Sample variance in N--body simulations and impact on tomographic shear
  predictions
  We study the effects of sample variance in N--body simulations, as a function
of the size of the simulation box, namely in connection with predictions on
tomographic shear spectra. We make use of a set of 8 $\Lambda$CDM simulations
in boxes of 128, 256, 512 $h^{-1}$Mpc aside, for a total of 24, differing just
by the initial seeds. Among the simulations with 128 and 512 $h^{-1}$Mpc aside,
we suitably select those closest and farthest from {\it average}. Numerical and
linear spectra $P(k,z)$ are suitably connected at low $k$ so to evaluate the
effects of sample variance on shear spectra $C_{ij}(\ell)$ for 5 or 10
tomographic bands. We find that shear spectra obtained by using 128 $h^{-1}$Mpc
simulations can vary up to $\sim 25\, \%$, just because of the seed. Sample
variance lowers to $\sim 3.3\, \%$, when using 512 $h^{-1}$Mpc. These very
percentages could however slightly vary, if other sets of the same number of
realizations were considered. Accordingly, in order to match the $\sim 1\, \%$
precision expected for data, if still using 8 boxes, we require a size $\sim
1300$ --$ 1700 \, h^{-1}$ Mpc for them.
