LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Non-linear damping of superimposed primordial oscillations on the matter power spectrum in galaxy surveys

Photo from wikipedia

Galaxy surveys are an important probe for superimposed oscillations on the primordial power spectrum of curvature perturbations, which are predicted in several theoretical models of inflation and its alternatives. In… Click to show full abstract

Galaxy surveys are an important probe for superimposed oscillations on the primordial power spectrum of curvature perturbations, which are predicted in several theoretical models of inflation and its alternatives. In order to exploit the full cosmological information in galaxy surveys it is necessary to study the matter power spectrum to fully non-linear scales. We therefore study the non-linear clustering in models with superimposed linear and logarithmic oscillations to the primordial power spectrum by running high-resolution dark-matter-only N-body simulations. We fit a Gaussian envelope for the non-linear damping of superimposed oscillations in the matter power spectrum to the results of the N-body simulations for $k \lesssim 0.6\ h/$Mpc at $0 \leq z \leq 5$ with an accuracy below the percent. We finally use this fitting formula to forecast the capabilities of future galaxy surveys, such as Euclid and Subaru, to probe primordial oscillation down to non-linear scales alone and in combination with the information contained in CMB anisotropies.

Keywords: matter; power spectrum; non linear; galaxy surveys

Journal Title: Journal of Cosmology and Astroparticle Physics
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.