摘要: There is untapped cosmological information in galaxy redshift surveys in the
non-linear regime. In this work, we use the AEMULUS suite of cosmological
$N$-body simulations to construct Gaussian process emulators of galaxy
clustering statistics at small scales ($0.1-50 \: h^{-1}\,\mathrm{Mpc}$) in
order to constrain cosmological and galaxy bias parameters. In addition to
standard statistics -- the projected correlation function
$w_\mathrm{p}(r_\mathrm{p})$, the redshift-space monopole of the correlation
function $\xi_0(s)$, and the quadrupole $\xi_2(s)$ -- we emulate statistics
that include information about the local environment, namely the underdensity
probability function $P_\mathrm{U}(s)$ and the density-marked correlation
function $M(s)$. This extends the model of AEMULUS III for redshift-space
distortions by including new statistics sensitive to galaxy assembly bias. In
recovery tests, we find that the beyond-standard statistics significantly
increase the constraining power on cosmological parameters of interest:
including $P_\mathrm{U}(s)$ and $M(s)$ improves the precision of our
constraints on $\sigma_8$ by 33%, $\Omega_m$ by 28%, and the growth of
structure parameter, $f \sigma_8$, by 18% compared to standard statistics. We
additionally find that scales below $4 \: h^{-1}\,\mathrm{Mpc}$ contain as much
information as larger scales. The density-sensitive statistics also contribute
to constraining halo occupation distribution parameters and a flexible
environment-dependent assembly bias model, which is important for extracting
the small-scale cosmological information as well as understanding the
galaxy-halo connection. This analysis demonstrates the potential of emulating
beyond-standard clustering statistics at small scales to constrain the growth
of structure as a test of cosmic acceleration. Our emulator is publicly
available at https://github.com/kstoreyf/aemulator.