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 150h−1Mpc in configuration space, from 0.005 to 0.7hMpc−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 20h−1Mpc 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.