Beware of commonly used approximations. Part II. Estimating systematic biases in the bestfit parameters
Abstract
Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or approximations that were sufficiently accurate so far, may introduce significant systematic biases in the parameter bestfit values and jeopardize the robustness of cosmological analyses. We generalize previously proposed expressions to estimate a priori the systematic error introduced in parameter inference due to the use of insufficiently good approximations in the computation of the observable of interest or the assumption of an incorrect underlying model. Although this methodology can be applied to measurements of any scientific field, we illustrate its power by studying the effect of modeling the angular galaxy power spectrum incorrectly. We also introduce Multi_CLASS, a new, public modification of the Boltzmann code CLASS, which includes the possibility to compute angular crosspower spectra for two different tracers. We find that significant biases in most of the cosmological parameters are introduced if one assumes the Limber approximation or neglects lensing magnification in modern galaxy survey analyses, and the effect is in general larger for the multitracer case, especially for the parameter controlling primordial nonGaussianity of the local type, f_{NL}.
 Publication:

Journal of Cosmology and Astroparticle Physics
 Pub Date:
 October 2020
 DOI:
 10.1088/14757516/2020/10/017
 arXiv:
 arXiv:2005.09666
 Bibcode:
 2020JCAP...10..017B
 Keywords:

 Astrophysics  Cosmology and Nongalactic Astrophysics
 EPrint:
 21 pages (+5 pages of appendices +6 pages of references), 8 figures, 1 table. Multi_CLASS can be found in https://github.com/nbellomo/Multi_CLASS