Internal robustness of growth rate data

Abstract

We perform an Internal Robustness analysis (iR) to a compilation of the most recent f σ8(z) data, using the framework of Ref. [1]. The method analyzes combinations of subsets in the data set in a Bayesian model comparison way, potentially finding outliers, subsets of data affected by systematics or new physics. In order to validate our analysis and assess its sensitivity we performed several cross-checks, for example by removing some of the data or by adding artificially contaminated points, while we also generated mock data sets in order to estimate confidence regions of the iR. Applying this methodology, we found no anomalous behavior in the f σ8(z) data set, thus validating its internal robustness. PACS numbers: 95.36.+x, 04.50.Kd, 98.80.Es

Designing Horndeski and the effective fluid approach

“…This degeneracy is useful as it can potentially alleviate and relax the tension that has been recently observed, see Refs. [27,88]. In particular, in Fig 9 we show the 68.3%, 95.4% and 99.7% confidence contours for the ΛCDM (left) and the HDES (n = 2) (right) models respectively in the (Ω m,0 , σ 8 ) plane.…”

“…This degeneracy is interesting as it can potentially alleviate the soft 2σ tension between the growth rate data (σ 8 = 0.88) and Planck (σ 8 = 0.831), which has been extensively discussed in the literature, see Ref. [27,88] and references therein.…”

“…The reason for this is that in linear Right: The evolution of the f σ8(z) parameter for the KGB model with n = 2 and σ8,0 = 0.8 versus the f σ8 data compilation from Ref. [88]. Here we show the theoretical curves for the "Full KGB" brute-force solution, the effective fluid approach, the ΛCDM model and the numerical solution of the G eff equation.…”

“…We show the evolution of the f σ8(z) parameter for the HDES model with n = 2,Jc = 5 · 10 −2 and σ8,0 = 0.8 versus the f σ8 data compilation from Ref. [88]. The values of values forJc were chosen so as to highlight the differences of these models with respect to GR.…”

“…The covariances of the data and how to make the necessary corrections for the Alcock-Paczynski effect are given in Refs. [27,88,105], while other related analyses with these data can be found in Refs. [24,26,28,65].…”