http://arxiv.org/abs/2202.05949
We investigate simulation-based bandpower covariance matrices commonly used in cosmological parameter inferences such as the estimation of the tensor-to-scalar ratio~$r$. We find that upper limits on $r$ can be biased low. The underestimation of the upper limit is most severe when the number of simulation realizations is similar to the number of observables. Convergence of the covariance-matrix estimation can require a number of simulations an order of magnitude larger than the number of observables. This is found to be caused by an additional scatter in the posterior probability of $r$ due to Monte Carlo noise in the estimated bandpower covariance matrix, in particular, by spurious non-zero off-diagonal elements. We show that matrix conditioning can be a viable mitigation strategy in the case that legitimate covariance assumptions can be made.
D. Beck, A. Cukierman and W. Wu
Tue, 15 Feb 22
62/75
Comments: 8 pages, 10 figures, to be submitted to MNRAS