  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.
