Recovering dark-matter clustering from galaxies with Gaussianization
Nuala McCullagh, Mark Neyrinck, Peder Norberg, Shaun Cole

TL;DR
This paper evaluates the Gaussianization transform's ability to recover dark matter clustering from galaxy samples, demonstrating its effectiveness in real space and identifying limitations in redshift space due to galaxy velocity effects.
Contribution
It provides a thorough assessment of Gaussianization on realistic galaxy samples, highlighting its potential and limitations for dark matter power spectrum recovery.
Findings
Gaussianization aligns galaxy power spectra with dark matter in real space
Breakdown of agreement in redshift space due to fingers of god
Redshift space agreement restored after finger-of-god compression
Abstract
The Gaussianization transform has been proposed as a method to remove the issues of scale-dependent galaxy bias and nonlinearity from galaxy clustering statistics, but these benefits have yet to be thoroughly tested for realistic galaxy samples. In this paper, we test the effectiveness of the Gaussianization transform for different galaxy types by applying it to realistic simulated blue and red galaxy samples. We show that in real space, the shapes of the Gaussianized power spectra of both red and blue galaxies agree with that of the underlying dark matter, with the initial power spectrum, and with each other to smaller scales than do the statistics of the usual (untransformed) density field. However, we find that the agreement in the Gaussianized statistics breaks down in redshift space. We attribute this to the fact that red and blue galaxies exhibit very different fingers of god in…
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