The phase transitions of a newly proposed torsion X-Y model, are studied with molecular dynamics. ForJ3 >0, the influence from J1 term is similar to the term.We found the Torsion X-Y Model and X-Y Model or Coupled X-Y Model all have the Kosterlitz-Thouless transition. (KT) We also confirm that the KT transition is a second order transition , The distribution of angle £c start from dis-ordered to well-ordered. KT starts first before the randomly distributed £c shows preference and ends when the preference is merged. For the J3 <0 case, the KT is also found in J3=-0.0167 and J3=-0.0334 The temperature for negative J3 is lower then that for positive J3 due to the resistant force to £c ordering from the coupled interaction.

Thèse de doctorat : Physique Chimie de la Matière et des Matériaux : Nancy 1 : 2008. / Titre provenant de l'écran-titre.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 55-58). Also available in electronic version. Access restricted to campus users.

No description available.

Grand-canonical inverse-temperature calculations of a single mode Bose-Hubbard model are presented, using the Gaussian phase space representation. Simulation of 100 particles is achieved in the ground state, having started with a low-particle-number thermal state. A preliminary foray into a three-mode lattice is made, but the sampling error appears to be too large for the simple approach taken here to be successful in larger systems. The quantum (real-time) dynamics of a one-dimensional Bose gas with two-particle losses are investigated. The Positive-P equations for this system are unstable, and this causes Positive-P simulations to `die' after a certain amount of time. Gauges are used to (sometimes partially) stabilise the equations. The effects on simulation times of various gauges, branching methods, and non-square diffusion matrix factorisations on simulation times are investigated. Despite the absence of repulsive inter-particle interactions, it is observed that $g^{(2)}$ rises above 1 at a finite particle separation. A phase space method for spin systems is introduced, based on SU(2) coherent states. This is essentially a spin analogue of the Positive-P method. The system of stochastic differential equations arising out of this method require weighted averages to be taken, and the weights can vary exponentially, leading to inefficient sampling. For the case of the Ising model, a transform is made to a set of equations which relaxes (in a dummy time variable) to the partition function at a given temperature, and allows unweighted ensemble averages to be taken. This allows accurate simulations to be achieved at a range of temperatures, with nearest-neighbour correlation functions agreeing with theory. This represents a proof of principle for the use of stochastic phase space methods in spin systems, and furthermore the method should be suited to open spin systems, at least for a small number of qubits.

Th. 3e cycle--Sci. des matér.--Nancy--I.N.P.L., 1984.

O conceito de heterogeneidade de tamanhos de domínios (Heq), definido como o número de tamanhos distintos de domínios existentes em determinada configuração de um sistema, foi recentemente introduzido no contexto do modelo de percolação explosiva. Além de introduzir um novo expoente de escala, o mesmo se mostrou útil em outros problemas da mecânica estatística de equilíbrio, como o de percolação aleatória, bem como nos modelos de Ising e Potts. Neste trabalho, aplicamos e medimos esta quantidade em situações fora do equilíbrio. Em particular, após submetermos os modelos de Ising e Potts a um súbito resfriamento, a partir de um estado de equilíbrio de alta temperatura, para uma temperatura crítica ou subcrítica, T > Tc, medimos a evolução temporal de H(t). Mostramos que o comportamento para tempos grandes é uma lei de potência com expoentes diferentes para os casos crítico e subcrítico. Adicionalmente, o comportamento para tempos pequenos apresenta ainda um máximo no valor de H(t), quando a temperatura inicial é T0 → Ѡ. Apresentamos um extenso conjunto de dados de simulação que apoiam essas conclusões e discutimos perspectivas futuras, com o objetivo de tentar compreender melhor o comportamento de H(t). / The concept of domain size heterogeneity (Heq), the number of distinct domain sizes occurring in a given con guration, was recently introduced in the context of explosive percolation. Besides introducing a new scaling exponent, it was shown to be useful in other classical equilibrium statistical mechanics problems, like random percolation, and the Ising and Potts models. Here we apply and measure this quantity for out of equilibrium situations. In particular, after quenching the Ising and Potts models from a high temperature equilibrium state, T > Tc, to a critical or subcritical temperature, T Tc, we measure the time evolution of H(t). We show that the long time behavior is power law with di erent exponents for critical and subcritical coarsening. Moreover, the short time behavior also presents a surprising maximum of H(t) when the initial temperature is T0 → Ѡ. We present extensive simulation data supporting these conclusions and discuss future perspectives, in order to help understand the overall behavior of H(t).

Neurons, the building blocks of the brain, are an astonishingly capable type of cell. Collectively they can store, manipulate and retrieve biologically important information, allowing animals to learn and adapt to environmental changes. This universal adaptability is widely believed to be due to plasticity: the readiness of neurons to manipulate and adjust their intrinsic properties and strengths of connections to other cells. It is through such modifications that associations between neurons can be made, giving rise to memory representations; for example, linking a neuron responding to the smell of pancakes with neurons encoding sweet taste and general gustatory pleasure. However, this malleability inherent to neuronal cells poses a dilemma from the point of view of stability: how is the brain able to maintain stable operation while in the state of constant flux? First of all, won’t there occur purely technical problems akin to short-circuiting or runaway activity? And second of all, if the neurons are so easily plastic and changeable, how can they provide a reliable description of the environment? Of course, evidence abounds to testify to the robustness of brains, both from everyday experience and scientific experiments. How does this robustness come about? Firstly, many control feedback mechanisms are in place to ensure that neurons do not enter wild regimes of behaviour. These mechanisms are collectively known as homeostatic plasticity, since they ensure functional homeostasis through plastic changes. One well-known example is synaptic scaling, a type of plasticity ensuring that a single neuron does not get overexcited by its inputs: whenever learning occurs and connections between cells get strengthened, subsequently all the neurons’ inputs get downscaled to maintain a stable level of net incoming signals. And secondly, as hinted by other researchers and directly explored in this work, networks of neurons exhibit a property present in many complex systems called sloppiness. That is, they produce very similar behaviour under a wide range of parameters. This principle appears to operate on many scales and is highly useful (perhaps even unavoidable), as it permits for variation between individuals and for robustness to mutations and developmental perturbations: since there are many combinations of parameters resulting in similar operational behaviour, a disturbance of a single, or even several, parameters does not need to lead to dysfunction. It is also that same property that permits networks of neurons to flexibly reorganize and learn without becoming unstable. As an illustrative example, consider encountering maple syrup for the first time and associating it with pancakes; thanks to sloppiness, this new link can be added without causing the network to fire excessively. As has been found in previous experimental studies, consistent multi-neuron activity patterns arise across organisms, despite the interindividual differences in firing profiles of single cells and precise values of connection strengths. Such activity patterns, as has been furthermore shown, can be maintained despite pharmacological perturbation, as neurons compensate for the perturbed parameters by adjusting others; however, not all pharmacological perturbations can be thus amended. In the present work, it is for the first time directly demonstrated that groups of neurons are by rule sloppy; their collective parameter space is mapped to reveal which are the sensitive and insensitive parameter combinations; and it is shown that the majority of spontaneous fluctuations over time primarily affect the insensitive parameters. In order to demonstrate the above, hippocampal neurons of the rat were grown in culture over multi-electrode arrays and recorded from for several days. Subsequently, statistical models were fit to the activity patterns of groups of neurons to obtain a mathematically tractable description of their collective behaviour at each time point. These models provide robust fits to the data and allow for a principled sensitivity analysis with the use of information-theoretic tools. This analysis has revealed that groups of neurons tend to be governed by a few leader units. Furthermore, it appears that it was the stability of these key neurons and their connections that ensured the stability of collective firing patterns across time. The remaining units, in turn, were free to undergo plastic changes without risking destabilizing the collective behaviour. Together with what has been observed by other researchers, the findings of the present work suggest that the impressively adaptable yet robust functioning of the brain is made possible by the interplay of feedback control of few crucial properties of neurons and the general sloppy design of networks. It has, in fact, been hypothesised that any complex system subject to evolution is bound to rely on such design: in order to cope with natural selection under changing environmental circumstances, it would be difficult for a system to rely on tightly controlled parameters. It might be, therefore, that all life is just, by nature, sloppy.

Domínios formados durante a evolução de misturas possuem grande importância tanto teórica quanto experimental. Diversos estudos das propriedades de crescimento de domínios podem ser vistos no contexto de espumas, tecidos celulares, domínios magnéticos, supercondutores, absorção de átomos em superfícies, etc. Particularmente, na ciência metalúrgica e de superfícies, entender a forma* das microestruturas policristalinas e suas respectivas evoluções temporais e importante na determinação das propriedades do material. 0 modelo de Potts permite representar a estrutura multicelular dos sistemas mencionados e, por esta razão, e muito empregado em seus estudos. Nesta tese apresentamos os resultados do estudo do ordenamento de fases dinâmico do modelo de Potts puro e com desordem ferromagnética fraca, do ponto de vista geométrico, através de simulações computacionais. Basicamente, estudamos a distribuição das áreas dos hulls do modelo com q > 2 estudos, apos ser submetido a um súbito resfriamento a partir da fase de alta temperatura (paramagnética) para dentro da fase ordenada (ferromagnética). Nesta fase, domínios com diferentes orientações se formam devido à intensidade das interações locais. A evolução temporal de cada domínio e regida basicamente pela curvatura da interface e a lei de crescimento depende, em geral, de fatores como a conservação (ou não) do parâmetro de ordem, da presença de desordem e da dimensão do parâmetro de ordem. lima vez que a solução analítica para a distribuição das áreas dos hulls obtida para o modelo de Ising (q = 2) não pode ser facilmente extrapolada para o modelo de Potts corn q > 2, nossa analise e baseada em simulações numéricas. Surpreendentemente, alguns resultados permanecem validos (como por exemplo, quando a transição e continua e o sistema esta equilibrado em T, antes do quench). Além das distribuições das áreas dos hulls para vários valores de q e diferentes condições iniciais, apresentamos uma visão geral, geométrica, do processo de crescimento de domínios no modelo de Potts, tanto para o modelo puro quanto na presença de desordem ferromagnética. / Domains formed during the evolution of mixtures are of both theoretical and technological importance, applications including foams, cellular tissues, superconductors, magnetic domains, adsorbed atoms on surfaces, etc. In particular, in metallurgy and surface science, understanding the formation of the polycrystalline microstructure, and its time evolution are important in determining the material properties. The Potts model, being able to represent the multicellular structure of these systems, is widely used in their study. In this thesis we present results for the phase ordering dynamics of the Potts model with and without weak quenched disorder, from a geometrical point of view, through computer simulations. Basically we studied the hull-enclosed area distributions of the model with q > 2 states, after a sudden quench from the high temperature phase (paramagnetic) into the ordered phase (ferromagnetic). In this phase, domains with different orientations are formed due to the strenght of local interactions. The temporal evolution of a single domain is essentially ruled by curvature-driven processes, and the growth law depends, in general, on features such like the conservation (or not) of the order parameter, the presence of quenched disorder, and the dimension of the order parameter. Once the analytical solution for the hull-enclosed areas obtained for the Ising model (q = 2) cannot be easily extrapolated to the q > 2 Potts model, our analysis is based on numerical simulations. Surprinsingly, some of the results remain valid (as, for example, when the equilibrium state before the quench is the second-order transition critical temperature). Besides the hull-enclosed areas, we present an overall, geometric description of the domain growth process for the Potts model, both with and without ferromagnetic disorder.

FREIRE, M. de M. Teoria de funções de Green para uma impureza isolada localizada intersticialmente em sistemas ferromagnéticos. 2017. 140 f. Tese (Doutorado em Física) – Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2017. / Submitted by Giordana Silva (giordana.nascimento@gmail.com) on 2017-04-03T22:07:25Z No. of bitstreams: 1 2017_tese_mdmfreire.pdf: 7628225 bytes, checksum: e3a2dea720868776f72333124b7437b6 (MD5) / Approved for entry into archive by Giordana Silva (giordana.nascimento@gmail.com) on 2017-04-03T22:08:00Z (GMT) No. of bitstreams: 1 2017_tese_mdmfreire.pdf: 7628225 bytes, checksum: e3a2dea720868776f72333124b7437b6 (MD5) / Made available in DSpace on 2017-04-03T22:08:00Z (GMT). No. of bitstreams: 1 2017_tese_mdmfreire.pdf: 7628225 bytes, checksum: e3a2dea720868776f72333124b7437b6 (MD5) Previous issue date: 2017 / A Green’s function formalism is used to calculate the expectrum of excitations associated with an interstitial magnetic impurity in different ferromagnetic structures described by the Ising and Heisenberg models. In the chapter 3 the non-resonant excitations of the system due to impurity (i.e, the defect modes outside the region of the bulk and surface spin waves) and the resonant excitations (the defect modes inside the region of the bulk and surface spin waves) are calculated numerically for the high-temperature phase. Two situations are analysed, depending on the position of the impurity: the impurity is on the surface (N = 1) and the impurity is in the bulk region (N ≥ 2). In the others chapters we use the model Ising/Heisenberg (where we can go from Heisenberg model to Ising model, by controlling the value of a parameter λ) to describe the following systems: ferromagnet with an infinite square lattice (Chap. 4), ferromagnet with an infinite face-centered square lattice (Chap. 5), ferromagnet with an infinite body-centered cubic lattice (Chap. 6) and ferromagnet with an infinite honey-comb lattice (Chap. 7), all the systems with a magnetic interstitial impurity. For the first tree cases, only the optical defect modes are calculated, and for the last one, only the acoustic modes are calculated. / Um formalismo da função de Green é usado para calcular o espectro de excitações associadas com uma impureza magnética localizada intersticialmente em diferentes estruturas ferromagnéticas descritas pelo modelo de Ising e de Heisenberg. No capítulo 3, descrevemos um ferromagneto de rede cúbica simples semi-infinita através do modelo de Ising. Neste caso, as excitações não-ressonantes (isto é, os modos de defeito fora da região das ondas de spin de volume e de superfície) e as excitações ressonantes (os modos de defeito dentro da região das ondas de spin de volume) são calculadas numericamente para a fase de alta-temperatura. Duas situações são analisadas, dependendo da posição da impureza em relação a seus vizinhos: a impureza está na superfície; a impureza está na região de volume. Nos demais capítulos, usamos o modelo de Heisenberg/Ising (onde passamos do modelo de Heisenberg para o de Ising através do controle de um parâmetro) para descrever os seguintes sistemas: ferromagneto de rede quadrada infinita (capítulo 4), ferromagneto de rede quadrada centrada infinita (capítulo 5), ferromagneto de rede cúbica de corpo centrado infinita (capítulo 6) e rede favo de mel infinita (capítulo 7), todos contendo uma impureza magnética localizada intersticialmente. Nos três primeiros casos, são calculados apenas os modos de defeito acima da banda de volume do material puro (modos ópticos). No capítulo 7, são analisados apenas os modos de defeito abaixo da banda de volume do material puro (modos acústicos).