Accounting for baryonic effects in cosmic shear tomography: Determining
  a minimal set of nuisance parameters using PCA
  Systematic uncertainties that have been subdominant in past large-scale
structure (LSS) surveys are likely to exceed statistical uncertainties of
current and future LSS data sets, potentially limiting the extraction of
cosmological information. Here we present a general framework (PCA
marginalization) to consistently incorporate systematic effects into a
likelihood analysis. This technique naturally accounts for degeneracies between
nuisance parameters and can substantially reduce the dimension of the parameter
space that needs to be sampled. As a practical application, we apply PCA
marginalization to account for baryonic physics as an uncertainty in cosmic
shear tomography. Specifically, we use CosmoLike to run simulated likelihood
analyses on three independent sets of numerical simulations, each covering a
wide range of baryonic scenarios differing in cooling, star formation, and
feedback mechanisms. We simulate a Stage III (Dark Energy Survey) and Stage IV
(Large Synoptic Survey Telescope/Euclid) survey and find a substantial bias in
cosmological constraints if baryonic physics is not accounted for. We then show
that PCA marginalization (employing at most 3 to 4 nuisance parameters) removes
this bias. Our study demonstrates that it is possible to obtain robust, precise
constraints on the dark energy equation of state even in the presence of large
levels of systematic uncertainty in astrophysical processes. We conclude that
the PCA marginalization technique is a powerful, general tool for addressing
many of the challenges facing the precision cosmology program.
