4.7 Article

The view from the boundary: a new void stacking method

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stw154

关键词

methods: data analysis; cosmology: theory; dark matter; large-scale structure of Universe

资金

  1. ERC Advanced Investigator grant COSMIWAY [GA 267291]
  2. Science and Technology Facilities Council [ST/F001166/1, ST/I00162X/1]
  3. Durham Junior Research Fellowship
  4. BIS National E-infrastructure capital grant [ST/K00042X/1]
  5. STFC capital grant [ST/H008519/1]
  6. STFC DiRAC Operations grant [ST/K003267/1]
  7. Durham University
  8. STFC [ST/I00162X/1, ST/M007006/1, ST/H008519/1, ST/K00042X/1] Funding Source: UKRI
  9. Science and Technology Facilities Council [ST/M007006/1, ST/I00162X/1, ST/H008519/1, ST/K00042X/1] Funding Source: researchfish

向作者/读者索取更多资源

We introduce a new method for stacking voids and deriving their profile that greatly increases the potential of voids as a tool for precision cosmology. Given that voids are distinctly non-spherical and have most of their mass at their edge, voids are better described relative to their boundary rather than relative to their centre, as in the conventional spherical stacking approach. The boundary profile is obtained by computing the distance of each volume element from the void boundary. Voids can then be stacked and their profiles computed as a function of this boundary distance. This approach enhances the weak lensing signal of voids, both shear and convergence, by a factor of 2 when compared to the spherical stacking method. It also results in steeper void density profiles that are characterized by a very slow rise inside the void and a pronounced density ridge at the void boundary. The resulting boundary density profile is self-similar when rescaled by the thickness of the density ridge, implying that the average rescaled profile is independent of void size. The boundary velocity profile is characterized by outflows in the inner regions whose amplitude scales with void size, and by a strong inflow into the filaments and walls delimiting the void. This new picture enables a straightforward discrimination between collapsing and expanding voids both for individual objects as well as for stacked samples.

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