Grant number: 21/14098-9 Support type: Scholarships abroad - Research Internship - Post-doctor Effective date (Start): January 31, 2022 Effective date (End): January 30, 2023 Field of knowledge: Physical Sciences and Mathematics - Astronomy - Extragalactic Astrophysics Principal researcher: Rogério Rosenfeld Grantee: Hugo Orlando Camacho Chavez Supervisor abroad: Chihway Chang Home Institution: Instituto de Física Teórica (IFT). Universidade Estadual Paulista (UNESP). Campus de São Paulo. São Paulo , SP, Brazil Research place: University of Chicago, United States Associated to the scholarship: 19/04881-8 - Cosmology with large photometric and spectroscopic galaxy surveys, BP.PD Abstract 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-relations, 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. Modern wide-area galaxy surveys such as the DES and the LSST appear as a powerful approach to these problems via the self-consistent combination of complementary cosmological tests. However, they bring new practical and theoretical challenges for exploiting the information contained in the data. This project aims to explore the use of data from the DES to constrain cosmological models using the self-consistent combination of weak gravitational lensing and galaxy clustering in harmonic space (power spectra). We will co-lead the task force for the 3$\times$2pt analysis in harmonic space on the third-year DES data (Y3) and beyond, continuing our analyses of data from the first year (Y1)~\cite{2019MNRAS.487.3870C,2021MNRAS.505.5714A,2021arXiv211107203C}. Taking advantage of this internship's collaborations, we will explore the possible extensions of the joint analysis methodology for using information from CMB surveys like the SPT. Finally, we will also explore applying all lessons learned from these studies for preliminary analysis of the upcoming LSST. (AU)