Observational determination of the galaxy bias from cosmic variance with a random pointing survey: Clustering of z~2 galaxies from Hubble’s BoRG survey. (arXiv:1811.03625v1 [astro-ph.GA])
<a href="http://arxiv.org/find/astro-ph/1/au:+Cameron_A/0/1/0/all/0/1">Alex Cameron</a> (1 and 2), <a href="http://arxiv.org/find/astro-ph/1/au:+Trenti_M/0/1/0/all/0/1">Michele Trenti</a> (1 and 2), <a href="http://arxiv.org/find/astro-ph/1/au:+Livermore_R/0/1/0/all/0/1">Rachael Livermore</a> (1 and 2), <a href="http://arxiv.org/find/astro-ph/1/au:+Velden_C/0/1/0/all/0/1">Cameron van der Velden</a> (1) ((1) The University of Melbourne, (2) ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions)
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 arcmin$^2$ 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 $m_{AB}leq24.5$ 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 $b approx 3.63 pm 0.57$. When divided by
SED-fit classification into ~400 early-type and ~600 late-type candidates, we
estimate biases of $b_{early} approx 4.06 pm 0.67$ and $b_{late} approx 2.98
pm 0.98$ respectively. These estimates are consistent with previous
measurements of the bias from the two-point correlation function, and
demonstrate that with $Ngtrsim100$ sight-lines, each containing $Ngtrsim5$
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.
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 arcmin$^2$ 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 $m_{AB}leq24.5$ 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 $b approx 3.63 pm 0.57$. When divided by
SED-fit classification into ~400 early-type and ~600 late-type candidates, we
estimate biases of $b_{early} approx 4.06 pm 0.67$ and $b_{late} approx 2.98
pm 0.98$ respectively. These estimates are consistent with previous
measurements of the bias from the two-point correlation function, and
demonstrate that with $Ngtrsim100$ sight-lines, each containing $Ngtrsim5$
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.
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