As semiconductor manufacture feature sizes scale into the nanometer dimension, circuit layout printability is significantly reduced due to the fundamental limit of lithography systems. This dissertation studies related research topics in lithography simulation and optical proximity correction. A recursive integration method is used to reduce the errors in transmission cross coefficient (TCC), which is an important factor in the Hopkins Equation in aerial image simulation. The runtime is further reduced, without increasing the errors, by using the fact that TCC is usually computed on uniform grids. A flexible software framework, ELIAS, is also provided, which can be used to compute TCC for various lithography settings, such as different illuminations. Optimal coherent approximations (OCAs), which are used for full-chip image simulation, can be speeded up by considering the symmetric properties of lithography systems. The runtime improvement can be doubled without loss of accuracy. This improvement is applicable to vectorial imaging models as well. Even in the case where the symmetric properties do not hold strictly, the new method can be generalized such that it could still be faster than the old method. Besides new numerical image simulation algorithms, variations in lithography systems are also modeled. A Variational LIthography Model (VLIM) as well as its calibration method are provided. The Variational Edge Placement Error (V-EPE) metrics, which is an improvement of the original Edge Placement Error (EPE) metrics, is introduced based on the model. A true process-variation aware OPC (PV-OPC) framework is proposed using the V-EPE metric. Due to the analytical nature of VLIM, our PV-OPC is only about 2-3× slower than the conventional OPC, but it explicitly considers the two main sources of process variations (exposure dose and focus variations) during OPC. The EPE metrics have been used in conventional OPC algorithms, but it requires many intensity simulations and takes the majority of the OPC runtime. By making the OPC algorithm intensity based (IB-OPC) rather than EPE based, we can reduce the number of intensity simulations and hence reduce the OPC runtime. An efficient intensity derivative computation method is also provided, which makes the new algorithm converge faster than the EPE based algorithm. Our experimental results show a runtime speedup of more than 10× with comparable result quality compared to the EPE based OPC. The above mentioned OPC algorithms are vector based. Other categories of OPC algorithms are pixel based. Vector based algorithms in general generate less complex masks than those of pixel based ones. But pixel based algorithms produce much better results than vector based ones in terms of contour fidelity. Observing that vector based algorithms preserve mask shape topologies, which leads to lower mask complexities, we combine the strengths of both categories—the topology invariant property and the pixel based mask representation. A topological invariant pixel based OPC (TIP-OPC) algorithm is proposed, with lithography friendly mask topological invariant operations and an efficient Fast Fourier Transform (FFT) based cost function sensitivity computation. The experimental results show that TIP-OPC can achieve much better post-OPC contours compared with vector based OPC while maintaining the mask shape topologies. / text

The first chapter provides some basic definitions and results from the theory of convex analysis and nonlinear mappings related to our work. Some sufficient conditions for the existence of a solution of problem (GVIP) are also recalled. In the second chapter, we first illustrate the scope of the auxiliary problem procedure designed to solve problems like (GVIP) by examining some well-known methods included in that framework. Then, we review the most representative convergence results for that class of methods that can be found in the literature in the case where F is singlevalued as well as in the multivalued case. Finally, we somewhat discuss the particular case of projection methods to solve affine variational inequalities. The third chapter introduces the variational convergence notion of Mosco and combines it with the auxiliary problem principle. Then, we recall the convergence conditions existing for the resulting perturbed scheme before our own contribution and we comment them. Finally, we introduce and illustrate the rate of convergence condition that we impose on the perturbations to obtain better convergence results. Chapter 4 presents global and local convergence results for the family of perturbed methods in the case where F is singlevalued. We also discuss how our results extend or improve the previous ones. Chapter 5 studies the multivalued case. First, we present convergence results generalizing those obtained when there is no perturbations. Then, we relax the scheme by means of a notion of enlargement of an operator and we provide convergence conditions for this inexact scheme. In Chapter 6, we build a bundle algorithm to solve problem (GVIP) and we study its convergence.

In a software development cycle, programs go through many iterations. Identifying and understanding program changes is a tedious but necessary task for programmers, especially when software is developed in a collaborative environment. Existing tools used by the programmers either lack in finding the structural differences, or report the differences as atomic changes, such as updates of individual syntax tree nodes. Programmers frequently use program restructuring techniques, such as refactorings that are composed of several individual atomic changes. Current version differencing tools omit these high-level changes, reporting just the set of individual atomic changes. When a large number of refactorings are performed, the number of reported atomic changes is very large. As a result, it will be very difficult to understand the program differences. This problem can be addressed by reporting the program differences as composite changes, thereby saving programmers the effort of navigating through the individual atomic changes. This thesis proposes a methodology to explore the atomic changes reported by existing version differencing tools to infer composite changes. First, we will illustrate the different approaches that can be used for representing object language program differences using a variation representation. Next we will present the process of composite change inference from the structured representation of atomic changes. This process describes patterns that specify the expected structure of an expression corresponding to each composite change that has to be inferred. The information in patterns is then used to design the change inference algorithm. The composite changes inferred from a given expression are annotated in the expression, allowing the changes to be reported as desired. / Graduation date: 2012

In this study two nonlinear analysis methods are proposed for investigation of nonlinear effects of high temperature superconductive(HTSC) thin film planar microwave circuits. The MoM-HB combination method is based on the combination formulation of the moment method(MoM) and the harmonic balance(HB) technique. It consists of linear and nonlinear solvers. The power series method treats the voltages at higher order frequencies as the excitations at the corresponding frequencies, and the higher order current distributions are then obtained by using the moment method again. The power series method is simple and fast for finding the output power at higher order frequencies. The MoM-HB combination method is suitable for strong nonlinearity, and it can be also used to find the fundamental current redistribution, conductor loss, and the scattering parameters variation at the fundamental frequency. These two proposed methods are efficient, accurate, and suitable for distributed-type HTSC nonlinearity. They can be easily incorporated into commercial EM CAD softwares to expand their capabilities. These two nonlinear analysis method are validated by analyzing a HTSC stripline filter and HTSC antenna dipole circuits. HTSC microstrip lines are then investigated for the nonlinear effects of HTSC material on the current density distribution over the cross section and the conductor loss as a function of the applied power. The HTSC microstrip patch filters are then studied to show that the HTSCinterconnecting line could dominate the behaviors of the circuits at high power. The variation of the transmission and reflection coefficients with the applied power and the third output power are calculated. The HTSC microstrip line structure with gilded edges is proposed for improving the power handling capability of HTSC thin film circuit based on a specified limit of harmonic generation and conductor loss. A general analysis approach suitable for any thickness of gilding layer is developed by integrating the multi-port network theory into aforementioned proposed nonlinear analysis methods. The conductor loss and harmonic generation of the gilded HTSC microstrip line are investigated.

Nonrigid image registration has received much attention in the medical imaging and computer vision research communities, because it enables a wide variety of applications. Feature tracking, segmentation, classification, temporal image differencing, tumour growth estimation, and pharmacokinetic modeling are examples of the many tasks that are enhanced by the use of aligned imagery. Over the years, the medical imaging and computer vision communties have developed and refined image registration techniques in parallel, often based on similar assumptions or underlying paradigms. This thesis focuses on variational registration, which comprises a subset of nonrigid image registration. It is divided into chapters that are based on fundamental aspects of the variational registration problem: image dissimilarity measures, changing overlap regions, regularizers, and computational solution strategies. Key contributions include the development of local versions of standard dissimilarity measures, the handling of changing overlap regions in a manner that is insensitive to the amount of non-interesting background information, the combination of two standard taxonomies of regularizers, and the generalization of solution techniques based on Fourier methods and the Demons algorithm for use with many regularizers. To illustrate and validate the various contributions, two sets of example imagery are used: 3D CT, MR, and PET images of the brain as well as 3D CT images of lung cancer patients.

This thesis concerns the regularity of holonomic minimisers of variational integrals in the context of direct methods in the calculus of variations. Specifically, we consider Sobolev mappings from a bounded domain into a connected compact Riemannian manifold without boundary, to which such mappings are said to be holonomically constrained. For a general class of strictly quasiconvex integral functionals, we give a direct proof of local C^1,α-Hölder continuity, for some 0 < α < 1, of holonomic minimisers off a relatively closed 'singular set' of Lebesgue measure zero. Crucially, the proof constructs comparison maps using the universal covering of the target manifold, the lifting of Sobolev mappings to the covering space and the connectedness of the covering space. A certain tangential A-harmonic approximation lemma obtained directly using a Lipschitz approximation argument is also given. In the context of holonomic minimisers of regular variational integrals, we also provide bounds on the Hausdorff dimension of the singular set by generalising a variational difference quotient method to the holonomically constrained case with critical growth. The results are analogous to energy-minimising harmonic maps into compact manifolds, however in this case the proof does not use a monotonicity formula. We discuss several applications to variational problems in condensed matter physics, in particular those concerning the superfluidity of liquid helium-3 and nematic liquid crystals. In these problems, the class of mappings are constrained to an orbit of 'broken symmetries' or 'manifold of internal states', which correspond to a sub-group of residual symmetries.

We briefly summarize existing result in theory of minimizers of elliptic variational functionals. We introduce proof of existence and regularity such functional under assumpti- ons of quaziconvexity and izotrophic growth estimates, and discuss possible generalization to anizotropic case. Our proof is a compilation from more sources, modified in order of simplicity, readability and detailed analysis of all steps.

The aim of this thesis is to provide an overview of currently used helvetisms in the field of cuisine and eating. In the initial part, a concept of German as a pluricentric language is introduced, followed by a description of the language situation in the German speaking Switzerland and basic characteristics of the Swiss variety. Five sources were analyzed, besides other things also a journal of a Switzerland-based Germanist and business company Migros' product database. Internet was used as a linguistic corpus in order to provide an analysis tool next to the selected dictionaries. Ascertained helvetisms were assessed on the basis of their existing lexicographic form and the degree of their intelligibility for other German speaking countries speakers. Selected helvetisms were processed as dictionary entries for the emerging Large German-Czech Academic Dictionary. Powered by TCPDF (www.tcpdf.org)

<p>Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.</p> / Dissertation

Neste trabalho desenvolvemos o formalismo do Método Celular Variacional para ser aplicado à estruturas cristalinas com vários átomos por célula unitária. O método foi usado para determinar a estrutura elementar do silício, com a célula unitária dividida em quatro poliedros, sendo dois átomos e dois intersticiais. As células intersticiais foram incluídas com o fim de melhorar a média esférica do potencial cristalino. Os resultados obtidos concordam muito bem com os experimentais, mostrando que, mesmo para estruturas periódicas mais complexas, o método exige apenas um pequeno número de funções de base para a expansão das funções de onda celulares. / In this work we developed the Variational Cellular Method formalism applied to three-dimensional periodic structures with an arbitrary number of atoms per unit cell. The Method was used to determine the eletronic structure of silicon, with the unit cell partitional into four space-filling polyhedra: two intersticial polyhedra. The intersticial cells were included in order to improve the spherical cellular potentials. The obtained results are in very good agreement with the experimental results, showing that even for more complex periodic structures the Method requires only a few number of base functions.