó responsável pela sincronização. A partir da definição de uma função na região sincronizada é mostrado que o acoplamento crítico de sincronização é obtido exatamente através da minimização dessa função. Através de uma sequência de exemplos de configurações com simetria é mostrado que a região sincronizada do sistema apresenta uma estrutura de múltiplas soluções estáveis, sendo a sua caracterização, análise de estabilidade e descrição das bifurcações realizada para o caso com frequências aleatórias arbitrariamente distribuídas
Abstract: This text is devoted to the study of the synchronization phenomena in the Kuramoto model. In its first part the focus lies on its original formulation of infinitely many oscillators and on the description of the synchronization transition and solutions' stability for systems with a finite number of elements. It is shown that a pair of equations characterize the critical synchronization coupling Ks, and the solution for a special case with symmetry on its natural frequencies configuration is obtained in a perturbatively way. The second part of the text is focused on the 1-dimensional Kuramoto model with periodic boundary conditions. The synchronization tree structure is described, where it is observed several transitions between chaotic and periodic regimes among the individual oscillators. The onset on synchronization is explored through a series of approximations that show the characteristic critical behavior of a saddle node bifurcation, which is responsible for the synchronization. By defining a function on the synchronized region it is shown that the critical synchronization coupling is exactly determined by the function's minimization process. Through a sequence of examples with symmetry on its configurations it is shown that the synchronized region presents a structure of multiple stable solutions. Its complete characterization, stability analysis and bifurcations' description is carried through for the case with randomly distributed natural frequencies
Doutor

Dans cette thèse, nous étudions le modèle de synchronisation de Kuramoto et plus généralement des systèmes de diffusions interagissant en champ moyen, en présence d'un aléa supplémentaire appelé désordre. La motivation principale en est l'étude du comportement du système en grande population, pour une réalisation fixée du désordre (modèle quenched). Ce document, outre l'introduction, comporte quatre chapitres. Le premier s'intéresse à la convergence de la mesure empirique du système d'oscillateurs vers une mesure déterministe, solution d'un système d'équations aux dérivées partielles non linéaires couplées (équation de McKean-Vlasov). Cette convergence est prouvée indirectement via un principe de grandes déviations dans le cas averaged et directement dans le cas quenched, sous des hypothèses plus faibles sur le désordre. Le deuxième chapitre est issu d'un travail en commun avec Giambattista Giacomin et Christophe Poquet et concerne la régularité des solutions de l'EDP limite ainsi que la stabilité de ses solutions stationnaires synchronisées dans le cas d'un désordre faible. Les deux derniers chapitres étudient l'influence du désordre sur une population d'oscillateurs de taille finie et illustrent des problématiques observées dans la littérature physique. Nous prouvons dans le troisième chapitre un théorème central limite quenched associé à la loi des grands nombres précédente: on montre que le processus de fluctuations quenched converge, en un sens faible, vers la solution d'une EDPS linéaire. Le dernier chapitre étudie le comportement en temps long de cette EDPS, illustrant le fait que les fluctuations dans le modèle de Kuramoto ne sont pas auto-moyennantes.

Mestrado em Física
Neste trabalho é estudado o modelo de Kuramoto num grafo completo, em redes scale-free com uma distribuição de ligações P(q) ~ q-Y e na presença de campos aleatórios com magnitude constante e gaussiana. Para tal, foi considerado o método Ott-Antonsen e uma aproximação "annealed network". Num grafo completo, na presença de campos aleatórios gaussianos, e em redes scale-free com 2 < y < 5 na presença de ambos os campos aleatórios referidos, foram encontradas transições de fase contínuas. Considerando a presença de campos aleatórios com magnitude constante num grafo completo e em redes scale-free com y > 5, encontraram-se transições de fase contínua (h < √2) e descontínua (h > √2). Para uma rede SF com y = 3, foi observada uma transição de fase de ordem infinita. Os resultados do modelo de Kuramoto num grafo completo e na presença de campos aleatórios com magnitude constante foram comparados aos de simulações, tendo-se verificado uma boa concordância. Verifica-se que, independentemente da topologia de rede, a constante de acoplamento crítico aumenta com a magnitude do campo considerado. Na topologia de rede scale-free, concluiu-se que o valor do acoplamento crítico diminui à medida que valor de y diminui e que o grau de sincronização aumenta com o aumento do número médio das ligações na rede. A presença de campos aleatórios com magnitude gaussiana num grafo completo e numa rede scale-free com y > 2 não destrói a transição de fase contínua e não altera o comportamento crítico do modelo de Kuramoto.
In the present work, a random field Kuramoto model is studied in complete graphs and scale-free networks with the degree distribution P(q) ~ q-Y, taking into account constant random fields with constant magnitude as well as gaussian distributed. For this purpose, the Ott-Antonsen method and the annealed-network approximation are used. A continuous phase transition is found in the case of complete graph and gaussian random fields, and in the case of scale-free networks with 2 < y < 5 in the presence of random fields with both constant and gaussian magnitude. In the case of random fields with a constant magnitude and the architectures: complete graph and scale-free network with y > 5, both first (h > √2) and second (h < √2) order phase transition are found. In a scale-free network with y = 3, it is revealed an infinite order phase transition. The numerical results for random field Kuramoto model with constant magnitude in complete graph are compared to simulations and a good agreement is found between the theoretical approach and simulations. It is shown that the critical coupling increases when increasing the field magnitude, independently of network topology. For scale-free networks, the critical coupling decreases when decreasing y and the synchronization degree increases when increasing the mean degree of the network. In the case of complete graph and a scale-free network with y > 2, gaussian random fields do not destroy the continuous phase transition and do not change critical behavior of the Kuramoto model.

Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from biological and physical to social and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. For decades, this model has been traditionally studied in globally coupled topologies. However, besides being intrinsically dynamical, complex systems exhibit very heterogeneous structure, which can be represented as complex networks. This thesis is dedicated to the investigation of fundamental problems regarding the collective dynamics of Kuramoto oscillators coupled in complex networks. First, we address the effects on network dynamics caused by the presence of triangles, which are structural patterns that permeate real-world networks but are absent in random models. By extending the heterogeneous degree mean-field approach to a class of configuration model that generates random networks with variable clustering, we show that triangles weakly affect the onset of synchronization. Our results suggest that, at least in the low clustering regime, the dynamics of clustered networks are accurately described by tree-based theories. Secondly, we analyze the influence of inertia in the phases evolutions. More precisely, we substantially extend the mean-field calculations to second-order Kuramoto oscillators in uncorrelated networks. Thereby hysteretic transitions of the order parameter are predicted with good agreement with simulations. Effects of degree-degree correlations are also numerically scrutinized. In particular, we find an interesting dynamical equivalence between variations in assortativity and damping coefficients. Potential implications to real-world applications are discussed. Finally, we tackle the problem of two intertwined populations of stochastic oscillators subjected to asymmetric attractive and repulsive couplings. By employing the Gaussian approximation technique we derive a reduced set of ODEs whereby a thorough bifurcation analysis is performed revealing a rich phase diagram. Precisely, besides incoherence and partial synchronization, peculiar states are uncovered in which two clusters of oscillators emerge. If the phase lag between these clusters lies between zero and π, a spontaneous drift different from the natural rhythm of oscillation emerges. Similar dynamical patterns are found in chaotic oscillators under analogous couplings schemes.
Sincronização de conjuntos de osciladores é um fenômeno emergente que permeia sistemas complexos de diversas naturezas, como por exemplo, sistemas biológicos, físicos, naturais e tecnológicos. A abordagem mais bem sucedida na descrição da emergência de comportamento coletivo em sistemas complexos é fornecida pelo modelo de Kuramoto. Durante décadas, este modelo foi tradicionalmente estudado em topologias completamente conectadas. Entretanto, além de ser intrinsecamente dinâmicos, tais sistemas complexos possuem uma estrutura altamente heterogênea que pode ser apropriadamente representada por redes complexas. Esta tese é dedicada à investigação de problemas fundamentais da dinâmica coletiva de osciladores de Kuramoto acoplados em redes. Primeiramente, abordamos os efeitos sobre a dinâmica das redes causados pela presença de triângulos padrões que estão omnipresentes em redes reais mas estão ausentes em redes gerados por modelos aleatórios. Estendemos a abordagem via campo-médio para uma variação do modelo de configuração tradicional capaz de criar topologias com número variável de triângulos. Através desta abordagem, mostramos que tais padrões estruturais pouco influenciam a emergência de comportamento coletivo em redes, podendo a dinâmica destas ser descrita em termos de teorias desenvolvidas para redes com topologia local semelhante a grafos de tipo árvore. Em seguida, analisamos a influência de inércia na evolução das fases. Mais precisamente, generalizamos cálculos de campo-médio para osciladores de segunda-ordem acoplados em redes sem correlação de grau. Demonstramos que na presença de efeitos inerciais o parâmetro de ordem do sistema se comporta de forma histerética. Ademais, efeitos oriundos de correlações de grau são examinados. Em particular, verificamos uma interessante equivalência dinâmica entre variações nos coeficientes de assortatividade e amortecimento dos osciladores. Possíveis aplicações para situações reais são discutidas. Finalmente, abordamos o problema de duas populações de osciladores estocásticos sob a influência de acoplamentos atrativos e repulsivos. Através da aplicação da aproximação Gaussiana, derivamos um conjunto reduzido de EDOs através do qual as bifurcações do sistema foram analisadas. Além dos estados asíncrono e síncrono, verificamos a existência de padrões peculiares na dinâmica de tal sistema. Mais precisamente, observamos a formação de estados caracterizados pelo surgimento de dois aglomerados de osciladores. Caso a defasagem entre estes grupos é inferior a π, um novo ritmo de oscilação diferente da frequência natural dos vértices emerge. Comportamentos dinâmicos similares são observados em osciladores caóticos sujeitos a acoplamentos análogos.

Il est bien connu que la synchronisation de l'activité oscillatoire dans les réseaux de neurones joue un rôle important dans le fonctionnement du cerveau et pour le traitement des informations données pas les neurones. Cette thèse porte sur l'analyse de l'activité de synchronisation en utilisant des outils et des méthodes issues de la théorie du contrôle et de la théorie de la stabilité. En particulier, deux modèles ont été étudiés pour décrire l'activité oscillatoire des réseaux de neurones : le modèle de Kuramoto et le modèle de Hindmarsh-Rose. Une partie de ce manuscript est consacrée à l'étude du modèle de Kuramoto, qui est un des systèmes les plus simples utilisé pour modéliser un réseau de neurones, avec une connexion complète (all-to-all). Il s'agit d'un modèle classique qui est utilisé comme une version simplifiée d'un réseau de neurones. Nous construisons un système linéaire qui conserve les informations sur les fréquences naturelles et sur les gains d'interconnexion du modèle original de Kuramoto. Les propriétés de stabilité de ce modèle sont ensuite analysées et nous montrons que les solutions de ce nouveau système linéaire convergent vers un cycle limite périodique et stable. Finalement, nous montrons que contraint au cycle limite, les dynamiques du système linéaire coïncident avec le modèle de Kuramoto. Dans une seconde partie, nous avons considéré un modèle de réseau de neurones plus proche de la réalité d'un point de vue biologique, mais qui est plus complexe que le modèle de Kuramoto. Plus précisément, nous avons utilisé le modèle de Hindmarsh-Rose pour décrire la dynamique de chaque neurone que nous avons interconnecté par un couplage diffusif (c'est à dire linéaire). A partir des propriétés de semi-passivité du modèle de Hindmarsh- Rose, nous avons analysé les propriétés de stabilité d'un réseau hétérogène de Rindmarsh-Rose. Nous avons également montré que ce réseau est pratiquement synchronisé pour une valeur suffisamment grande du gain d'interconnexion. D'autre part, nous avons caractérisé le comportement limite des neurones synchronisés et avons établi une approximation de ce comportement par une moyenne des dynamiques de tous les neurones.

Synchonisation ist ein universelles Phänomen welches in den Natur- und Ingenieurwissenschaften, aber auch in Sozialsystemen vorkommt. Verschiedene Modellsysteme wurden zur Beschreibung von Synchronisation vorgeschlagen, wobei das Kuramoto-Modell das am weitesten verbreitete ist. Das Kuramoto-Modell zweiter Ordnung beschreibt eigenständige Phasenoszillatoren mit heterogenen Eigenfrequenzen, die durch den Sinus ihrer Phasendifferenzen gekoppelt sind, und wird benutzt um nichtlineare Dynamiken in Stromnetzen, Josephson-Kontakten und vielen anderen Systemen zu analysieren. Im Laufe der letzten Jahre wurden insbesondere Netzwerke von Kuramoto-Oszillatoren studiert, da sie einfach genug für eine analytische Beschreibung und denoch reich an vielfältigen Phänomenen sind. Eines dieser Phänomene, explosive synchronization, entsteht in skalenfreien Netzwerken wenn eine Korrelation zwischen den Eigenfrequenzen der Oszillatoren und der Netzwerktopolgie besteht. Im ersten Teil dieser Dissertation wird ein Kuramoto-Netzwerk zweiter Ordnung mit einer Korrelation zwischen den Eigenfrequenzen der Oszillatoren und dem Netzwerkgrad untersucht. Die Theorie im Kontinuumslimit und für unkorrelierte Netzwerke wird für das Modell mit asymmetrischer Eigenfrequenzverteilung entwickelt. Dabei zeigt sich, dass Cluster von Knoten mit demselben Grad nacheinander synchronisieren, beginnend mit dem kleinsten Grad. Dieses neue Phänomen wird als cluster explosive synchronization bezeichnet. Numerische Untersuchungen zeigen, dass dieses Phänomen auch durch die Zusammensetzung der Netzwerkgrade beeinflusst wird. Zum Beispiel entstehen unstetige Übergänge nicht nur in disassortativen, sondern auch in stark assortativen Netzwerken, im Gegensatz zum Kuramoto-Modell erster Ordnung.Unstetige Phasenübergänge lassen sich anhand eines Ordnungsparameters und der Hysterese auf unterschiedliche Anfangsbedingungen zurückführen. Unter starken Störungen kann das System von wünschenswerten in nicht gewünschte Zustände übergehen. Diese Art der Stabilität unter starken Störungen kann mit dem Konzept der basin stability quantifiziert werden. Im zweiten Teil dieser Dissertation wird die basin stability der Synchronisation im Kuramoto-Modell zweiter Ordnung untersucht, wobei die Knoten separat gestört werden. Dabei wurde ein neues Phänomen mit zwei nacheinander auftretenden Übergängen erster Art entdeckt: Eine \emph{onset transition} von einer globalen Stabilität zu einer lokalen Instabilität, und eine suffusing transition von lokaler zu globaler Stabilität. Diese Abfolge wird als onset and suffusing transition bezeichnet.Die Stabilität von Netzwerknoten kann durch die lokale Netzwerktopologie beeinflusst werden, zum Beispiel haben Knoten neben Netzwerk-Endpunkten eine geringe basin stability. Daraus folgend wird ein neues Konzept der partiellen basin stability vorgeschlagen, insbesondere für cluster synchronization, um die wechselseitigen Stabilitätseinflüsse von Clustern zu quantifizieren.Dieses Konzept wird auf zwei wichtige reale Beispiele angewandt: Neuronale Netzwerke und das nordeuropäische Stromnetzwerk. Die neue Methode erlaubt es instabile und stabile Cluster in neuronalen Netzwerken zu identifizieren und erklärt wie Netzwerk-Endpunkte die Stabilität gefährden.
Synchronization phenomena are ubiquitous in the natural sciences and engineering, but also in social systems. Among the many models that have been proposed for a description of synchronization, the Kuramoto model is most popular. It describes self-sustained phase oscillators rotating at heterogeneous intrinsic frequencies that are coupled through the sine of their phase differences. The second-order Kuramoto model has been used to investigate power grids, Josephson junctions, and other systems.The study of Kuramoto models on networks has recently been boosted because it is simple enough to allow for a mathematical treatment and yet complex enough to exhibit rich phenomena. In particular, explosive synchronization emerges in scale-free networks in the presence of a correlation between the natural frequencies and the network topology. The first main part of this thesis is devoted to study the networked second-order Kuramoto model in the presence of a correlation between the oscillators'' natural frequencies and the network''s degree. The theoretical framework in the continuum limit and for uncorrelated networks is provided for the model with an asymmetrical natural frequency distribution. It is observed that clusters of nodes with the same degree join the synchronous component successively, starting with small degrees. This novel phenomenon is named cluster explosive synchronization. Moreover, this phenomenon is also influenced by the degree mixing in the network connection as shown numerically. In particular, discontinuous transitions emerge not just in disassortative but also in strong assortative networks, in contrast to the first-order model. Discontinuous phase transitions indicated by the order parameter and hysteresis emerge due to different initial conditions. For very large perturbations, the system could move from a desirable state to an undesirable state. Basin stability was proposed to quantify the stability of a system to stay in the desirable state after being subjected to strong perturbations. In the second main part of this thesis, the basin stability of the synchronization of the second-order Kuramoto model is investigated via perturbing nodes separately. As a novel phenomenon uncovered by basin stability it is demonstrated that two first-order transitions occur successively in complex networks: an onset transition from a global instability to a local stability and a suffusing transition from a local to a global stability. This sequence is called onset and suffusing transition.Different nodes could have a different stability influence from or to other nodes. For example, nodes adjacent to dead ends have a low basin stability. To quantify the stability influence between clusters, in particular for cluster synchronization, a new concept of partial basin stability is proposed. The concept is implemented on two important real examples: neural networks and the northern European power grid. The new concept allows to identify unstable and stable clusters in neural networks and also explains how dead ends undermine the network stability of power grids.

In the first part of this thesis, motivated by the development of deep brain stimulation for Parkinson's disease, we consider the problem of reducing the synchrony of a neuronal population via a closed-loop electrical stimulation. This, under the constraints that only the mean membrane voltage of the ensemble is measured and that only one stimulation signal is available (mean-field feedback). The neuronal population is modeled as a network of interconnected Landau-Stuart oscillators controlled by a linear single-input single-output feedback device. Based on the associated phase dynamics, we analyze existence and robustness of phase-locked solutions, modeling the pathological state, and derive necessary conditions for an effective desynchronization via mean-field feedback. Sufficient conditions are then derived for two control objectives: neuronal inhibition and desynchronization. Our analysis suggests that, depending on the strength of feedback gain, a proportional mean-field feedback can either block the collective oscillation (neuronal inhibition) or desynchronize the ensemble.In the second part, we explore two possible ways to analyze related problems on more biologically sound models. In the first, the neuronal population is modeled as the interconnection of nonlinear input-output operators and neuronal synchronization is analyzed within a recently developed input-output approach. In the second, excitability and synchronizability properties of neurons are analyzed via the underlying bifurcations. Based on the theory of normal forms, a novel reduced model is derived to capture the behavior of a large class of neurons remaining unexplained in other existing reduced models.

Orientadores: Alberto Vazquez Saa, Marcus Aloizio Martinez de Aguiar
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin
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Resumo: Sincronização está presente em uma miríade de situações, indo desde vaga-lumes piscando em uníssono na copa das árvores, populações de leveduras ajustando seu metabolismo para um ritmo comum, atividades neurais ocorrendo no cérebro, chegando até as redes de distribuição de energia elétrica, as maiores máquinas construídas pelo homem. Neste trabalho, nós analisamos como se dá o processo de sincronização utilizando o bem conhecido modelo de Kuramoto, estudado incansavelmente nas últimas décadas, quando ele se encontra sobre uma rede complexa, que determina os padrões de interação entre os elementos que compõem a população. A topologia dessas interações determina de maneira crucial a dinâmica do sistema, possibilitando, ou não, a sincronização dos seus elementos. Primeiros, nós analisamos o fenômeno da sincronização explosiva: a correlação de propriedades da rede com a frequência natural dos osciladores altera dramaticamente a natureza da transição de fase do estado não sincronizado para o estado sincronizado. Mostramos que sincronização explosiva ocorre mesmo quando apenas uma pequena fração dos vértices da rede possuem tal correlação, a saber, os vértices mais bem conectados da rede. Além do mais, ajustando o número de vértices onde a correlação é válida, podemos controlar propriedades dessa transição de fase. A seguir estudamos o processo de optimização de topologia para favorecer sincronização. Dado um conjunto de vértices/osciladores com frequências naturais conhecidas e um certo número de links, qual é a melhor topologia, ou seja, o padrão de conexões, que favorece a sincronização? Estudamos esse problema numericamente para o modelo de Kuramoto com inércia, que serve como um modelo simples para analisar as redes de transmissão de energia elétrica, obtendo princípios básicos que devem ser utilizados para o design de tais sistemas. Por fim, ainda no problema de optimização de topologia para favorecer sincronização, obtivemos pela primeira vez de forma analítica as condições para optimização para o modelo de Kuramoto, bem como para uma generalização sua, onde há interações positivas e negativas. Esses resultados analíticos ainda servem para criar algoritmos de optimização mais ecientes que os utilizados atualmente
Abstract: Synchronization is present in a myriad of situations, from the unison ashing of reies in trees, populations of yeast adjusting their metabolism to a common rhythm, neural activities in the brain to the largest machines ever built, the power grids. We analysed how the process of synchronization happens using the well known Kuramoto model, tirelessly studied in the last decades, when it is on top of a complex network, that determines the patterns of interaction between the elements of the population. The topology of this network's determines crucially the possible dynamics of the systems, allowing, or not, the synchronization of its elements. We rst discuss the phenomenon of explosive synchronization, where the correlation between properties of the network and the oscillators changes drastically the nature of the phase transition separating the incoherent state from the synchronized state.We show that explosive synchronization can occur even when a small subset of the vertices are correlated. It is necessary that only the hubs, vertices with highest degrees, show the correlation. Moreover, adjust the fraction of correlated vertices allows us to control properties of the phase transition. Next we study the optimization of the topology to favor synchronization. Given a set of vertices/oscillators with know natural frequencies and a certain number of links, which is the best topology, its pattern of interactions, to favor synchronization? We studied this problem to a generalized Kuramoto model (Kuramoto model with inertia) that is used as a simple tool to model power grids, obtaining in this way simple rules that can be applied to the design of such systems that already helps the synchronization of its elements. In our nal contribution, still in the optimization of the topology problem, we were able, for the first time, to obtain analytically the conditions of optimization for the Kuramoto model, as well as for one of its generalizations, where there can exist positive and negative interactions between the elements. Beyond the signicant fact that the conditions can be know analytically, these results can be used to obtain faster optimization algorithms that the current ones
Doutorado
Física
Doutor em Ciências
2012/09357-9
CAPES

Les systèmes en interaction à longue portée sont connus pour avoir des propriétés statistiques et dynamiques particulières. Pour décrire leur évolution dynamique, on utilise des équations cinétiques décrivant leur densité dans l'espace des phases. Ce manuscrit est divisé en deux parties indépendantes. La première traite de notre collaboration avec une équipe expérimentale sur un Piège Magnéto-Optique. Ce dispositif à grand nombre d'atomes présente des interactions coulombiennes effectives provenant de la rediffusion des photons. Nous avons proposé des tests expérimentaux pour mettre en évidence l'analogue d'une longueur de Debye, et son influence sur la réponse du système. Les expériences réalisées ne permettent pour l'instant pas de conclure de façon définitive. Dans la deuxième partie, nous avons analysé les modèles cinétiques de Vlasov et de Kuramoto. Pour étudier leur dynamique de dimension infinie, nous avons examiné les bifurcations autour des états stationnaires instables, l'objectif étant d'obtenir des équations réduites décrivant la dynamique de ces états. Nous avons réalisé des développements en variété instable sur cinq systèmes différents. Ces réductions sont parsemées de singularités, mais prédisent correctement la nature de la bifurcation, que nous avons testée numériquement. Nous avons conjecturé une réduction exacte (obtenue via la forme normale Triple Zero) autour des états inhomogènes de l'équation de Vlasov. Ces résultats génériques pourraient être pertinents dans un contexte astrophysique. Les autres résultats s'appliquent aux phénomènes de synchronisation du modèle de Kuramoto pour les oscillateurs avec inertie et/ou interactions retardées
Long-range interacting systems are known to display particular statistical and dynamical properties.To describe their dynamical evolution, we can use kinetic equations describing their density in the phase space. This PhD thesis is divided into two distinct parts. The first part concerns our collaboration with an experimental team on a Magneto-Optical Trap. The physics of this widely-used device, operating with a large number of atoms, is supposed to display effective Coulomb interactions coming from photon rescattering. We have proposed experimental tests to highlight the analog of a Debye length, and its influence on the system response. The experimental realizations do not allow yet a definitive conclusion. In the second part, we analyzed the Vlasov and Kuramoto kinetic models. To study their infinite dimensional dynamics, we looked at bifurcations around unstable steady states. The goal was to obtain reduced equations describing the dynamical evolution. We performed unstable manifold expansions on five different kinetic systems. These reductions are in general not exact and plagued by singularities, yet they predict correctly the nature and scaling of the bifurcation, which we tested numerically. We conjectured an exact dimensional reduction (obtained using the Triple Zero normal form) around the inhomogeneous states of the Vlasov equation. These results are expected to be very generic and could be relevant in an astrophysical context. Other results apply to synchronization phenomena through the Kuramoto model for oscillators with inertia and/or delayed interactions

This work is concerned with the spatio-temporal structures that emerge when non-identical, diffusively coupled oscillators synchronize. It contains analytical results and their confirmation through extensive computer simulations. We use the Kuramoto model which reduces general oscillatory systems to phase dynamics. The symmetry of the coupling plays an important role for the formation of patterns. We have studied the ordering influence of an asymmetry (non-isochronicity) in the phase coupling function on the phase profile in synchronization and the intricate interplay between this asymmetry and the frequency heterogeneity in the system. The thesis is divided into three main parts. Chapter 2 and 3 introduce the basic model of Kuramoto and conditions for stable synchronization. In Chapter 4 we characterize the phase profiles in synchronization for various special cases and in an exponential approximation of the phase coupling function, which allows for an analytical treatment. Finally, in the third part (Chapter 5) we study the influence of non-isochronicity on the synchronization frequency in continuous, reaction diffusion systems and discrete networks of oscillators.
Die vorliegende Arbeit beschäftigt sich in Theorie und Simulation mit den raum-zeitlichen Strukturen, die entstehen, wenn nicht-identische, diffusiv gekoppelte Oszillatoren synchronisieren. Wir greifen dabei auf die von Kuramoto hergeleiteten Phasengleichungen zurück. Eine entscheidene Rolle für die Musterbildung spielt die Symmetrie der Kopplung. Wir untersuchen den ordnenden Einfluss von Asymmetrie (Nichtisochronizität) in der Phasenkopplungsfunktion auf das Phasenprofil in Synchronisation und das Zusammenspiel zwischen dieser Asymmetrie und der Frequenzheterogenität im System. Die Arbeit gliedert sich in drei Hauptteile. Kapitel 2 und 3 beschäftigen sich mit den grundlegenden Gleichungen und den Bedingungen für stabile Synchronisation. Im Kapitel 4 charakterisieren wir die Phasenprofile in Synchronisation für verschiedene Spezialfälle sowie in der von uns eingeführten exponentiellen Approximation der Phasenkopplungsfunktion. Schliesslich untersuchen wir im dritten Teil (Kap.5) den Einfluss von Nichtisochronizität auf die Synchronisationsfrequenz in kontinuierlichen, oszillatorischen Reaktions-Diffusionssystemen und diskreten Netzwerken von Oszillatoren.

Cette thèse est centrée sur l'analyse mathématique des solutions de deux modèles issus de la biologie. Le premier appartient à la famille des modèles de Kuramoto et décrit l'évolution d'une population d'oscillateurs de phase couplés en champ moyen. Le second est un modèle d'oscillation original, basé sur une perturbation singulière d'une équation différentielle retardée, introduit en particulier pour expliquer des phénomènes oscillatoires observés dans des réseaux de neurones, et qui fait l'objet d'analyse mathématique depuis les années 1980
Ln this report, we focus on mathematical analysis of two models coming from biology. The first model, a Kuramoto model, describes the time-evolution of a large number of mean-field coupled phase oscillators. The second one is an original oscillation model, based on a singuiar perturbation of a delayed differential equation. It had been introduced in relation with oscillatory patterns observed in neural networks, and it is subject fo mathematical analysis since the 1980's

This dissertation focuses on the further development of creating accurate numerical models of complex dynamical systems using the holistic discretisation technique [Roberts, Appl. Num. Model., 37:371-396, 2001]. I extend the application from second to fourth order systems and from only one spatial dimension in all previous work to two dimensions (2D). We see that the holistic technique provides useful and accurate numerical discretisations on coarse grids. We explore techniques to model the evolution of spatial patterns governed by pdes such as the Kuramoto-Sivashinsky equation and the real-valued Ginzburg-Landau equation. We aim towards the simulation of fluid flow and convection in three spatial dimensions. I show that significant steps have been taken in this dissertation towards achieving this aim. Holistic discretisation is based upon centre manifold theory [Carr, Applications of centre manifold theory, 1981] so we are assured that the numerical discretisation accurately models the dynamical system and may be constructed systematically. To apply centre manifold theory the domain is divided into elements and using a homotopy in the coupling parameter, subgrid scale fields are constructed consisting of actual solutions of the governing partial differential equation(pde). These subgrid scale fields interact through the introduction of artificial internal boundary conditions. View the centre manifold (macroscale) as the union of all states of the collection of subgrid fields (microscale) over the physical domain. Here we explore how to extend holistic discretisation to the fourth order Kuramoto-Sivashinsky pde. I show that the holistic models give impressive accuracy for reproducing the steady states and time dependent phenomena of the Kuramoto-Sivashinsky equation on coarse grids. The holistic method based on local dynamics compares favourably to the global methods of approximate inertial manifolds. The excellent performance of the holistic models shown here is strong evidence in support of the holistic discretisation technique. For shear dispersion in a 2D channel a one-dimensional numerical approximation is generated directly from the two-dimensional advection-diffusion dynamics. We find that a low order holistic model contains the shear dispersion term of the Taylor model [Taylor, IMA J. Appl. Math., 225:473-477, 1954]. This new approach does not require the assumption of large x scales, formerly absolutely crucial in deriving the Taylor model. I develop holistic discretisation for two spatial dimensions by applying the technique to the real-valued Ginzburg-Landau equation as a representative example of second order pdes. The techniques will apply quite generally to second order reaction-diffusion equations in 2D. This is the first study implementing holistic discretisation in more than one spatial dimension. The previous applications of holistic discretisation have developed algebraic forms of the subgrid field and its evolution. I develop an algorithm for numerical construction of the subgrid field and its evolution for 1D and 2D pdes and explore various alternatives. This new development greatly extends the class of problems that may be discretised by the holistic technique. This is a vital step for the application of the holistic technique to higher spatial dimensions and towards discretising the Navier-Stokes equations.

The human brain is as much fascinating as complicated: this is the reason why it has always captured scientists’ attention in several fields of research, from biology to medicine, from psychology to engineering. In this context various non-invasive technologies have been optimized in order to allow the measure of signals, able to describe brain activities. These data, derived from measurement methods that largely differ in their nature, have opened the door to new characterizations of this organ, that highlighted the main features of its operating principles. Brain signals indeed have revealed to be fluctuating during time, both during a specific task, and when we are not carrying on any activities. Furthermore, a selective coordination among different regions of the brain has emerged. As engineers, we are particularly attracted by the description of our brain as a graph, whose nodes and edges can be representative of several different elements, at distinct spatial scales (from single neurons to large brain areas). In the last decades, wide attention has been devoted to reproduce and explain the complex dynamics of the brain elements by means of computational models. Graph theory tools, as well as the design of population models, allow the exploitation of many mathematical tools, helpful to enlarge the knowledge of healthy and damaged brains functioning, by means of brain networks. Interestingly, the incapability of human brains to work properly in case of disease, has found to be correlated with dysfunctions in the activity of mitochondria, the organelles that produce large part of the cells’ energy. In particular, specific relationships have been reported among neurological diseases and impairments in mitochondrial dynamics, which refers to the continuous change in shape of mitochondria, by means of fusion and fission processes. Although the existing link between brain and mitochondria is still ambiguous and under debate, the huge amount of energy required by our brain to work properly suggests a larger mitochondrial-dependence of the brain than of the other organs. In this thesis we report the results of our research, aimed to investigate a few aspects of this complex brain-mitochondria relationship. We focus on mitochondrial dynamics and brain network, as well as on suitable mathematical models used to describe them. Specifically, the main topics handled in this work can be summarized as follows. Population models for mitochondrial dynamics. We propose a modified preypredator non-linear population model to simulate the main processes, which take part in the mitochondrial dynamics, and the ones that are strongly related to it, without neglecting the energy production process. We present two possible setups, which differ in the inclusion of a feedback link between the available energy and the formation of new mitochondria. We discuss their dynamics, and their potential in reproducing biological behaviors. Brain signals: comparison of datasets derived through different technologies. We analyze two different datasets of brain signals, recorded with various methods (functional magnetic resonance imaging, fMRI, and magnetoencephalography, MEG), both in condition of no activity and during an attentional task. The aim of the analysis is twofold: the investigation of the spontaneous activity of the brain, and the exploration of possible relationships between the two different techniques. Brain network: a Kuramoto-based description. We analyze empirical brain data by means of their oscillatory features, with the purpose of highlighting the characteristics that a computational phase-model should be able to reproduce. Hence, we use a modified version of the classic Kuramoto model to reproduce the empirical oscillatory characteristics. Analysis and control of Kuramoto networks. Most of the theoretical contribution of this thesis refers to analytical results on Kuramoto networks. We analyze the topological and intrinsic conditions required to achieve a desired pattern of synchronization, represented by fully or clustered synchronized configuration of oscillators.
Il cervello umano è tanto affascinante quanto complesso: questo è il motivo per cui ha sempre attirato l’attenzione degli scienziati in molteplici ambiti di ricerca, dalla biologia alla medicina, dalla psicologia all’ingegneria. In questo contesto, diverse tecnologie non invasive sono state ottimizzate per permettere la misurazione di segnali, atti a descrivere l’attività cerebrale. Questi dati, derivanti da metodi di misura che differiscono molto nella loro natura, hanno aperto la porta a nuove descrizioni di quest’organo, che a loro volta hanno evidenziato le caratteristiche principali delle sue funzionalità. In particolare, è emerso come i segnali cerebrali fluttuino nel tempo, sia durante lo svolgimento di una particolare operazione, sia nei periodo di completa inattività. Inoltre, è stata individuato un coordinamento specifico e selettivo tra le diverse regioni del cervello. In quanto ingegneri, la nostra attenzione è principalmente focalizzata sulla descrizione del cervello umano come un grafo, i cui nodi ed archi possono assumere il ruolo di elementi diversi, a seconda della specifica scala spaziale di interesse (siano essi descrittivi di singoli neuroni o intere aree cerebrali). Negli ultimi decenni, un notevole impegno è stato applicato per riprodurre e spiegare le complesse dinamiche degli elementi cerebrali attraverso l’utilizzo di modelli matematici. Infatti, la teoria dei grafi e il design di modelli di popolazione permettono lo sfruttamento di molti strumenti matematici, utili per ampliare la conoscenza del funzionamento del nostro cervello, sia in stato di salute, sia in malattia, attraverso la definizione di reti cerebrali. È affascinante come l’incapacità del cervello umano di operare correttamente in caso di malattia sembri essere correlato ad alcune disfunzioni dell’attività dei mitocondri, gli organelli che producono la maggiorparte dell’energia cellulare. In particolare, sono state riportate delle relazioni specifiche tra alcune malattie neurologiche e il danneggiamento della dinamica mitocondriale, ossia il continuo cambio di forma e lunghezza dei mitocondri, tramite i processi di fusione e fissione. Nonostante l’effettiva esistenza di un collegamento tra il cervello e i mitocondri sia ancora ambiguo ed oggetto di dibattito tra gli scienziati, la considerevole quantità di energia richiesta dal cervello umano per lavorare correttamente suggerisce che il cervello, più degli altri organi, sia dipendente dall’attività mitocondriale. In questo lavoro di tesi sono riportati i risultati della nostra ricerca, atta ad investigare alcuni aspetti di questa complessa relazione tra cervello e mitocondri. Ci siamo quindi concentrati sulla dinamica mitocondriale e sul concetto di rete cerebrale, oltre che sui modelli matematici idonei alla loro descrizione matematica. Qui di seguito sono riportati e riassunti i principali argomenti trattati in questo manoscritto. Modelli di popolazione per la dinamica mitocondriale. Proporremo un modello di popolazione non lineare ispirato ai modelli preda-predatore per simulare tutti i processi principali che prendono parte alla dinamica mitocondriale e quelli che sono fortemente connessi ad essa, incluso il processo di produzione di energia. Nello specifico, presenteremo due possibili configurazioni, che si differenziano nella presenza o meno di un collegamento in retroazione tra la quantità di energia libera disponibile e la formazione di nuovi mitocondri. Verrà quindi discussa la dinamica di entrambe le configurazioni e la loro capacità di riprodurre i comportamenti biologici osservati nella realtà. Segnali cerebrali: confronto tra dataset ottenuti tramite tecnologie differenti. Riporteremo l’analisi di due dataset di segnali cerebrali registrati con diversi metodi (risonanza magnetica funzionale, fMRI, e magnetoencefalografia, MEG), sia in assenza di attività, sia durante lo svolgimento di un compito di attenzione. Quest’analisi ha un duplice obiettivo: lo studio dell’attività cerebrale spontanea e l’esplorazione di possibile relazioni esistenti tra le due diverse tecniche di misura. Rete cerebrale: una descrizione basata sul modello Kuramoto. Ci soffermeremo sull’analisi di dati cerebrali empirici evidenziando le loro proprietà oscillatorie, con lo scopo di sottolinearne le caratteristiche che un modello matematico di fase dovrebbe essere in grado di riprodurre. Quindi, riporteremo una versione modificata del modello Kuramoto classico che abbiamo utilizzato per riprodurre le caratteristiche oscillatorie osservate empiricamente. Analisi e controllo di reti di Kuramoto. La maggior parte del contributo teorico di questo lavoro di tesi comprende alcuni risultati analitici riguardo reti di oscillatori Kuramoto. Riporteremo quindi l’analisi atta a determinare le condizioni intrinseche e topologiche necessarie per ottenere un desiderato pattern di sincronizzazione, relativo sia ad una configurazione di oscillatori interamente sincronizzata, sia sincronizzata a gruppi.

In questo elaborato viene presentato un algoritmo Consensus-Based per l'ottimizazione vincolata a ipersuperfici. Il metodo consiste in una tecnica di ottimizzazione di tipo metaeuristico dove un insieme di particelle interagenti si muove secondo un meccanismo che unisce movimenti deterministici e stocastici per creare un consenso attorno ad un luogo del dominio dove è presente un minimo della funzione. La dinamica è governata da un sistema di SDE ed è studiata attraverso il formalismo della teoria cinetica per modelli di particelle interagenti. Innanzitutto, viene dimostrato che il sistema è ben posto e viene formalmente derivato il suo limite di campo medio. Il meccanismo di consenso viene poi studiato analiticamente e computazionalmente soffermandosi sulle difficoltà che il rispetto del vincolo comporta. Infine, vengono condotti esperimenti su classiche funzioni test.

The understanding of nonequilibrium phenomena, of fundamental importance in statistical physics, has great implications for many physical, chemical, and biological systems. Such phenomena are observed almost everywhere in the natural world. These phenomena are characterized by complicated spatiotemporal evolution. To explore nonequilibrium phenomena we often study simple model systems that embody their essential characteristics. In this thesis, we report the results of our investigations of the statistically steady state properties of three one-dimensional models: multispecies asymmetric simple exclusion processes, the Kuramoto- Sivashinsky equation, and the Burgers equation. The thesis is divided into two parts: Part I and Part II. In Chapters 2–5 of Part I, we present our results for multispecies exclusion models, principally the phase diagrams and statistical properties of their nonequilibrium steady state (NESS). We list below abstracts of these chapters. • In Chapter 2, we consider a multispecies ASEP (mASEP) on a one-dimensional lattice with semipermeable boundaries in contact with particle reservoirs. The mASEP involves ¹2𝑟 ¸1º species of particles: 𝑟 species of positive charges and their negative counterparts as well as vacancies. At the boundaries, a species can replace or be replaced by its negative counterpart. We derive the exact nonequilibrium phase diagram for the system in the long time limit. We find two new phenomena in certain regions of the phase diagram: dynamical expulsion when the density of a species becomes zero throughout the system, and dynamical localization when the density of a species is nonzero only within an interval far from the boundaries. We give a complete explanation of the macroscopic features of the phase diagram using what we call nested fat shocks. • In Chapter 3, we study an asymmetric exclusion process with two species and vacancies on an open one-dimensional lattice called the left-permeable ASEP (LPASEP). The left boundary is permeable for the vacancies but the right boundary is not. We find a matrix product solution for the stationary state and the exact stationary phase diagram for the densities and currents. By calculating the density of each species at the boundaries, we find further structure in the stationary phases. In particular, we find that the slower species can reach and accumulate at the far boundary, even in phases where the bulk density of these particles approaches zero. • In Chapter 4, we study a multispecies generalization of the model in Chapter 3. We determine all phases in the phase diagram using an exact projection to the LPASEP solved earlier. In most phases, we observe the phenomenon of dynamical expulsion of one or more species. We explain the density profiles in each phase using interacting shocks. This explanation is corroborated by simulations. • In Chapter 5, we investigate a multispecies generalization of the single-species asymmetric simple exclusion process defined on an open one-dimensional, finite lattice connected to particle reservoirs. At the boundaries, a species can be replaced with any other species. We devise an exact projection scheme to find the phase diagram in terms of densities and currents of all species. In most of the phases, one or more species are absent in the system due to dynamical expulsion. We observe shocks as well in some regions of the phase diagram. We explain the density profiles using a generalized shock structure that is substantiated by numerical simulations. In Chapters 7 and 8 of Part II, we study the statistical properties of turbulent, but statistically steady, states of the Kuramoto-Sivashinsky and the Burgers equations in one dimension. Our main results are summarized below. • In Chapter 7, we investigate the long time and large system size properties of the onedimensional Kuramoto-Sivashinsky equation. Tracy-Widom and Baik-Rains distributions appear as universal limit distributions for height fluctuations in the one-dimensional Kardar-Parisi-Zhang (KPZ) stochastic partial differential equation (PDE). We obtain the same universal distributions in the spatiotemporally chaotic, nonequilibrium, but statistically steady state of KS deterministic PDE, by carrying out extensive pseudospectral direct numerical simulations to obtain the spatiotemporal evolution of the KS height profile h(x,t) for different initial conditions. We establish, therefore, that the statistical properties of the one-dimensional (1D) KS PDE in this state are in the 1D KPZ universality class. • In Chapter 8, we study the statistical properties of decaying turbulence in the onedimensional Burgers equation, in the vanishing-viscosity limit; we start with random initial conditions, whose energy spectra have simple functional dependences on the wavenumber k: E_0(k) = A \mathcal{E}(k) exp[ - 2 k^2 / k^2_c ] , where A is a positive real number, and k_c is a cutoff wavenumber. The simplest case is the single-power law \mathcal{E}(k) = k^{n}. We focus here on the case of the Gaussian laws which are characterized by E_0(k) = exp[ - 2 (k-k_c)^2 / k^2_c +2 k^2 / k^2_c]; in addition, we consider initial spectra which are combinations of either two or four single-power law spectral regions. For all these initial conditions, we systematize (a) the temporal decay of the total energy, (b) the rich temporal evolution of the energy spectrum, and (c) the spatiotemporal evolution of the velocity field. We present our results in the context of earlier studies of this problem.