2019MNRAS.483.1922C

Gravitational clustering broadens the count-in-cells distribution of galaxies for surveys along uncorrelated (well-separated) lines of sight beyond Poisson noise. A number of methods have proposed to measure this excess 'cosmic' variance to constrain the galaxy bias (i.e. the strength of clustering) independently of the two-point correlation function. Here we present an observational application of these methods using data from 141 uncorrelated fields (∼700 arcmin² total) from Hubble's Brightest of Reionizing Galaxies (BoRG) survey. We use BoRG's broad-band imaging in optical and near-infrared to identify N ∼ 1000 photometric candidates at z ∼ 2 through a combination of colour selection and photometric redshift determination, building a magnitude-limited sample with m_AB <= 24.5 in F160W. We detect a clear excess in the variance of the galaxy number counts distribution compared to Poisson expectations, from which we estimate a galaxy bias b ≃ 3.63 ± 0.57. When divided by SED-fit classification into ∼400 early-type and ∼600 late-type candidates, we estimate biases of b_early ≃ 4.06 ± 0.67 and b_late ≃ 2.98 ± 0.98, respectively. These estimates are consistent with previous measurements of the bias from the two-point correlation function, and demonstrate that with N >= 100 sightlines, each containing N >= 5 objects, the counts-in-cell analysis provides a robust measurement of the bias. This implies that the method can be applied effectively to determine clustering properties (and characteristic dark-matter halo masses) of z ∼ 6-9 galaxies from a pure-parallel James Webb Space Telescope survey similar in design to Hubble's BoRG survey.