Large Scale Structures in photometric and spectroscopic surveys

• Ano de defesa: 2019
• Autor(a) principal: Chavez, Hugo Orlando Camacho
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Astronomia; Astronomy; Cosmologia; Cosmology; Estrutura do universo; Structure of the universe
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/43/43134/tde-07052019-084133/

The dynamics of formation of the observed large-scale structures, along with dark matter, dark energy, the accelerated expansion of the universe and their inter-connections remain as some of the biggest puzzles of modern cosmology and have been extensively investigated over the last years. In particular, understanding the nature of cosmic acceleration foresees important implications for Cosmology, Gravitation and Particle Physics, among others. Complementary cosmological probes from large photometric and spectroscopic galaxy surveys, such as DES and eBOSS, represent a powerful approach to these problems, while simultaneously offering new practical and theoretical challenges for exploiting the information contained in observed data. In this work, we present three analyses of the large scale structure of the universe in the context of two galaxy surveys, the DES and the eBOSS, by measuring clustering signal of tracers for the matter distribution using different approaches to their two-point correlation function and power spectrum. In the context of BOSS-eBOSS, we present contributions to some of the first analyses of the clustering signal in configuration space of ELGs and LRGs with early eBOSS data and their interpretation and comparison with previous data and theoretical models. In the context of DES, we present measurements of the galaxy angular power spectrum of galaxies using data from the first year of observations and use these measurements to search for the BAO feature in harmonic space. This work is part of the DES effort for the analysis of the BAO feature in Y1 data.