Apresentamos uma versão hierárquica do modelo de Ising para mostrar a equivalência entre os modelos ferromagnético em campo aleatório e antiferromagnético diluído em campo uniforme. A equivalência está baseada no fato de que transformações do grupo de renormalização quando aplicadas ao modelo antiferromagnético diluído produzam, como efeito combinado do campo externo e da diluição. um campo externo aleatório na nova escala. Verificamos também que quando não se leva em conta contornos dentro de contornos os modelos analisados apresentam transição de fase para dimensão d maior ou igual a dois. O método usado foi a combinação dos argumentos de Peierls, Imry e Ma as transformações da Teoria do Grupo de Renormalização que na versão hierárquica tornam-se um processo exato. / We are presenting a hierarchical version of Ising modal to show an equivalence between the ferromagnetic model in a random magnetic field and dilute antiferromagnetic modal in a uniform magnetic field. The equivalence is based on the fact that a dilute antiferromagnetic in a uniform magnetic field generates under a renormalization group transformation a random magnetic field. We also verify that when we do not take into account contours inside contours the models analyzed show phase transition for dimension d greater than or equal to two. The method used consist of combination of Peierls, Imry and Ma arguments and the Renormalization Group Transformation, which in the hierarchical approach becomes an exact process.

Even simple observation of stock price graphs can reveal dominant patterns. In our work, we will refer to such re-occurring, dominant patterns as “coherent structures”, a term borrowed from the theory of turbulence in fluid dynamics. Stock price performance exhibits coherent structures, which by definition make it non-random, although a price-versus-time graph might seem totally chaotic to the naked eye. A novel low-order modeling technique for systems that are seemingly random has been developed. Though stock market data is used for the formulation and verification of the technique, its application in diverse fields is verified. The dissertation discusses some of the salient features of the novel technique along with a dynamic system analogy. The technique reduces many of the significant limitations associated with traditional methods like Fourier analysis and digital filters. Application of the technique to a nonlinear dynamical system and meteorological data are presented as well as the primary application on stock market securities.

Apresentamos uma versão hierárquica do modelo de Ising para mostrar a equivalência entre os modelos ferromagnético em campo aleatório e antiferromagnético diluído em campo uniforme. A equivalência está baseada no fato de que transformações do grupo de renormalização quando aplicadas ao modelo antiferromagnético diluído produzam, como efeito combinado do campo externo e da diluição. um campo externo aleatório na nova escala. Verificamos também que quando não se leva em conta contornos dentro de contornos os modelos analisados apresentam transição de fase para dimensão d maior ou igual a dois. O método usado foi a combinação dos argumentos de Peierls, Imry e Ma as transformações da Teoria do Grupo de Renormalização que na versão hierárquica tornam-se um processo exato. / We are presenting a hierarchical version of Ising modal to show an equivalence between the ferromagnetic model in a random magnetic field and dilute antiferromagnetic modal in a uniform magnetic field. The equivalence is based on the fact that a dilute antiferromagnetic in a uniform magnetic field generates under a renormalization group transformation a random magnetic field. We also verify that when we do not take into account contours inside contours the models analyzed show phase transition for dimension d greater than or equal to two. The method used consist of combination of Peierls, Imry and Ma arguments and the Renormalization Group Transformation, which in the hierarchical approach becomes an exact process.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第20899号 / 理博第4351号 / 新制||理||1624(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)准教授 福間 將文, 教授 川合 光, 教授 青木 慎也 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

This dissertation is devoted to investigation of quantum chaos in the Sachdev-Ye-Kitaev (SYK) and supersymmetric SYK models. First, a unified minimal scheme is developed to classify quantum chaos in the SYK and supersymmetric SYK models and also work out the structure of the energy levels in one periodic table. The SYK with even q-body or supersymmetric SYK with odd q-body interaction, with N even or odd number of sites, are put on an equal footing in the minimal Hilbert space; N (mod 8), q (mod 4) double Bott periodicity, and a reflection relation are identified. Then, exact diagonalizations are performed to study both the bulk energy level statistics and hard-edge behaviors. Excellent agreements between the exact diagonalization results and the symmetry classifications are demonstrated. This compact and systematic method can be transformed to map out more complicated periodic tables of SYK models with more degrees of freedom, tensor models, or symmetry protected topological phases.

L'urne de Polya est l'exemple typique de processus stochastique avec renforcement. La limite presque sûre (p.s.) en temps existe, est aléatoire et non dégénérée. L'urne de Friedman est une généralisation naturelle dont la limite (proportion asymptotique en temps) n'est plus aléatoire. De nombreux modèles aléatoires sont fondés sur des processus de renforcement comme pour la conception d'essais cliniques au design adaptatif, en économie, ou pour des algorithmes stochastiques à des fins d'optimisation ou d'estimation non paramétrique. Dans ce mémoire, inspirés par de nombreux articles récents, nous introduisons une nouvelle famille de systèmes (finis) de processus de renforcement où l'interaction se traduit par un phénomène de renforcement collectif additif, de type champ moyen. Les deux taux de renforcement (l'un spécifique à chaque composante, l'autre collectif et commun à toutes les composantes) sont possiblement différents. Nous prouvons deux types de résultats mathématiques. Différents régimes de paramètres doivent être considérés : type de la règle (brièvement, Polya/Friedman), taux du renforcement. Nous prouvons l'existence d'une limite p.s. coommune à toutes les composantes du système (synchronisation). La nature de la limite (aléatoire/déterministe) est étudiée en fonction du régime de paramètres. Nous étudions également les fluctuations en prouvant des théorèmes centraux de la limite. Les changements d'échelle varient en fonction du régime considéré. Différentes vitesses de convergence sont ainsi établies. / The Polya urn is the paradigmatic example of a reinforced stochastic process. It leads to a random (non degenerated) almost sure (a.s.) time-limit.The Friedman urn is a natural generalization whose a.s. time-limit is not random anymore. Many stochastic models for applications are based on reinforced processes, like urns with their use in adaptive design for clinical trials or economy, stochastic algorithms with their use in non parametric estimation or optimisation. In this work, in the stream of previous recent works, we introduce a new family of (finite) systems of reinforced stochastic processes, interacting through an additional collective reinforcement of mean field type. The two reinforcement rules strengths (one componentwise, one collective) are tuned through (possibly) different rates. In the case the reinforcement rates are like 1/n, these reinforcements are of Polya or Friedman type as in urn contexts and may thus lead to limits which may be random or not. We state two kind of mathematical results. Different parameter regimes needs to be considered: type of reinforcement rule (Polya/Friedman), strength of the reinforcement. We study the time-asymptotics and prove that a.s. convergence always holds. Moreover all the components share the same time-limit (synchronization). The nature of the limit (random/deterministic) according to the parameters' regime is considered. We then study fluctuations by proving central limit theorems. Scaling coefficients vary according to the regime considered. This gives insights into the different rates of convergence.