A curvature-weighted, non-flat volume measure removes the leading-order marginalization bias in posterior means, recovering cosmological parameters in mocks to below 0.1 sigma.
Analytic marginalization over CMB calibration and beam uncertainty
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abstract
With the increased accuracy and angular scale coverage of the recent CMB experiments it has become important to include calibration and beam uncertainties when estimating cosmological parameters. This requires an integration over possible values of the calibration and beam size, which can be done numerically but increases computation times. We present a fast and simple algorithm for marginalization over beam and calibration errors by analytical integration. We also illustrate the effect of incorporating these uncertainties by calculating the constraints on various cosmological and inflationary parameters including the spectral index n_s and the physical baryon density Omega_b h^2, using the latest CMB data. We find that parameter constraints are significantly changed when calibration/beam uncertainties are taken into account. Typically the best fit parameters are shifted and the errors bars are increased by up to fifty per cent for e.g. n_s and Omega_b h^2, although as expected there is no change for Omega_K, because it is constrained by the positions of the peaks.
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Debiasing inference in large-scale structure with non-flat volume measures
A curvature-weighted, non-flat volume measure removes the leading-order marginalization bias in posterior means, recovering cosmological parameters in mocks to below 0.1 sigma.