The Uchuu-GLAM BOSS and eBOSS LRG lightcones: Exploring clustering and covariance errors

This study investigates the clustering and bias of Luminous Red Galaxies (LRG) in the BOSS-LOWZ, -CMASS, -COMB, and eBOSS samples, using two types of simulated lightcones: (i) high-fidelity lightcones from Uchuu $N$-body simulation, employing SHAM technique to assign LRG to (sub)halos, and (ii) 16000 covariance lightcones from GLAM-Uchuu $N$-body simulations, including LRG using HOD data from Uchuu. Our results indicate that Uchuu and GLAM lightcones closely replicate BOSS/eBOSS data, reproducing correlation function and power spectrum across scales from redshifts $0.2$ to $1.0$, from $2$ to $150\,h^{-1}\mathrm{Mpc}$ in configuration space, from $0.005$ to $0.7\,h\mathrm{Mpc}^{-1}$ in Fourier space, and across different LRG stellar masses. Furthermore, comparing with existing MD-Patchy and EZmock BOSS/eBOSS lightcones based on approximate methods, our GLAM-Uchuu lightcones provide more precise clustering estimates. We identify significant deviations from observations within $20\,h^{-1}\mathrm{Mpc}$ scales in MD-Patchy and EZmock, with our covariance matrices indicating that these methods underestimate errors by between $10\%$ and $60\%$. Lastly, we explore the impact of cosmology on galaxy clustering. Our findings suggest that, given the current level of uncertainties in BOSS/eBOSS data, distinguishing models with and without massive neutrino effects on LSS is challenging. This paper highlights the Uchuu and GLAM-Uchuu simulations' robustness in verifying the accuracy of Planck cosmological parameters, providing a strong foundation for enhancing lightcone construction in future LSS surveys. We also demonstrate that generating thousands of galaxy lightcones is feasible using $N$-body simulations with adequate mass and force resolution.