The Cosmological Analysis of the SDSS/BOSS data from the Effective Field Theory of Large-Scale Structure (1909.05271v1)

Abstract: The Effective Field Theory of Large-Scale Structure (EFTofLSS) is a formalism that allows us to predict the clustering of Cosmological Large-Scale Structure in the mildly non-linear regime in an accurate and reliable way. After validating our technique against several sets of numerical simulations, we perform the analysis for the cosmological parameters of the DR12 BOSS data. We assume $\Lambda$CDM, a fixed value of the baryon/dark-matter ratio, $\Omega_b/\Omega_c$, and of the tilt of the primordial power spectrum, $n_s$, and no significant input from numerical simulations. By using the one-loop power spectrum multipoles, we measure the primordial amplitude of the power spectrum, $A_s$, the abundance of matter, $\Omega_m$, and the Hubble parameter, $H_0$, to about $13\%$, $3.2\%$ and $3.2\%$ respectively, obtaining $\ln(10^{10}As)=2.72\pm 0.13$, $\Omega_m=0.309\pm 0.010$, $H_0=68.5\pm 2.2$ km/(s Mpc) at 68\% confidence level. If we then add a CMB prior on the sound horizon, the error bar on $H_0$ is reduced to $1.6\%$. These results are a substantial qualitative and quantitative improvement with respect to former analyses, and suggest that the EFTofLSS is a powerful instrument to extract cosmological information from Large-Scale Structure.

• The paper demonstrates that EFTofLSS can extract key cosmological parameters with uncertainties of about 13% for Aₛ and 3.2% for Ωₘ and H₀ (improved to 1.6% with a CMB prior).
• It utilizes the mildly non-linear regime of large-scale structures to break parameter degeneracies without heavy dependence on numerical simulations.
• Comparisons with various simulations confirm that EFTofLSS provides robust predictions, paving the way for its adoption in future cosmological surveys.

Essay on "The Cosmological Analysis of the SDSS/BOSS Data from the Effective Field Theory of Large-Scale Structure"

This paper presents a significant advancement in cosmology by applying the Effective Field Theory of Large-Scale Structure (EFTofLSS) to the Sloan Digital Sky Survey/Baryon Oscillation Spectroscopic Survey (SDSS/BOSS) data. The authors aim to extract cosmological parameters from the mildly non-linear regime of Large-Scale Structure (LSS) structures with enhanced precision and reliability, without heavy reliance on numerical simulations.

In the context of the $\Lambda$CDM cosmological model, the analysis assumes a fixed baryon-to-dark-matter ratio, $\Omega_b/\Omega_c$, and a specified tilt of the primordial power spectrum, $n_s$. Notably, the study accomplishes notable precision in measuring key cosmological parameters: it determines the primordial amplitude of the power spectrum, $A_s$, the matter abundance, $\Omega_m$, and the Hubble parameter, $H_0$, with uncertainties of approximately 13%, 3.2%, and 3.2%, respectively. The inclusion of a Cosmic Microwave Background (CMB) prior refines the uncertainty in $H_0$ to 1.6%.

The paper contrasts EFTofLSS outcomes against different numerical simulations to ascertain its effectiveness in non-linear regime predictions. The study finds that the theoretical systematic error remains under control, even in the absence of tuning the framework to particular simulations—thus corroborating that EFTofLSS can be a reliable method for cosmological parameter extraction from LSS data.

The results indicate a substantial qualitative and quantitative leap in interpreting LSS data. The EFTofLSS framework allows the incorporation and analysis of broader shape and redshift-space distortions without necessitating the breakdown of the numerical complexity into isolated BAO peaks or broadband signals. This methodology results in breaking the parameter degeneracies inherent in traditional LSS data analysis, leading to more accurate estimates of cosmological parameters.

On speculative fronts, the implications of successfully deploying EFTofLSS span both theoretical and observational cosmology. The broader and more accurate cosmological data extraction framework it offers could significantly impact dark matter nature studies, the equation of state of dark energy, and understanding the gravitational interactions at cosmological scales. Moreover, considering the precedence set by EFTofLSS, more extensive cosmological surveys such as DES, DESI, Euclid, LSST, etc., could augment their data analysis techniques incorporating this framework for even more precise insights.

In conclusion, the paper underlines the potential of the EFTofLSS in advancing our understanding of the universe’s large-scale structures. The method paves a promising route for effectively utilizing forthcoming cosmological datasets, potentially paving the way for answering some of the most probing questions in modern cosmology.