Tomographic measurement of the intergalactic gas pressure through galaxy-tSZ cross-correlations (vol 491, pg 5464, 2020)
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY Oxford University Press (OUP) 499:1 (2020) 520-522
Abstract:
© 2020 Oxford 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.Tomographic measurement of the intergalactic gas pressure through galaxy-tSZ cross-correlations (vol 491, pg 5464, 2020)
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY Oxford University Press (OUP) 499:1 (2020) 520-522
Abstract:
© 2020 Oxford 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.Dark-matter-deficient dwarf galaxies form via tidal stripping of dark matter in interactions with massive companions
(2020)
A hierarchical field-level inference approach to reconstruction from sparse Lyman-α forest data
A&A 2020
Abstract:
We address the problem of inferring the three-dimensional matter distribution from a sparse set of one-dimensional quasar absorption spectra of the Lyman-α forest. Using a Bayesian forward modelling approach, we focus on extending the dynamical model to a fully self-consistent hierarchical field-level prediction of redshift-space quasar absorption sightlines. Our field-level approach rests on a recently developed semiclassical analogue to Lagrangian perturbation theory (LPT), which improves over noise problems and interpolation requirements of LPT. It furthermore allows for a manifestly conservative mapping of the optical depth to redshift space. In addition, this new dynamical model naturally introduces a coarse-graining scale, which we exploited to accelerate the Markov chain Monte-Carlo (MCMC) sampler using simulated annealing. By gradually reducing the effective temperature of the forward model, we were able to allow it to first converge on large spatial scales before the sampler became sensitive to the increasingly larger space of smaller scales. We demonstrate the advantages, in terms of speed and noise properties, of this field-level approach over using LPT as a forward model, and, using mock data, we validated its performance to reconstruct three-dimensional primordial perturbations and matter distribution from sparse quasar sightlines.