In the past decade, aggressive scaling of transistor feature size has been a primary force driving higher Static Random Access Memory (SRAM) integration density. Due to the scaling, nanometer SRAM designs are getting more and more stability issues. The traditional way of analyzing stability is the Static Noise Margins (SNM). However, SNM has limited capability to capture critical nonlinearity, so it becomes incapable of characterizing the key dynamics of SRAM operations with induced soft-error. This thesis defines new stability margin metrics using a system-theoretic approach. Nonlinear system theories will be applied rigorously in this work to construct new stability concepts. Based on the phase portrait analysis, soft-error can be explained using bifurcation theory. The state flipping requires a minimum noise current (Icritical) and time (Tcritical). This work derives Icritical analytically for simple L1 model and provides design insight using a level one circuit model, and also provides numerical algorithms on both Icritical and Tcritial for higher a level device model. This stability analysis provides more physical characterization of SRAM noise tolerance property; thus has potential to provide needed yield estimation.

This thesis presents two dimensional discrete dynamical system, the extended standard family of maps, which approximates homoclinic bifurcations of continuous dissipative systems. The main subject of study is the problem of separatrix splitting which was first discovered by Poincaré in the context of the n-body problem. Separatrix splitting leads to chaotic behaviour of the system on exponentially small region in parameter space. To estimate the size of the region the dissipative map is extended to complex variables and approximated by differential equation on a specific domain. This approach was proposed by Lazutkin to study separatrix splitting for Chirikov’s standard map. Furthermore the complex nearly periodic function is used to estimate the width of the exponentially small region where chaos prevails and the map is related to the semistandard map. Numerical computations require solving complex differential equation and provide the constants involved in the asymptotic formula for the size of the region. Another problem studied in this thesis is the prevalence of resonance for the dissipative standard map on a specific invariant set, which for one dimensional map corresponds to a circle. The regions in parameter space where periodic behaviour occurs on the invariant set is known as Arnold tongues. The width of Arnold tongue is studied and numerical results obtained by iterating the map and solving differential equation are related to the semistandard map.

Auditory physiology is nearly unique in the human body because of its small-diameter neurons. When considering a single node on one neuron, the number of channels is very small, so ion fluxes exhibit randomness. Hodgkin and Huxley, in 1952, set forth a system of Ordinary Differential Equations (ODEs) to track the flow of ions in a squid motor neuron, based on a circuit analogy for electric current. This formalism for modeling is still in use today and is useful because coefficients can be directly measured. To measure auditory properties of Firing Efficiency (FE) and Post Stimulus Time (PST), we can simply measure the depolarization, or "upstroke," of a node. Hence, we reduce the four-dimensional squid neuron model to a two-dimensional system of ODEs. The stochastic variable m for sodium activation is allowed a random walk in addition to its normal evolution, and the results are drastic. The diffusion coefficient, for spreading, is inversely proportional to the number of channels; for 130 ion channels, D is closer to 1/3 than 0 and cannot be called negligible. A system of Partial Differential Equations (PDEs) is derived in these pages to model the distribution of states of the node with respect to the (nondimensionalized) voltage v and the sodium activation gate m. Initial conditions describe a distribution of (v,m) states; in most experiments, this would be a curve with mode at the resting state. Boundary conditions are Robin (Natural) boundary conditions, which gives conservation of the population. Evolution of the PDE has a drift term for the mean change of state and a diffusion term, the random change of state. The phase plane is broken into fired and resting regions, which form basins of attraction for fired and resting-state fixed points. If a stimulus causes ions to flow from the resting region into the fired region, this rate of flux is approximately the firing rate, analogous to clinically measuring when the voltage crosses a threshold. This gives a PST histogram. The FE is an integral of the population over the fired region at a measured stop time after the stimulus (since, in the reduced model, when neurons fire they do not repolarize). This dissertation also includes useful generalizations and methodology for turning other ODEs into PDEs. Within the HH modeling, parameters can be switched for other systems of the body, and may present a similar firing and non-firing separatrix (as in Chapter 3). For any system of ODEs, an advection model can show a distribution of initial conditions or the evolution of a given initial probability density over a state space (Chapter 4); a system of Stochastic Differential Equations can be modeled with an advection-diffusion equation (Chapter 5). As computers increase in speed and as the ability of software to create adaptive meshes and step sizes improves, modeling with a PDE becomes more and more efficient over its ODE counterpart.

Vector field topology has a long tradition as a visualization tool. The separatrices segment the domain visually into canonical regions in which all streamlines behave qualitatively the same. But application scientists often need more than just a nice image for their data analysis, and, to best of our knowledge, so far no workflow has been proposed to extract the critical points, the associated separatrices, and then provide the induced segmentation on the data level. We present a workflow that computes the segmentation of the domain of a 2D vector field based on its separatrices. We show how it can be used for the extraction of quantitative information about each segment in two applications: groundwater flow and heat exchange.

Mixing in Stokes flows is notoriously difficult to achieve. With characteristic scales of the flows being too small for the turbulence to be present, and too large for the molecular diffusion to be significant, the chaotic advection presents almost the only mechanism that can lead to mixing. Unfortunately for mixing, the intrinsic symmetries of the flow create invariant surfaces that act as barriers to mixing. Thus, a key to efficient mixing is to add to the original (symmetric) flow a certain kind of perturbation that destroys those symmetries. In this dissertation, two ways of obtaining mixing in 3D near-integrable bounded time -dependent Stoke Flows are studied: resonances and separatrix crossings. First, I illustrate that the resonances between different components of the original flow and the perturbation may break the invariant surfaces, paving a way to the large-scale mixing. Theoretical estimations are compared against the results of numerical simulations, as well as 3D particle tracking velocimetry (3D-PTV) experimental results. Second, chaotic advection and mixing due to quasi-random jumps of the adiabatic invariant (AI) occurring when a streamline crosses the separatrix surfaces is studied. Analytical expressions for the change in the AI near the separatrix surfaces are derived and compared with numerical simulations. / Mechanical Engineering

The structure of the magnetic field is often an important factor in many energetic processes in the solar corona. To determine the topology of the magnetic field features such as null points, separatrix surfaces, and separators must be found. It has been found that these features may be preferred sites for the formation of current sheets associated with the accumulation of free magnetic energy. Over the last decade, it also became clear that the geometrical analogs of the separatrices, the so-called quasi separatrix layers, have similar properties. This thesis has the aim of investigating these properties and to find correlations between these quantities. Our goal is to determine the relation between the geometrical features associated with the QSLs and with current structures, sites of reconnection and topological features. With these aims we conduct three different studies. First, we investigate a non linear force free magnetic field extrapolation from observed magnetogram data taken during a solar flare eruption concentrating our attention on two snapshots, one before the event and one after. We determine the QSLs and related structures and by considering carefully how these change between the two snapshots we are able to propose a possible scenario for how the flare occurred. In our second project we consider potential source distributions. We take different potential point source models: two four sources models already presented in the literature and a random distribution of fifteen sources. From these potential models we conduct a detailed analysis of the relationship between topological features and QSLs. It is found that the maxima of the Q-factor in the photosphere are located near and above the position of the subphotospheric null points (extending part way along their spines) and that their narrow QSLs are associated with the curves defined by the photospheric endpoints of all fan field lines that start from subphotospheric sources. Our last study investigates two different flux rope emergence simulations. In particular, we take one case with and one without an overlying magnetic field. Here, we can identify the QSLs, current, and sites of reconnection and determine the relation between them. From this work we found that not all high-Q regions are associated with current and/or reconnection and vice-versa. We also investigated the geometry of the field lines associated with high-Q regions to determine which geometrical behaviour of the magnetic field they are associated with. Those that are associated with reconnection also coincide with topological features such as separators.

Made available in DSpace on 2016-04-27T16:58:46Z (GMT). No. of bitstreams: 1 Fernanda de Mello Garcia.pdf: 1582979 bytes, checksum: 4aef5034a5f4500d0e0d481e36d26840 (MD5) Previous issue date: 2008-10-23 / Secretaria da Educação do Estado de São Paulo / The National Curricular Parameters, published in 1997, introduce for the first time in the primary and secondary school curriculum a set of concepts named Information Handling , with issues regarding to statistic, probability, and combining analyses. Hereby, springs the need for mathematic teachers working with these new concepts. Current researches reveal the little knowledge teachers hold on the subject, since in their initial graduation they didn t study these new concepts or if they did, it was with a very technical approach. This work seeks to answer the following question: What are the meanings attributed by 8th year students from secondary school to the variability when worked in a schooling context of mathematic classes? What are the contributions to the understanding of the statistic s content when the learning takes place in an exploratory way, making use of the separatrix measures and focusing in the variability? For that, we elaborated and applied a sequence of didactics that approached the idea of variability by using the separatrix measures. Our objects of research were 8th year students from the 9 year length current primary/secondary school. We noticed that the involved students were able to attribute meaning to the data variation, to the values observed in the determination of measures. It was also noticed the need for more specific activities that develop the graphic Box-plot comprehension associated with other graphic representations / Os Parâmetros Curriculares Nacionais, publicados em 1997, inserem, pela primeira vez no currículo da Escola Básica, um Bloco de conteúdos denominado Tratamento da Informação , contendo assuntos relacionados a Estatística, a Probabilidade e a Análise Combinatória. Surge assim a necessidade dos professores de Matemática trabalhar com esses novos conteúdos. Pesquisas atuais indicam o pouco conhecimento dos professores sobre esse tema, uma vez que em sua formação inicial não o estudaram, ou fizeram-no em uma abordagem tecnicista. Neste trabalho, buscamos responder a seguinte questão: Quais os significados atribuídos por alunos de 8º ano do Ensino Fundamental, para a variabilidade quando trabalhada num contexto escolar em aulas de Matemática? Que contribuições há na compreensão de conteúdos Estatísticos quando os alunos os apreendem em um enfoque exploratório, com uso das medidas separatrizes e com foco na variabilidade? Para isso, elaboramos e aplicamos uma seqüência didática que abordou a idéia de variabilidade pelo uso das medidas separatrizes. Nossos sujeitos de pesquisa foram alunos do 8º ano do atual Ensino Fundamental de 9 anos. Pudemos observar que os alunos envolvidos atribuíram significados à variação dos dados, aos valores observados na determinação das medidas. Observou-se também a necessidade de mais atividades específicas que trabalhem a compreensão do gráfico Box-plot, associando-o a outras representações gráficas

Signalverarbeitung im Nervensystem hängt sowohl von der Netzwerkstruktur, als auch den zellulären Eigenschaften der Nervenzellen ab. In dieser Abhandlung werden zwei zelluläre Eigenschaften im Hinblick auf ihre funktionellen Anpassungsmöglichkeiten untersucht: Es wird gezeigt, dass neuronale Morphologie die Signalweiterleitung unter Berücksichtigung energetischer Beschränkungen verstärken kann, und dass selbst kleine Änderungen in biophysikalischen Parametern die Aktivierungsbifurkation in Nervenzellen, und damit deren Informationskodierung, wechseln können. Im ersten Teil dieser Abhandlung wird, unter Verwendung von mathematischen Modellen und Daten, die Hypothese aufgestellt, dass Energie-effiziente Signalweiterleitung als starker Evolutionsdruck für unterschiedliche Zellkörperlagen bei Nervenzellen wirkt. Um Energie zu sparen, kann die Signalweiterleitung vom Dendrit zum Axon verstärkt werden, indem relativ kleine Zellkörper zwischen Dendrit und Axon eingebaut werden, während relativ große Zellkörper besser ausgelagert werden. Im zweiten Teil wird gezeigt, dass biophysikalische Parameter, wie Temperatur, Membranwiderstand oder Kapazität, den Feuermechanismus des Neurons ändern, und damit gleichfalls Aktionspotential-basierte Informationsverarbeitung. Diese Arbeit identifiziert die sogenannte "saddle-node-loop" (Sattel-Knoten-Schlaufe) Bifurkation als den Übergang, der besonders drastische funktionale Auswirkungen hat. Neben der Änderung neuronaler Filtereigenschaften sowie der Ankopplung an Stimuli, führt die "saddle-node-loop" Bifurkation zu einer Erhöhung der Netzwerk-Synchronisation, was möglicherweise für das Auslösen von Anfällen durch Temperatur, wie bei Fieberkrämpfen, interessant sein könnte. / Signal processing in nervous systems is shaped by the connectome as well as the cellular properties of nerve cells. In this thesis, two cellular properties are investigated with respect to the functional adaptations they provide: It is shown that neuronal morphology can improve signal transmission under energetic constraints, and that even small changes in biophysical parameters can switch spike generation, and thus information encoding. In the first project of the thesis, mathematical modeling and data are deployed to suggest energy-efficient signaling as a major evolutionary pressure behind morphological adaptations of cell body location: In order to save energy, the electrical signal transmission from dendrite to axon can be enhanced if a relatively small cell body is located between dendrite and axon, while a relatively large cell body should be externalized. In the second project, it is shown that biophysical parameters, such as temperature, membrane leak or capacitance, can transform neuronal excitability (i.e., the spike onset bifurcation) and, with that, spike-based information processing. This thesis identifies the so-called saddle-node-loop bifurcation as the transition with particularly drastic functional implications. Besides altering neuronal filters and stimulus locking, the saddle-node-loop bifurcation leads to an increase in network synchronization, which may potentially be relevant for the initiation of seizures in response to increased temperature, such as during fever cramps.