Simulating the Anisotropic Clustering of Luminous Red Galaxies with
  Subhalos: A Direct Confrontation with Observation and Cosmological
  Implications
  We model the apparent clustering anisotropy of Luminous Red Galaxies (LRGs)
in the Sloan Digital Sky Survey using subhalos identified in cosmological
$N$-body simulations. We first conduct a Markov-chain Monte Carlo analysis on
the parameters characterizing subhalos hosting LRGs assuming a specific
$\Lambda$CDM cosmology on which we run the simulations. We show that simple
models with central and satellite subhalos can explain the observed multipole
moments of the power spectrum up to hexadecapole on large scales
($k\lesssim0.3~h\mathrm{Mpc}^{-1}$). A satellite fraction of $20$ to $30$ per
cent is favored weakly depending on the detail of the model. The fraction is
shown to be robust when we adopt a more refined model based on the halo
occupation number from the literature. We then vary cosmological parameters
controlling the anisotropy in redshift-space effectively by deforming the
simulation box (the Alcock-Paczynski effect) and changing the amplitude of the
velocities (the redshift-space distortions). We demonstrate that we can
constrain the geometry of the universe, the structure growth rate, and the
parameters characterizing LRGs simultaneously. This is a step toward
cosmological analysis with realistic bias description beyond empirical bias
functions with nuisance parameters.
