2015/09/21 by M. Vargas-Magaña, Shirley Ho, Vargas-Magaña, M. +5 · 1 citation
Computer Science · Environmental Science · Physics and Astronomy · #Blind Source Separation Techniques #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Galaxies: Formation, Evolution, Phenomena #Remote Sensing in Agriculture
paper · pdf · doi:10.48550/arxiv.1509.06384
openalex publication_date 2015/09/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The reconstruction algorithm introduced by \citeEis07, which is widely used in clustering analysis, is based on the inference of the first order Lagrangian displacement field from the Gaussian smoothed galaxy density field in redshift space. The \modif2smoothing scale applied to the density field affects the inferred displacement field that is used to move the galaxies, and partially \modif2erases the nonlinear evolution of the density field. In this article, we explore this crucial step \modif2in the reconstruction algorithm. We study the performance of the reconstruction technique using two metrics: first, we study the performance using the anisotropic clustering, extending previous studies focused on isotropic clustering; second, we study its effect on the displacement field. We find that smoothing has a strong effect in the quadrupole of the correlation function and affects the accuracy and precision \modif2with which we can measure DA (z) and H(z). We find that the optimal smoothing scale to use in the reconstruction algorithm applied to BOSS-CMASS is between 5-10 h-1Mpc. Varying from the "usual" 15h-1Mpc to 5 h-1Mpc \modif2shows ∼ 0.3% variations in DA(z) and ∼ 0.4% H(z) and uncertainties are also reduced by 40% and 30% respectively. We also find that the accuracy of velocity field reconstruction depends strongly on the smoothing scale used for the density field. We measure the bias and uncertainties associated with different choices of smoothing length.