The late integrated sachs-wolfe effect and its detectability in galaxy-redshift surveys

Abstract

ABSTRACT: The late Integrated Sachs-Wolfe (ISW) effect is underwent by the Cosmic Microwave Background (CMB) photons due to the presence of the Large-Scale Structures (LSS) in an expanding Universe; it can be measured through the temperature fluctuations of the CMB. We use observational data from the 2MASS galaxy-redshift survey (GRS) and from numerical simulations of structure formation to study the detectability of the ISW effect. To compute the ISW effect, an estimation of the density field through Cloud-In-Cell (CIC) and Triangular-Shaped-Cloud (TSC) mass assignment schemes (MAS) is done. Using Fourier methods, the time derivative of the gravitational potential is computed using two different approaches: first, an exact solution that makes use of the full velocity field which should account for a contribution of both, Rees-Sciama and ISW effects. Second, a linear approximation related with the linear theory for the formation of LSS. We apply the method to three cosmological simulations: one, a box of 400 h-1 Mpc used to study the effects of the MAS on the estimation of the ISW effect. The other two, part of the MultiDark project, are used to study the effects of the resolution of the grid and of the approach used to compute the time derivative of the potential on the estimation of the ISW fluctuation. In the three cases we obtain coherent results with those expected in the literature for a ΛCDM cosmology with a signal in the expected range of 10–20 uK. Then, we apply our method on the data of 2MASS-GRS through a reconstruction of the mass density field using a halo based method (HBM). Using this reconstructions we find a low ISW signal due to the 2MASS density field. When comparing our 2MASS-ISW temperature with CMB surveys through cross-correlation and angular power spectrum we cannot find a correlation between both signals, fact that does not allow us to state for a positive detection of the ISW signal with our observational sample."