1,720,962 research outputs found
Quantum Monte Carlo studies of soft Bosonic systems and Minimum Energy Pathways.
Full text linkIn this thesis, we make use of Monte Carlo techniques to address two rather different subjects in condensed matter physics.
The first study deals with the characterization of a relatively novel and elusive phase of matter, the so-called supersolid, in which crystalline order and dissipationless flow coexist. While supersolidity is a well studied phenomenology in lattice models, we will be working here in continuous space, where much fewer results are available. Specifically, we study a soft core Bosonic system, quantum analog of thoroughly studied classical models, which displays an unambiguous supersolid phenomenology. In this system such a behavior is not obtained through Bose Condensation of lattice defects, but rather it is mean field in character. By computer simulations we characterize many properties of the system: of these, the most prominent are the phase diagram of the system and its excitation spectrum.
This study is loosely related to the ultracold atom experimental field, as it is speculated that interparticle potential pertaining to the same class of the one employed here may be realized in this context. After the recent (and apparently definitive) ruling out of supersolidity effects in ^4He, it seems fair to state that ultracold atoms are the most promising candidate for the observation of this phenomenology. In this section we employ our own implementation of the worm algorithm on the continuum.
The second part of this thesis is instead related to electronic structure, more specifically to the study of minimum energy pathways of reactions calculated via quantum Monte Carlo methods. In particular, we aim at assessing the computational feasibility and the accuracy of determining the most significant geometries of a reaction (initial/final and transition state) and its energy barrier via these stochastic techniques. To this end, we perform calculations on a set of simple reactions and compare the results with density functional theory and high level quantum chemistry calculations. We show that the employed technique indeed performs better than density functional for both geometries and energy barrier. Therefore our methodology is a good candidate to study reactions in which an high accuracy is needed, but it is not possible to employ high level quantum chemistry methods due to computational limitations.
We believe that this study is significant also because of its systematic use of forces from Monte Carlo simulations. Although several studies have addressed various aspects of the problem of computing forces within quantum Monte Carlo accurately and efficiently, there is little awareness that such estimators are in fact mature, and consequently there are very few studies which actually employ them. We hope to show here that these estimators are actually ready to be used and provide good results. In this section we have mainly developed interfaces for existing Quantum Monte Carlo codes
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Deep Learning-Based Pipeline for the Generation of Synthetic Tabular Data
Full text linkThe recent and rapid progresses in Machine Learning (ML) tools and methodologies paved the way for an accessible market of ML services. In principle, small and medium-sized enterprises, as well as big companies, could act as providers and consumers of services, resulting in an intense exchange of ML services where a consumer may ask many providers for a service preview based on its particular business case, that is, its data. In practice, however, many potential service consumers are reluctant to release their data, when seeking for ML services, because of privacy or intellectual property concerns. As a consequence, the market of ML services is not as fluid as it could be. An alternative to providing real data when looking for an ML service consists in generating and releasing synthetic data. The synthetic data should 1) allow the service provider to preview an ML service whose performance is predictive of the one the same service will achieve on the real data; and 2) prevent the disclosure of the real data. In this paper, we propose a data synthesis technique tailored to a family of very relevant business cases: supervised and unsupervised learning on single-table datasets and relational datasets. Our technique is based on generative deep learning models and we instantiate it in three variants: standard Variational Autoencoders (VAEs), β -VAEs, and Introspective VAEs. We experimentally evaluate the two variants to measure the degree to which they meet the two requirements above, using several performance indexes that capture different aspects of the quality of the generated data. The results suggest that data synthesis is a practical answer to the need of decoupling ML service providers and consumers and, hence, can favor the arising of an active and accessible market of ML services
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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