Computational Methods for Studies of Quantum Dots and Boson Condensates

This thesis presents ab initio studies of two kinds of physical systems, quantum dots and bosons, using two program packages of which the bosonic one has mainly been developed by the author. The implemented models, \emph{i.e.}, configuration interaction (CI) and coupled cluster (CC) take the correlated motion of the particles into account, and provide a hierarchy of computational schemes, on top of which the exact solution, within the limit of the single-particle basis set, is obtained. The theory underlying the models is presented in some detail, in order to provide insight into the approximations made and the circumstances under which they hold. Some of the computational methods are also highlighted. In the final sections the results are summarized. The CI and CC calculations on multiexciton complexes in self-assembled semiconductor quantum dots are presented and compared, along with radiative and non-radiative transition rates. Full CI calculations on quantum rings and double quantum rings are also presented. In the latter case, experimental and theoretical results from the literature are re-examined and an alternative explanation for the reported photoluminescence spectra is found. The boson program is first applied on a fictitious model system consisting of bosonic electrons in a central Coulomb field for which CI at the singles and doubles level is found to account for almost all of the correlation energy. Finally, the boson program is employed to study Bose-Einstein condensates confined in different anisotropic trap potentials. The effects of the anisotropy on the relative correlation energy is examined, as well as the effect of varying the interaction potential.}

Perturbative growth of cosmological clustering. I: Formalism

Here we rederive the hierarchy of equations for the evolution of distribution functions of various orders using a convenient parameterization. We use this to obtain equations for two- and three-point correlation functions in powers of a small parameter, viz., the initial density contrast. The correspondence of the lowest order solutions of these equations to the results from the linear theory of density perturbations is shown for an OMEGA = 1 universe. These equations are then used to calculate, to the lowest order, the induced three-point correlation function that arises from Gaussian initial conditions in an OMEGA = 1 universe. We obtain an expression which explicitly exhibits the spatial structure of the induced three-point correlation function. It is seen that the spatial structure of this quantity is independent of the value of OMEGA. We also calculate the triplet momentum. We find that the induced three-point correlation function does not have the ''hierarchical'' form often assumed. We discuss possibilities of using the induced three-point correlation to interpret observational data. The formalism developed here can also be used to test a validity of different schemes to close the

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

Thermo-physical and structural studies of sodium zinc borovanadate glasses in the region of high concentration of modifier oxides

This paper reports investigation of Na2O and ZnO modified borovanadate glasses in the highly modified regime of compositions. These glasses have been prepared by microwave route. Ultraviolet (UV) and visible, infrared (IR), Magic Angle Spinning Nuclear Magnetic Resonance (MAS NMR) and Electron Paramagnetic Resonance (EPR) spectroscopies have been used to characterize the speciation in the glasses. Together with the variation of properties such as molar volume and glass transition temperatures, spectroscopic data indicate that at high levels of modification, ZnO tends to behave like network former. It is proposed that the observed variation of all the properties can be reasonably well understood with a structural model. The model considers that the modification and speciation in glasses are strongly determined by the hierarchy of group electronegativities. Further, it is proposed that the width of the transitions of glasses obtained under same condition reflects the fragility of the glasses. An empirical expression has been suggested to quantify fragility on the basis of width of the transition regions. (C) 2012 Elsevier Ltd. All rights reserved.

The evolution of complexity in social organization-A model using dominance-subordinate behavior in two social wasp species

Dominance and subordinate behaviors are important ingredients in the social organizations of group living animals. Behavioral observations on the two eusocial species Ropalidia marginata and Ropalidia cyathiformis suggest varying complexities in their social systems. The queen of R. cyathiformis is an aggressive individual who usually holds the top position in the dominance hierarchy although she does not necessarily show the maximum number of acts of dominance, while the R. marginata queen rarely shows aggression and usually does not hold the top position in the dominance hierarchy of her colony. In R. marginata, more workers are involved in dominance-subordinate interactions as compared to R. cyathiformis. These differences are reflected in the distribution of dominance-subordinate interactions among the hierarchically ranked individuals in both the species. The percentage of dominance interactions decreases gradually with hierarchical ranks in R. marginata while in R. cyathiformis it first increases and then decreases. We use an agent-based model to investigate the underlying mechanism that could give rise to the observed patterns for both the species. The model assumes, besides some non-interacting individuals, the interaction probabilities of the agents depend on their pre-differentiated winning abilities. Our simulations show that if the queen takes up a strategy of being involved in a moderate number of dominance interactions, one could get the pattern similar to R. cyathiformis, while taking up the strategy of very low interactions by the queen could lead to the pattern of R. marginata. We infer that both the species follow a common interaction pattern, while the differences in their social organization are due to the slight changes in queen as well as worker strategies. These changes in strategies are expected to accompany the evolution of more complex societies from simpler ones.

The role of tusks, musth and body size in male-male competition among Asian elephants, Elephas maximus

The evolution of sexually dimorphic, elaborate male traits that are seemingly maladaptive may be driven by sexual selection (male-male competition and or female mate choice). Tusk possession in the Asian elephant is sexually dimorphic and exaggerated but its role in male-male competition has not yet been determined. We examined the role of the tusks in establishing dominance along with two other known male-male signals, namely, body size and musth (a temporary physiologically heightened sexual state) in an Asian elephant population in northeastern India with equal proportions of tusked and tuskless males. We observed 116 agonistic interactions with clear dominance outcomes between adult (>15 years) males during 458 field days in the dry season months of 2008-2011. A generalized linear mixed-effects model was used to predict the probability of winning as a function of body size, tusk possession and musth status relative to the opponent. A hierarchy of the three male-male signals emerged from this analysis, with musth overriding body size and body size overriding tusk possession. In this elephant population tusk possession thus plays a relatively minor role in male-male competition. An important implication of musth and body size being stronger determinants of dominance than tusk possession is that it could facilitate rapid evolution of tuskless males in the population under artificial selection against tusked individuals, which are poached for ivory. (C) 2013 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

An exploration framework to identify and track movement of cloud systems

We describe a framework to explore and visualize the movement of cloud systems. Using techniques from computational topology and computer vision, our framework allows the user to study this movement at various scales in space and time. Such movements could have large temporal and spatial scales such as the Madden Julian Oscillation (MJO), which has a spatial scale ranging from 1000 km to 10000 km and time of oscillation of around 40 days. Embedded within these larger scale oscillations are a hierarchy of cloud clusters which could have smaller spatial and temporal scales such as the Nakazawa cloud clusters. These smaller cloud clusters, while being part of the equatorial MJO, sometimes move at speeds different from the larger scale and in a direction opposite to that of the MJO envelope. Hitherto, one could only speculate about such movements by selectively analysing data and a priori knowledge of such systems. Our framework automatically delineates such cloud clusters and does not depend on the prior experience of the user to define cloud clusters. Analysis using our framework also shows that most tropical systems such as cyclones also contain multi-scale interactions between clouds and cloud systems. We show the effectiveness of our framework to track organized cloud system during one such rainfall event which happened at Mumbai, India in July 2005 and for cyclone Aila which occurred in Bay of Bengal during May 2009.

Interactome analyses of Salmonella pathogenicity islands reveal SicA indispensable for virulence

Background: Serovars of Salmonella enterica, namely Typhi and Typhimurium, reportedly, are the bacterial pathogens causing systemic infections like gastroenteritis and typhoid fever. To elucidate the role and importance in such infection, the proteins of the Type III secretion system of Salmonella pathogenicity islands and two component signal transduction systems, have been mainly focused. However, the most indispensable of these virulent ones and their hierarchical role has not yet been studied extensively. Results: We have adopted a theoretical approach to build an interactome comprising the proteins from the Salmonella pathogeneicity islands (SPI) and two component signal transduction systems. This interactome was then analyzed by using network parameters like centrality and k-core measures. An initial step to capture the fingerprint of the core network resulted in a set of proteins which are involved in the process of invasion and colonization, thereby becoming more important in the process of infection. These proteins pertained to the Inv, Org, Prg, Sip, Spa, Ssa and Sse operons along with chaperone protein SicA. Amongst them, SicA was figured out to be the most indispensable protein from different network parametric analyses. Subsequently, the gene expression levels of all these theoretically identified important proteins were confirmed by microarray data analysis. Finally, we have proposed a hierarchy of the proteins involved in the total infection process. This theoretical approach is the first of its kind to figure out potential virulence determinants encoded by SPI for therapeutic targets for enteric infection. Conclusions: A set of responsible virulent proteins was identified and the expression level of their genes was validated by using independent, published microarray data. The result was a targeted set of proteins that could serve as sensitive predictors and form the foundation for a series of trials in the wet-lab setting. Understanding these regulatory and virulent proteins would provide insight into conditions which are encountered by this intracellular enteric pathogen during the course of infection. This would further contribute in identifying novel targets for antimicrobial agents. (C) 2014 Elsevier Ltd. All rights reserved.

Prevalence and clinical correlates of obsessive-compulsive disorder in schizophrenia

Obsessive compulsive symptoms frequently occur in a substantial proportion of patients with schizophrenia. The term schizoobsessive has been proposed to delineate this subgroup of schizophrenia patients who present with obsessive compulsive symptoms/disorder. However, whether this co-occurrence is more than just co-morbidity and represents a distinct subgroup remains controversial. A striking variation is noted across studies examining prevalence of obsessive compulsive symptoms/disorder in schizophrenia patients and their impact on clinical profile of schizophrenia. Hence, in this study, we examined the prevalence of obsessive compulsive symptoms/disorder in a large sample of consecutively hospitalized schizophrenia patients and compared the clinical and functional characteristics of schizophrenia patients with and without obsessive compulsive symptoms/disorder. We evaluated 200 consecutive subjects with the DSM-IV diagnosis of schizophrenia using the Structured Clinical Interview for DSM-IV Axis I disorders, Positive and Negative Syndrome Scale, Yale Brown Obsessive Compulsive Scale, Brown Assessment of Beliefs Scale, Clinical Global Impression-Severity scale, Global Assessment of Functioning Scale, Family Interview for Genetic Studies and World Health Organization Quality of Life scale. The prevalence of obsessive compulsive symptoms in patients with schizophrenia was 24% (n = 48); 37 of them had obsessive compulsive disorder (OCD) and II had obsessive compulsive symptoms not amounting to a clinical diagnosis of OCD (OCS). Schizophrenia patients with OCS/OCD had an earlier age at onset of schizophrenia symptoms, lower positive symptoms score, higher co-morbidity with Axis II disorders, higher occurrence of OCD in family and better quality of life. Findings of the study indicate a higher prevalence of OCS/OCD in schizophrenia. Schizophrenia patients with and without OCS/OCD have comparable clinical profile with few exceptions. High rates of OCD in first degree relatives suggest possible genetic contributions and differences in neurobiology. Finally, evidence to consider schizoobsessive as a distinct diagnostic entity is inconclusive and warrants further studies. (C) 2014 Elsevier Inc. All rights reserved.

Unraveling Public Good Games: The Role of Priors

This paper provides experimental evidence on how players predict end game effects in a linear public good game. Our regression analysis yields a measure of the relative importance of priors and signals on subjects\' beliefs on contributions and allow us to conclude that, firstly, the weight of the signal is relatively unimportant, while priors have a large weight and, secondly, priors are the same for all periods. Hence, subjects do not expect end game effects and there is very little updating of beliefs.

Identification of a biomarker panel for colorectal cancer diagnosis

Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

Confianza del consumidor en la compra a través de Internet: una propuesta de modelización basada en la jerarquía de aprendizaje estándar

[ES] Este trabajo se encuadra dentro de los estudios centrados en el análisis del comportamiento de compra del consumidor en Internet. Nos centramos en la adaptación del modelo de la jerarquía de efectos basado en su variante de la jerarquía estándar de aprendizaje para proponer teóricamente un modelo conceptual que explica cómo las creencias —i.e. diseño, velocidad de interacción, beneficios sociales y privacidad— y actitudes del consumidor hacia Internet, como medio de comunicación, pueden considerarse como determinantes plausibles de la confianza en la compra online. Asimismo, en nuestro modelo se plantea que las opiniones del consumidor respecto a la compra a distancia también deben ejercer una influencia sobre sus valoraciones de Internet, como medio de comunicación y, especialmente, de compra.

Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.

Climatology of the seasonal precipitation maximum in the western United States

The western United States is characterized by heterogeneous patterns of seasonal precipitation regimes due to the hierarchy of climatic controls that operate at different spatial scales. A climatology of intermonthly precipitation changes, using data from more than 4,000 stations including high-elevation sites, illustrate how different climatic controls explain the spatial distribution of the seasonal precipitation maximum. These results indicate that smaller-scale climatic controls must be considered along with larger-scale ones to explain patterns of spatial climate heterogeneity over mountainous areas. The results also offer important implications for scholars interested in assessing spatial climatic variations of the western United States at different timescales.

Response of Pacific Northwest vegetation to large-scale changes in climate during the last 100,000 years [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Paleoclimatic variations in western North America depend on a hierarchy of temporal and spatial controls that can be examined using a combination of modeling studies and data synthesis. ... The regional vegetation response to large-scale changes in the climate system of the last 21,000 years is used as a conceptual model to help explain earlier vegetation and climate at two localities.