Cosmological parameter inference with Bayesian statistics

Bayesian statistics and Markov Chain Monte Carlo (MCMC) algorithms have found their place in the field of Cosmology. They have become important mathematical and numerical tools, especially in parameter estimation and model comparison. In this paper, we review some fundamental concepts to understand Bayesian statistics and then introduce MCMC algorithms and samplers that allow us to perform the parameter inference procedure. We also introduce a general description of the standard cosmological model, known as the $\Lambda$CDM model, along with several alternatives, and current datasets coming from astrophysical and cosmological observations. Finally, with the tools acquired, we use an MCMC algorithm implemented in python to test several cosmological models and find out the combination of parameters that best describes the Universe.Comment: 30 pages, 17 figures, 5 tables; accepted for publication in Universe; references adde

Peak characteristics of F2 region over Tucumán: Predictions and measurements

Ionosonde measurements obtained at Tucuman are used to check the validity of the International Reference Ionosphere model to predict the maximum electron density of F2 region (NmF2) and its height (hmF2) over this station. Data corresponding to different months and solar activity conditions are considered. CCIR and URSI options are used to model calculations. The results show that, generally, the predictions of hmF2 are better than those of NmF2. Disagreements between predicted and measured NmF2 values are observed and the consequence in the vertical total electron content modeling are stressed.Fil: Ezquer, Rodolfo Gerardo. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionósfera; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mosert, Marta Estela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Ciencias Astronómicas, de la Tierra y del Espacio. Universidad Nacional de San Juan. Instituto de Ciencias Astronómicas, de la Tierra y del Espacio; ArgentinaFil: Scida, Luis Alberto. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionósfera; ArgentinaFil: López, J.. Universidad Tecnológica Nacional; Argentin

Multiplicative structures of hypercyclic functions for convolution operators

In this note, it is proved the existence of an infinitely generated multiplicative group consisting of entire functions that are, except for the constant function 1, hypercyclic with respect to the convolution operator associated to a given entire function of subexponential type. A certain stability under multiplication is also shown for compositional hypercyclicity on complex domains.Comment: 12 page

Model selection applied to non-parametric reconstructions of the Dark Energy

The main aim of this paper is to perform a model comparison for non-parametric reconstructions of the key properties that describe the dark energy of the Universe i.e. energy density and the equation of state (EoS). We carry out this process by using a binning and a linear interpolation methodologies, and on the top of that, we incorporate a correlation function mechanism. An extension of the two of them was also introduced, where internal amplitudes are allowed to vary in height as well as in position. The reconstructions were made with data from the Hubble parameter, Supernovae Type Ia and Baryon Acoustic Oscillations (H+SN+BAO), all of which span a range from $z=0.01$ to $z=2.8$. First we perform the parameter estimation for each of the reconstructions to then provide a model selection through the Bayesian Evidence. Throughout our process we found a better fit to the data, up to $4\sigma$ compared to $\Lambda$CDM, and the presence of some interesting features, i.e. an oscillatory behaviour at late times, a decrease in the dark energy density component at early times and a transition to the phantom divide-line in the EoS. To discern these features from noisy contributions, we include a principal component analysis and found that some of these characteristics should be taken into account to satisfy observations.Comment: 14 pages, 7 figure

Compositional uniformity, domain patterning and the mechanism underlying nano-chessboard arrays

We propose that systems exhibiting compositional patterning at the nanoscale, so far assumed to be due to some kind of ordered phase segregation, can be understood instead in terms of coherent, single phase ordering of minority motifs, caused by some constrained drive for uniformity. The essential features of this type of arrangements can be reproduced using a superspace construction typical of uniformity-driven orderings, which only requires the knowledge of the modulation vectors observed in the diffraction patterns. The idea is discussed in terms of a simple two dimensional lattice-gas model that simulates a binary system in which the dilution of the minority component is favored. This simple model already exhibits a hierarchy of arrangements similar to the experimentally observed nano-chessboard and nano-diamond patterns, which are described as occupational modulated structures with two independent modulation wave vectors and simple step-like occupation modulation functions.Comment: Preprint. 11 pages, 11 figure