Validating a minimal galaxy bias method for cosmological parameter
  inference using HSC-SDSS mock catalogs
  We assess the performance of a perturbation theory inspired method for
inferring cosmological parameters from the joint measurements of galaxy-galaxy
weak lensing ($\Delta\Sigma$) and the projected galaxy clustering ($w_{\rm
p}$). To do this, we use a wide variety of mock galaxy catalogs constructed
based on a large set of $N$-body simulations that mimic the Subaru HSC-Y1 and
SDSS galaxies, and apply the method to the mock signals to address whether to
recover the underlying true cosmological parameters in the mocks. We find that,
as long as the appropriate scale cuts, $12$ and $8~h^{-1}{\rm Mpc}$ for
$\Delta\Sigma$ and $w_{\rm p}$ respectively, are adopted, a "minimal-bias"
model using the linear bias parameter $b_1$ alone and the nonlinear matter
power spectrum can recover the true cosmological parameters (here focused on
$\Omega_{\rm m}$ and $\sigma_8$) to within the 68% credible interval, for all
the mocks we study including one in which an assembly bias effect is
implemented. This is as expected if physical processes inherent in galaxy
formation/evolution are confined to local, small scales below the scale cut,
and thus implies that real-space observables have an advantage in filtering out
the impact of small-scale nonlinear effects in parameter estimation, compared
to their Fourier-space counterparts. In addition, we find that a theoretical
template including the higher-order bias contributions such as nonlinear bias
parameter $(b_2)$ does not improve the cosmological constraints, but rather
leads to a larger parameter bias compared to the baseline $b_1$-method.
