A Systematic Study of Projection Biases in Weak Lensing Analysis
  We present a systematic study of projection biases in the weak lensing
analysis of the first year of data from the Dark Energy Survey (DES)
experiment. In the analysis we used a $\Lambda$CDM model and three two-point
correlation functions. We show that these biases are a consequence of
projecting, or marginalizing, over parameters like $h$, $\Omega_b$, $n_s$ and
$\Omega_\nu h^2$ that are both poorly constrained and correlated with the
parameters of interest like $\Omega_m$, $\sigma_8$ and $S_8$. Covering the
relevant parameter space we show that the projection biases are a function of
where the true values of the poorly constrained parameters lie with respect to
the parameter priors. For example, biases in the position of the posteriors can
exceed the 1.5$\sigma$ level if the true values of $h$ and $n_s$ are close to
the top of the prior's range and the true values of $\Omega_b$ and $\Omega_\nu
h^2$ are close to the bottom of the range of their priors. We also show that in
some cases the 1D credible intervals can be over-specified by as much as 30%
and coverage can be as low as 27%. Finally we estimate these projection biases
for the analysis of three and six years worth of DES data.
