29 resultados para Electronic optimization

em Brock University, Canada


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Optimization of wave functions in quantum Monte Carlo is a difficult task because the statistical uncertainty inherent to the technique makes the absolute determination of the global minimum difficult. To optimize these wave functions we generate a large number of possible minima using many independently generated Monte Carlo ensembles and perform a conjugate gradient optimization. Then we construct histograms of the resulting nominally optimal parameter sets and "filter" them to identify which parameter sets "go together" to generate a local minimum. We follow with correlated-sampling verification runs to find the global minimum. We illustrate this technique for variance and variational energy optimization for a variety of wave functions for small systellls. For such optimized wave functions we calculate the variational energy and variance as well as various non-differential properties. The optimizations are either on par with or superior to determinations in the literature. Furthermore, we show that this technique is sufficiently robust that for molecules one may determine the optimal geometry at tIle same time as one optimizes the variational energy.

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We developed the concept of split-'t to deal with the large molecules (in terms of the number of electrons and nuclear charge Z). This naturally leads to partitioning the local energy into components due to each electron shell. The minimization of the variation of the valence shell local energy is used to optimize a simple two parameter CuH wave function. Molecular properties (spectroscopic constants and the dipole moment) are calculated for the optimized and nearly optimized wave functions using the Variational Quantum Monte Carlo method. Our best results are comparable to those from the single and double configuration interaction (SDCI) method.

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Methods for both partial and full optimization of wavefunction parameters are explored, and these are applied to the LiH molecule. A partial optimization can be easily performed with little difficulty. But to perform a full optimization we must avoid a wrong minimum, and deal with linear-dependency, time step-dependency and ensemble-dependency problems. Five basis sets are examined. The optimized wavefunction with a 3-function set gives a variational energy of -7.998 + 0.005 a.u., which is comparable to that (-7.990 + 0.003) 1 of Reynold's unoptimized \fin ( a double-~ set of eight functions). The optimized wavefunction with a double~ plus 3dz2 set gives ari energy of -8.052 + 0.003 a.u., which is comparable with the fixed-node energy (-8.059 + 0.004)1 of the \fin. The optimized double-~ function itself gives an energy of -8.049 + 0.002 a.u. Each number above was obtained on a Bourrghs 7900 mainframe computer with 14 -15 hrs CPU time.

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The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

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The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

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(A) Solid phase synthesis of oligonucleotides are well documented and are extensively studied as the demands continue to rise with the development of antisense, anti-gene, RNA interference, and aptamers. Although synthesis of RNA sequences faces many challenges, most notably the choice of the 2' -hydroxy protecting group, modified 2' -O-Cpep protected ribonucleotides were synthesized as alternitive building blocks. Altering phosphitylation procedures to incorporate 3' -N,N-diethyl phosphoramidites enhanced the overall reactivity, thus, increased the coupling efficiency without loss of integrety. Furthermore, technical optimizations of solid phase synthesis cycles were carried out to allow for successful synthesis of a homo UIO sequences with a stepwise coupling efficiency reaching 99% and a final yield of 91 %. (B) Over the past few decades, dipyrrometheneboron difluoride (BODIPY) has gained recognition as one of the most versatile fluorophores. Currently, BODIPY labeling of oligonucleotides are carried out post-synthetically and to date, there lacks a method that allows for direct incorporation of BODIPY into oligonucleotides during solid phase synthesis. Therefore, synthesis of BODIPY derived phosphoramidites will provide an alternative method in obtaining fluorescently labelled oligonucleotides. A method for the synthesis and incorporation of the BODIPY analogues into oligonucleotides by phosphoramidite chemistry-based solid phase DNA synthesis is reported here. Using this approach, BODIPY-labeled TlO homopolymer and ISIS 5132 were successfully synthesized.

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This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

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Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.

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Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.

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This study was a comparative investigation of face-toface (i.e., proximate) and computer-mediated written (i.e., graphic) pre-writing conferences. The participants in this study were advanced English as a second language students. The 2 types of conferences were compared in terms of textual features, participation, and the . degree to which they were on topic. Moreover, drafts written after the 2 types of conferences were compared in terms of textual features, and the degree to which they were related to the conferences. Students produced an equivalent amount of discourse in an equivalent amount of time in the 2 types of conferences. The discourse in graphic conferences displayed greater lexical range, and some evidence suggests that it was less on-topic. Both these results likely occurred because the graphic conferences contained more discourse demonstrating interactive competence. Participation in graphic conferences was found to be as balanced or more balanced among students, and among students and the group leader combined. Overall, the drafts produced after the 2 types of conferences were of equivalent length and topical range, but some evidence suggests that drafts written after proximate conferences were more related to the conferences.

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Interest in mixed-valent perovskite manganese oxides of La\-xAxMnO^ (v4-divalent alkaline earth Ca, Sr or Ba), whose unusual properties were discovered nearly a half century ago, has recently been revived. The discovery of the colossal magnetoresistance and pressure effects introduced new questions concerning the complex interplay between lattice structure, magnetism and transport in doped perovskite manganites. In this study, we report our experimental investigations of pressure and magnetic field dependencies of La-i/sCai/sMnOs (LCMO) epitaxial films with various thickness on SrTiO$ substrate. An analysis of film thickness dependency of the resistivity of LCMO epitaxial films under pressure and magnetic field has been performed by taking into account substrate contributions. This verifies the correlation of lattice distortion with magnetic and transport properties. Strong dependencies of Mn — O — Mn bond bending and Mn — O bond stretching with pressure as well as Mn spin alignment with magnetic field, and the lattice distortion induced by the substrate are discussed.

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We examined three different algorithms used in diffusion Monte Carlo (DMC) to study their precisions and accuracies in predicting properties of isolated atoms, which are H atom ground state, Be atom ground state and H atom first excited state. All three algorithms — basic DMC, minimal stochastic reconfiguration DMC, and pure DMC, each with future-walking, are successfully impletmented in ground state energy and simple moments calculations with satisfactory results. Pure diffusion Monte Carlo with future-walking algorithm is proven to be the simplest approach with the least variance. Polarizabilities for Be atom ground state and H atom first excited state are not satisfactorily estimated in the infinitesimal differentiation approach. Likewise, an approach using the finite field approximation with an unperturbed wavefunction for the latter system also fails. However, accurate estimations for the a-polarizabilities are obtained by using wavefunctions that come from the time-independent perturbation theory. This suggests the flaw in our approach to polarizability estimation for these difficult cases rests with our having assumed the trial function is unaffected by infinitesimal perturbations in the Hamiltonian.

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A series of LaVi^xOs compounds (x=0.00, 0.02, 0.04, 0.06, 0.08) were prepeired using the standard solid reaction. The samples were chareicterized by X-ray diffraction (XRD), fourprobe resistivity, smd magnetic susceptibility studies. Powder X-ray diffraction analysis indicated the formation of a single-phase sample with a orthorhombic structure which was first found in GdFeOs (space group Pnma) . The Unit Cell program was used for calculating lattice peirameters from XFID data. The XRD spectnim could be indexed on a cubic lattice with Og = 2ap ~ (7.8578 to 7.9414 A). The lattice parameter was observed to increase as the Vanadium vacancy increased. Four-probe resistivity measurements exhibited semiconductor behavior for all sajnples from room temperature down to 19K. The resistivity of samples increased with increasing Vanadium vacancy. The resistivity of samples demonstrated activated conduction with an activation energy of approximately 0.2 eV. The activation energy increased with increasing lattice parameter. Field cool magnetic susceptibility measurements were performed with field of 500 G from 300 K to 5 K. These measurements indicated the presence of an antiferromagnetic transition at about 140 K. The data was fitted above Neel temperature to Ciurie-Weiss law yielding a negative parameignetic Curie temperature. This implies that antiferromagnetic ordering is present.

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A method using L-cysteine for the determination of arsenous acid (As(III)), arsenic acid (As(V)), monomethylarsonic acid (MMAA), and dimethylarsinic acid (DMAA) by hydride generation was demonstrated. The instrument used was a d.c. plasma atomic emission spectrometer (OCP-AES). Complete recovery was reported for As(III), As(V), and DMAA while 86% recovery was reported for MMAA. Detection limits were determined, as arsenic for the species listed previously, to be 1.2, 0.8, 1.1, and 1.0 ngemL-l, respectively. Precision values, at 50 ngemL-1 arsenic concentration, were f.80/0, 2.50/0, 2.6% and 2.6% relative standard deviation, respectively. The L-cysteine reagent was compared directly with the conventional hydride generation technique which uses a potassium iodide-hydrochloric acid medium. Recoveries using L-cysteine when compared with the conventional method provided the following results: similar recoveries were obtained for As(III), slightly better recoveries were obtained for As(V) and MMAA, and significantly better recoveries for DMAA. In addition, tall and sharp peak shapes were observed for all four species when using L-cysteine. The arsenic speciation method involved separation by ion exchange .. high perfonnance liquid chromatography (HPLC) with on-line hydride generation using the L.. cysteine reagent and measurement byOCP-AES. Total analysis time per sample was 12 min while the time between the start of subsequent runs was approximately 20 min. A binary . gradient elution program, which incorporated the following two eluents: 0.01 and 0.5 mM tri.. sodium citrate both containing 5% methanol (v/v) and both at a pH of approximately 9, was used during the separation by HPLC. Recoveries of the four species which were measured as peak area, and were normalized against As(III), were 880/0, 290/0, and 40% for DMAA, MMAA and As(V), respectively. Resolution factors between adjacent analyte peaks of As(III) and DMAA was 1.1; DMAA and MMAA was 1.3; and MMAA and As(V) was 8.6. During the arsenic speciation study, signals from the d.c. plasma optical system were measured using a new photon-signal integrating device. The_new photon integrator developed and built in this laboratory was based on a previously published design which was further modified to reflect current available hardware. This photon integrator was interfaced to a personal computer through an AID convertor. The .photon integrator has adjustable threshold settings and an adjustable post-gain device.

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Both El MS and FAB MS behavior of two groups of compounds, aryltin and ferrocene compounds, have been studied. For the aryltin compounds, the effect of substituent group position, substituent group type and ligand type on the El spectra have been explored in the El MS studies. The fragmentation mechanism has been investigated under El with linked scans, such as fragment ion scans(BJE), parent ion scans(B2JE) and constant neutral radical loss scans(B2(1-E)JE2). In the FAB MS studies, matrix optimization experiments have been carried out. The positive ion FAB MS studies focused on the effect of substituent group position, substituent group type and ligand type on the spectra. The fragmentation mechanisms of all the samples under positive ion FAB have been studied by means of the linked scans. The CA positive ion FAB fragmentation studies were also carried out for a typical sample. Negative ion FAB experiments of all the compounds have been done. And finally, the comparison of the El MS and FAB MS has been made. For ferrocenes, the studies concentrated on the fragmentation mechanism of each compound under El with linked scan techniques in the first field-free region and the applicability of positive/negative ion FAB MS to this group of compounds. The fragmentation mechanisms under positive ion FAB of those ferrocenes which can give positive ion FAB MS spectra were studied with the linked scan techniques. The CA +ve F AB fragmentation studies were carried out for a typical sample. Comparison of the E1 MS and FAB MS has been made.