Sparsely Sampling the Sky: A Bayesian Experimental Design Approach
  The next generation of galaxy surveys will observe millions of galaxies over
large volumes of the universe. These surveys are expensive both in time and
cost, raising questions regarding the optimal investment of this time and
money. In this work we investigate criteria for selecting amongst observing
strategies for constraining the galaxy power spectrum and a set of cosmological
parameters. Depending on the parameters of interest, it may be more efficient
to observe a larger, but sparsely sampled, area of sky instead of a smaller
contiguous area. In this work, by making use of the principles of Bayesian
Experimental Design, we will investigate the advantages and disadvantages of
the sparse sampling of the sky and discuss the circumstances in which a sparse
survey is indeed the most efficient strategy. For the Dark Energy Survey (DES),
we find that by sparsely observing the same area in a smaller amount of time,
we only increase the errors on the parameters by a maximum of 0.45%.
Conversely, investing the same amount of time as the original DES to observe a
sparser but larger area of sky we can in fact constrain the parameters with
errors reduced by 28%.
