Non-Gaussian Error Contribution to Likelihood Analysis of the Matter
  Power Spectrum
  We study the sample variance of the matter power spectrum for the standard
Lambda Cold Dark Matter universe. We use a total of 5000 cosmological N-body
simulations to study in detail the distribution of best-fit cosmological
parameters and the baryon acoustic peak positions. The obtained distribution is
compared with the results from the Fisher matrix analysis with and without
including non-Gaussian errors. For the Fisher matrix analysis, we compute the
derivatives of the matter power spectrum with respect to cosmological
parameters using directly full nonlinear simulations. We show that the
non-Gaussian errors increase the unmarginalized errors by up to a factor 5 for
k_{max}=0.4h/Mpc if there is only one free parameter provided other parameters
are well determined by external information. On the other hand, for
multi-parameter fitting, the impact of the non-Gaussian errors is significantly
mitigated due to severe parameter degeneracies in the power spectrum. The
distribution of the acoustic peak positions is well described by a Gaussian
distribution, with its width being consistent with the statistical interval
predicted from the Fisher matrix. We also examine systematic bias in the
best-fit parameter due to the non-Gaussian errors. The bias is found to be
smaller than the 1 sigma statistical error for both the cosmological parameters
and the acoustic scale positions.
