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de Souza R.S.,Korea Astronomy and Space Science Institute | de Souza R.S.,Eotvos University | Maio U.,National institute for astrophysics | Maio U.,Leibniz Institute for Astrophysics Potsdam | And 2 more authors.
Monthly Notices of the Royal Astronomical Society | Year: 2014

We present a novel approach, based on robust principal components analysis (RPCA) and maximal information coefficient (MIC), to study the redshift dependence of halo baryonic properties. Our data are composed of a set of different physical quantities for primordial minihaloes: dark matter mass (Mdm), gas mass (Mgas), stellar mass (Mstar), molecular fraction (Xmol), metallicity (Z), star formation rate (SFR) and temperature.We find thatMdm andMgas are dominant factors for variance, particularly at high redshift. Nonetheless, with the emergence of the first stars and subsequent feedback mechanisms, Xmol, SFR and Z start to have a more dominant role. Standard PCA gives three principal components (PCs) capable to explain more than 97 per cent of the data variance at any redshift (two PCs usually accounting for no less than 92 per cent), whilst the first PC from the RPCA analysis explains no less than 84 per cent of the total variance in the entire redshift range (with two PCs explaining ≥95 per cent anytime). Our analysis also suggests that all the gaseous properties have a stronger correlation with Mgas than with Mdm, while Mgas has a deeper correlation with Xmol than with Z or SFR. This indicates the crucial role of gas molecular content to initiate star formation and consequent metal pollution from Population III and Population II/I regimes in primordial galaxies. Finally, a comparison between MIC and Spearman correlation coefficient shows that the former is a more reliable indicator when halo properties are weakly correlated. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. Source

De Souza R.S.,Korea Astronomy and Space Science Institute | De Souza R.S.,Eotvos University | Ishida E.E.O.,Max Planck Institute for Astrophysics | Ishida E.E.O.,University of Sao Paulo | And 4 more authors.
Monthly Notices of the Royal Astronomical Society | Year: 2014

The first supernovae (SNe) will soon be visible at the edge of the observable universe, revealing the birthplaces of Population III stars. With upcoming near-infrared missions, a broad analysis of the detectability of high-z SNe is paramount. We combine cosmological and radiationtransport simulations, instrument specifications and survey strategies to create synthetic observations of primeval core-collapse (CC), Type IIn and pair-instability (PI) SNe with the James Webb Space Telescope (JWST). We show that a dedicated observational campaign with theJWST can detect up to ~15 PI explosions, ~300 CC SNe, but less than one Type IIn explosion per year, depending on the Population III star formation history. Our synthetic survey also shows that ≈1-2 × 102 SNe detections, depending on the accuracy of the classification, are sufficient to discriminate between a Salpeter and flat mass distribution for high-redshift stars with a confidence level greater than 99.5 per cent. We discuss how the purity of the sample affects our results and how supervised learning methods may help to discriminate between CC and PI SNe. © 2014 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. Source

Fuzi A.,IP Systems Ltd. | Madi-Nagy G.,IP Systems Ltd. | Madi-Nagy G.,Eotvos University
Periodica Polytechnica, Social and Management Sciences | Year: 2014

The paper introduces the mechanism of the Flow-based Capacity Allocation (FBA) method on the electricity market of the Central-Eastern Europe (CEE) Region, proposed by the Central Allocation Office (CAO). The method is a coordinated heterogeneous multi-unit uniform price auction where the allocation is determined by the solution of a linear programming problem. On one hand, the properties of the underlying linear programming problem are discussed: the possibilities of multiple solutions are analysed, then a non-standard sensitivity analysis method of the market spread auction is developed. On the other hand, a global optimization problem is presented that yields uniform auction prices corresponding to higher total income than at the original allocation method. Several numerical examples and results of practical test problems are presented. Source

de Souza R.S.,Eotvos University | Ciardi B.,Max Planck Institute for Astrophysics
Astronomy and Computing | Year: 2015

We present AMADA, an interactive web application to analyze multidimensional datasets. The user uploads a simple ascii file and AMADA performs a number of exploratory analysis together with contemporary visualizations diagnostics. The package performs a hierarchical clustering in the parameter space, and the user can choose among linear, monotonic or non-linear correlation analysis. AMADA provides a number of clustering visualization diagnostics such as heatmaps, dendrograms, chord diagrams, and graphs. In addition, AMADA has the option to run a standard or robust principal components analysis, displaying the results as polar bar plots. The code is written in r and the web interface was created using the shiny framework. AMADA source-code is freely available at https://goo.gl/KeSPue, and the shiny-app at http://goo.gl/UTnU7I. © 2015 Elsevier B.V.. Source

Ishida E.E.O.,Max Planck Institute for Astrophysics | Abdalla F.B.,University College London | De Souza R.S.,Korea Astronomy and Space Science Institute | De Souza R.S.,Eotvos University
Proceedings of the International Astronomical Union | Year: 2015

The problem of supernova photometric identification is still an open issue faced by large photometric surveys. In a previous investigation, we showed how combining Kernel Principal Component Analysis and Nearest Neighbour algorithms enable us to photometrically classify supernovae with a high rate of success. In the present work, we demonstrate that the introduction of Gaussian Process Regression (GPR) in determining each light curve highly improves the efficiency and purity rates. We present detailed comparison with results from the literature, based on the same simulated data set. The method proved to be satisfactorily efficient, providing high purity (96%) rates when compared with standard algorithms, without demanding any information on astrophysical properties of the local environment, host galaxy or redshift. © International Astronomical Union 2015. Source

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