91̽»¨

Abstract:

We present a new method to marginalize over uncertainties in redshift distributions, N(z), within tomographic cosmological analyses applicable to current and upcoming photometric galaxy surveys. We allow for arbitrary deviations from the best-guess N(z) governed by a general covariance matrix describing the uncertainty in our knowledge of redshift distributions. In principle, this is marginalization over hundreds or thousands of new parameters describing potential deviations as a function of redshift and tomographic bin. However, by linearly expanding the theory predictions around a fiducial model, this marginalization can be performed analytically, resulting in a modified data covariance matrix that effectively downweights the modes of the data vector that are more sensitive to redshift distribution variations. We showcase this method by applying it to the galaxy clustering measurements from the Hyper Suprime-Cam first data release. We illustrate how to marginalize over sample-variance of the calibration sample and a large general systematic uncertainty in photometric estimation methods, and explore the impact of priors imposing smoothness in the redshift distributions.

Abstract:

© 2020 91̽»¨ University Press. All rights reserved. The paper 'Tomographic measurement of the intergalactic gas pressure through galaxy-tSZ cross-correlations' was published inMNRAS, 491, 5464-5480 (2020). After publication a typographical error in our analysis pipeline code was discovered, which slightly affected some of our results. In particular, our implementation of the generalised NFW profile (GNFW) described in Arnaud et al. (2010) lacked a factor of 1 - bH in the calculation of R500. We have corrected this error, re-run our analysis and present our updated results and comments (where applicable) in this manuscript. (i) Table 3 is updated with new best-fitting values. (ii) Likewise, Figs 8 and 9 are also updated with the new values of the best-fitting 1 - bHand<bPe>. (iii) Finally, our combined constraint on bH following this procedure (equation 48) is 1 - bH= 0.75 ± 0.03. While the main conclusions remain unchanged, it is worth pointing out that the best-fitting mass bias value 1 - bH= 0.75 ± 0.03 is now at a ~3-4s tension with the results measured by Planck Collaboration et al. (2016a) (1 - bH= 0.58 ± 0.04), combining tSZ cluster number counts and the TT CMB power spectrum. Consequently, our results can no longer be viewed as evidence of compatibility between the best-fit cosmology and the clustering properties of galaxies in the datasets used. Further, the best-fitting value of the mass bias is no longer at odds with the one derived from hydrodynamical simulations (Biffi et al. 2016), the estimate from CMB lensing mass calibration (Zubeldia & Challinor 2019), and other direct calibration efforts (e.g. Smith et al. 2016; Eckert et al. 2019), which seem to prefer smaller missing mass fractions (1 - bH~ 0.8). Lastly, our results are in agreement with Chiang et al. (2020), who explore the cosmic thermal history using SZ tomography.