Image Reconstruction Using Interval Simulated Annealing in Electrical Impedance Tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.

Analysis of Synthetic Diamond Wafer Interferograms Using a Parallelized Simulated Annealing Algorithm

Diamonds are known for both their beauty and their durability. Jefferson National Lab in Newport News, VA has found a way to utilize the diamond's strength to view the beauty of the inside of the atomic nucleus with the hopes of finding exotic forms of matter. By firing very fast electrons at a diamond sheet no thicker than a human hair, high energy particles of light known as photons are produced with a high degree of polarization that can illuminate the constituents of the nucleus known as quarks. The University of Connecticut Nuclear Physics group has responsibility for crafting these extremely thin, high quality diamond wafers. These wafers must be cut from larger stones that are about the size of a human finger, and then carefully machined down to the final thickness. The thinning of these diamonds is extremely challenging, as the diamond's greatest strength also becomes its greatest weakness. The Connecticut Nuclear Physics group has developed a novel technique to assist industrial partners in assessing the quality of the final machining steps, using a technique based on laser interferometry. The images of the diamond surface produced by the interferometer encode the thickness and shape of the diamond surface in a complex way that requires detailed analysis to extract. We have developed a novel software application to analyze these images based on the method of simulated annealing. Being able to image the surface of these diamonds without requiring costly X-ray diffraction measurements allows rapid feedback to the industrial partners as they refine their thinning techniques. Thus, by utilizing a material found to be beautiful by many, the beauty of nature can be brought more clearly into view.

Acoustic properties of microperforated panels and their optimizatión by simulated annealing

This thesis investigates the acoustic properties of microperforated panels as an alternative to passive noise control. The first chapters are devoted to the review of analytical models to obtain the acoustic impedance and absorption coefficient of perforated panels. The use of panels perforated with circular holes or with slits is discussed. The theoretical models are presented and some modifications are proposed to improve the modeling of the physical phenomena occurring at the perforations of the panels. The absorption band is widened through the use of multiple layer microperforated panels and/or the combination of a millimetric panel with a porous layer that can be a fibrous material or a nylon mesh. A commercial micrometric mesh downstream a millimetric panel is proposed as a very efficient and low cost solution for controlling noise in reduced spaces. The simulated annealing algorithm is used in order to optimize the panel construction to provide a maximum of absorption in a determined wide band frequency range. Experiments are carried out at normal sound incidence and plane waves. One example is shown for a double layer microperforated panel subjected to grazing flow. A good agreement is achieved between the theory and the experiments. RESUMEN En esta tesis se investigan las propiedades acústicas de paneles micro perforados como una alternativa al control pasivo del ruido. Los primeros capítulos están dedicados a la revisión de los modelos de análisis para obtener la impedancia acústica y el coeficiente de absorción de los paneles perforados. El uso de paneles perforados con agujeros circulares o con ranuras es discutido. Se presentan diferentes modelos y se proponen algunas modificaciones para mejorar la modelización de los fenómenos físicos que ocurren en las perforaciones. La banda de absorción se ensancha a través del uso de capas múltiples de paneles micro perforados y/o la combinación de un panel de perforaciones milimétricas combinado con una capa porosa que puede ser un material fibroso o una malla de nylon. Se propone el uso de una malla micrométrica detrás de un panel milimétrico como una solución económica y eficiente para el control del ruido en espacios reducidos. El algoritmo de recocido simulado se utiliza con el fin de optimizar la construcción de paneles micro perforados para proporcionar un máximo de absorción en una banda determinada frecuencias. Los experimentos se llevan a cabo en la incidencia normal de sonido y ondas planas. Se muestra un ejemplo de panel micro perforado de doble capa sometido a flujo rasante. Se consigue un buen acuerdo entre la teoría y los experimentos.

Cross-validated maximum likelihood enhances crystallographic simulated annealing refinement

Recently, the target function for crystallographic refinement has been improved through a maximum likelihood analysis, which makes proper allowance for the effects of data quality, model errors, and incompleteness. The maximum likelihood target reduces the significance of false local minima during the refinement process, but it does not completely eliminate them, necessitating the use of stochastic optimization methods such as simulated annealing for poor initial models. It is shown that the combination of maximum likelihood with cross-validation, which reduces overfitting, and simulated annealing by torsion angle molecular dynamics, which simplifies the conformational search problem, results in a major improvement of the radius of convergence of refinement and the accuracy of the refined structure. Torsion angle molecular dynamics and the maximum likelihood target function interact synergistically, the combination of both methods being significantly more powerful than each method individually. This is demonstrated in realistic test cases at two typical minimum Bragg spacings (dmin = 2.0 and 2.8 Å, respectively), illustrating the broad applicability of the combined method. In an application to the refinement of a new crystal structure, the combined method automatically corrected a mistraced loop in a poor initial model, moving the backbone by 4 Å.

Investigating the molecular structures of solid dispersions by the simulated annealing method

Knowledge of the molecular structures of solid dispersions is vital, yet, despite thousands of reports in this area, it remains unclear. The aim of this research is to investigate the molecular structure of solid dispersions with hot melt preparation method by the simulated annealing method. Simulation results showed linear polymer chains form the random coils under heat and the drug molecules stick on the surface of polymer coils, while drug molecules are dispersed molecularly but irregularly within the amorphous low molecular weight carriers. This research presents more reasonable molecular images of solid dispersions than the existed theory.

Improving the performance of FBG sensors in a WDM network using a simulated annealing technique

Simulated annealing technique is used to improve the performance of fiber Bragg grating (FBG) sensors in a wavelength-division-multiplexed network. Experiments demonstrated strain detection accuracy of ̃2.5 με when the spectrums of FBGs are fully or partially overlapped.

O problema de alocação de berços: um estudo das heurísticas simulated annealing e algoritmo genético

Este trabalho apresenta um estudo de caso das heurísticas Simulated Annealing e Algoritmo Genético para um problema de grande relevância encontrado no sistema portuário, o Problema de Alocação em Berços. Esse problema aborda a programação e a alocação de navios às áreas de atracação ao longo de um cais. A modelagem utilizada nesta pesquisa é apresentada por Mauri (2008) [28] que trata do problema como uma Problema de Roteamento de Veículos com Múltiplas Garagens e sem Janelas de Tempo. Foi desenvolvido um ambiente apropriado para testes de simulação, onde o cenário de análise foi constituido a partir de situações reais encontradas na programação de navios de um terminal de contêineres. Os testes computacionais realizados mostram a performance das heurísticas em relação a função objetivo e o tempo computacional, a m de avaliar qual das técnicas apresenta melhores resultados.

Implementação paralela escalável e eficiente do algoritmo simplex padrão em arquitetura multicore

This work presents a scalable and efficient parallel implementation of the Standard Simplex algorithm in the multicore architecture to solve large scale linear programming problems. We present a general scheme explaining how each step of the standard Simplex algorithm was parallelized, indicating some important points of the parallel implementation. Performance analysis were conducted by comparing the sequential time using the Simplex tableau and the Simplex of the CPLEXR IBM. The experiments were executed on a shared memory machine with 24 cores. The scalability analysis was performed with problems of different dimensions, finding evidence that our parallel standard Simplex algorithm has a better parallel efficiency for problems with more variables than constraints. In comparison with CPLEXR , the proposed parallel algorithm achieved a efficiency of up to 16 times better

Quantum annealing of an ising spin-glass by Green's function Monte Carlo

We present an implementation of quantum annealing (QA) via lattice Green's function Monte Carlo (GFMC), focusing on its application to the Ising spin glass in transverse field. In particular, we study whether or not such a method is more effective than the path-integral Monte Carlo- (PIMC) based QA, as well as classical simulated annealing (CA), previously tested on the same optimization problem. We identify the issue of importance sampling, i.e., the necessity of possessing reasonably good (variational) trial wave functions, as the key point of the algorithm. We performed GFMC-QA runs using such a Boltzmann-type trial wave function, finding results for the residual energies that are qualitatively similar to those of CA (but at a much larger computational cost), and definitely worse than PIMC-QA. We conclude that, at present, without a serious effort in constructing reliable importance sampling variational wave functions for a quantum glass, GFMC-QA is not a true competitor of PIMC-QA.

Optimization through quantum annealing: theory and some applications

Quantum annealing is a promising tool for solving optimization problems, similar in some ways to the traditional ( classical) simulated annealing of Kirkpatrick et al. Simulated annealing takes advantage of thermal fluctuations in order to explore the optimization landscape of the problem at hand, whereas quantum annealing employs quantum fluctuations. Intriguingly, quantum annealing has been proved to be more effective than its classical counterpart in many applications. We illustrate the theory and the practical implementation of both classical and quantum annealing - highlighting the crucial differences between these two methods - by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems ( namely, Random Ising model and Travelling Salesman Problem). The techniques used to implement quantum and classical annealing are either deterministic evolutions, for the simplest models, or Monte Carlo approaches, for harder optimization tasks. We discuss the pro and cons of these approaches and their possible connections to the landscape of the problem addressed.