Abstract
Upcoming galaxy surveys such as LSST and Euclid are expected to significantly
improve the power of weak lensing as a cosmological probe. In order to maximise
the information that can be extracted from these surveys, it is important to
explore novel statistics that complement standard weak lensing statistics such
as the shear-shear correlation function and peak counts. In this work, we use a
recently proposed weak lensing observable -- weak lensing voids -- to make
parameter constraint forecasts for an LSST-like survey. We make use of the
cosmo-SLICS suite of $w$CDM simulations to measure void statistics (abundance
and tangential shear) as a function of cosmological parameters. The simulation
data is used to train a Gaussian process regression emulator that we use to
generate likelihood contours and provide parameter constraints from mock
observations. We find that the void abundance is more constraining than the
tangential shear profiles, though the combination of the two gives additional
constraining power. We forecast that without tomographic decomposition, these
void statistics can constrain the matter fluctuation amplitude, $S_8$ within
0.7\% (68\% confidence interval), while offering 4.3, 4.7 and 6.9\% precision
on the matter density parameter, $Ømega_m$, the reduced Hubble constant,
$h$, and the dark energy equation of state parameter, $w_0$, respectively. We
find that these results are tighter than the constraints given by the
shear-shear correlation function with the same observational specifications,
indicating that weak lensing void statistics can be a promising cosmological
probe potentially complementary with other lensing tests.
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