Kavli Affiliate: Tom Abel
| First 5 Authors: Sihan Yuan, Boryana Hadzhiyska, Tom Abel, ,
| Summary:
Novel summary statistics beyond the standard 2-point correlation function
(2PCF) are necessary to capture the full astrophysical and cosmological
information from the small-scale (r < 30Mpc/h) galaxy clustering. However, the
analysis of beyond-2PCF statistics on small scales is challenging because we
lack the appropriate treatment of observational systematics for arbitrary
summary statistics of the galaxy field. In this paper, we develop a full
forward modeling pipeline for a wide range of summary statistics using the
large high-fidelity AbacusSummit lightcones that accounts for many systematic
effects but also remains flexible and computationally efficient to enable
posterior sampling. We apply our forward model approach to a fully realistic
mock galaxy catalog and demonstrate that we can recover unbiased constraints on
the underlying galaxy-halo connection model using two separate summary
statistics: the standard 2PCF and the novel k-th nearest neighbor (kNN)
statistics, which are sensitive to correlation functions of all orders. We will
extend this method to a full cosmology emulator in a follow up paper. We expect
this to become a powerful approach when applying to upcoming surveys such as
DESI where we can leverage a multitude of summary statistics across a wide
redshift range to maximally extract information from the non-linear scales.
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