# Smoothing the redshift distributions of random samples for the baryon acoustic oscillations : applications to the SDSS-III BOSS DR12 and QPM mock samples

## TL;DR

This paper introduces a method to smooth the redshift distributions of random samples in galaxy surveys, improving BAO signal detection and cosmological parameter estimation from SDSS-III BOSS DR12 data.

## Contribution

It proposes a smooth function approach for redshift distributions of random samples, reducing fiducial fluctuations and enhancing BAO signal significance.

## Key findings

- BAO signal significance increased by 0.33σ in LOWZ sample
- Redshift distribution smoothing improves cosmological parameter accuracy
- Method effectively matches mock catalogue input parameters

## Abstract

We investigate the impact of different redshift distributions of random samples on the baryon acoustic oscillations (BAO) measurements of $D_V(z)r_\mathrm{d}^\mathrm{fid}/r_\mathrm{d}$ from the two-point correlation functions (2PCF) of galaxies in the Data Release 12 (DR12) of the Baryon Oscillation Spectroscopic Survey (BOSS). Big surveys, such as BOSS, usually assign redshifts to the random samples by randomly drawing values from the measured redshift distributions of the data, which would necessarily introduce fiducial signals of fluctuations into the random samples, weakening the signals of BAO, if the cosmic variance cannot be ignored. We propose a smooth function of redshift distribution that fits the data well to populate the random galaxy samples. The resulting cosmological parameters match the input parameters of the mock catalogue very well. The significance of BAO signals has been improved by $0.33\sigma$ for a low-redshift (LOWZ) sample and by $0.03\sigma$ for a constant-stellar-mass (CMASS) sample, though the absolute values do not change significantly. Given the precision of the measurements of current cosmological parameters, it would be appreciated for the future improvements on the measurements of galaxy clustering.