Abstract

The reconstruction algorithm introduced by Eisenstein et al., 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 smoothing scale applied to the density field affects the inferred displacement field that is used to move the galaxies, and partially erases the non-linear evolution of the density field. In this article, we explore this crucial step in 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; secondly, 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 with which we can measure DA(z) and H(z). We find that the optimal smoothing scale to use in the reconstruction algorithm applied to Baryonic Oscillations Spectroscopic Survey-Constant (stellar) MASS (CMASS) is between 5 and 10 h−1 Mpc. Varying from the ‘usual’ 15–5 h−1 Mpc shows ∼0.3 per cent variations in DA(z) and ∼0.4 per cent H(z) and uncertainties are also reduced by 40 per cent and 30 per cent, 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.

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