Turning dispersion into signal: density-split analyses of pairwise velocities
Aritra Kumar Gon, Yan-Chuan Cai

TL;DR
This paper introduces a density-split analysis method for pairwise velocities in large-scale structures, enhancing the extraction of cosmological information by leveraging environmental differences to turn dispersion into a signal.
Contribution
It demonstrates that splitting data by density environment significantly improves the signal-to-noise ratio in pairwise velocity measurements, revealing new ways to utilize velocity dispersion.
Findings
Splitting by density environment increases measurement precision.
Environmental differences cause opposite signs in streaming velocities.
Global measurements mask valuable information in velocity distributions.
Abstract
Pairwise velocities of the large-scale structure encode valuable information about the growth of structure. They can be observed indirectly through redshift-space distortions and the kinetic Sunyaev-Zeldovich effect. Whether it is Gaussian or non-Gaussian, pairwise velocity has a broad distribution, but the cosmologically useful information lies primarily in the mean - the streaming velocities; the dispersion around the mean is often treated as a nuisance and marginalized over. This conventional approach reduces the constraining power of our observations. Here, we show that this does not have to be the case, provided the physics behind the dispersion is understood. We demonstrate that by splitting the halo/galaxy samples according to their density environments and measuring the streaming velocities separately, the total signal-to-noise is several times greater than in conventional…
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