부산대학교 도서관

Cosmologists aim to uncover the underlying cosmological model governing the formation and evolution of the Universe. One approach is through studying the large-scale structure (LSS) traced by galaxy redshift surveys. In this paper, we explore clustering and covariance errors of BOSS and eBOSS surveys in configuration and Fourier space with a new generation of galaxy lightcones. We create 16 lightcones using the UCHUU simulation: a 2$h^{-1}$Gpc $N$-body simulation tracking 2.1 trillion dark matter particles within a Planck-$\Lambda$CDM cosmology. Simulation's (sub)halos are populated with Luminous red galaxies (LRGs) using the subhalo abundance matching. For estimating covariance errors, we generate 5,040 GLAM-UCHUU LRG lightcones based on GLAM $N$-body simulations. LRGs are included using halo occupation distribution. Our simulated lightcones reproduce BOSS/eBOSS clustering statistics on scales from redshifts 0.2 to 1.0, from 2 to 150$h^{-1}$Mpc, and from 0.005 to 0.7$h$Mpc$^{-1}$, in configuration and Fourier space, respectively. We analyse stellar mass and redshift effects on clustering and bias, revealing consistency with data and noting an increasing bias factor with redshift. Our investigation leads us to the conclusion that the Planck-$\Lambda$CDM cosmology accurately explains the observed LSS. Furthermore, we compare our GLAM-UCHUU LRG lightcones with MD-PATCHY and EZMOCK, identifying large deviations from observations within 20$h^{-1}$Mpc. We examine covariance matrices, finding that our data estimated errors are higher than those previously reported, carrying significant implications for cosmological parameter inferences. Lastly, we explore cosmology's impact on galaxy clustering. Our results suggest that, given the current level of uncertainties, we are unable to distinguish models with and without massive neutrino effects on LSS.