Kavli Affiliate: Tom Abel
| First 5 Authors: William R. Coulton, Tom Abel, Arka Banerjee, ,
| Summary:
Searches for primordial non-Gaussianity in cosmological perturbations are a
key means of revealing novel primordial physics. However, robustly extracting
signatures of primordial non-Gaussianity from non-linear scales of the
late-time Universe is an open problem. In this paper, we apply k-Nearest
Neighbor cumulative distribution functions, kNN-CDFs, to the
textsc{quijote-png} simulations to explore the sensitivity of kNN-CDFs to
primordial non-Gaussianity. An interesting result is that for halo samples with
$M_h<10^{14}$ M$_odot$/h, the kNN-CDFs respond to textit{equilateral} PNG in
a manner distinct from the other parameters. This persists in the galaxy
catalogs in redshift space and can be differentiated from the impact of galaxy
modelling, at least within the halo occupation distribution (HOD) framework
considered here. kNN-CDFs are related to counts-in-cells and, through mapping a
subset of the kNN-CDF measurements into the count-in-cells picture, we show
that our results can be modeled analytically. A caveat of the analysis is that
we only consider the HOD framework, including assembly bias. It will be
interesting to validate these results with other techniques for modeling the
galaxy–halo connection, e.g., (hybrid) effective field theory or
semi-analytical methods.
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