Robustness of cosmic void statistics: insights from SDSS DR7 and the ELUCID simulation

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ID: 318020
2026
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Abstract
Abstract We present a systematic analysis of the statistical properties of cosmic voids using galaxies from the Sloan Digital Sky Survey Data Release 7 (SDSS DR7) and subhaloes from the ELUCID constrained simulation. By comparing voids identified in redshift space, real space, and reconstructed volumes, we assess the impact of redshift-space distortions (RSD) and tracer bias. Using the VAST toolkit, we apply both the geometry-based VoidFinder algorithm and watershed-based methods. We find that void properties are not equally robust. The three-dimensional morphology of voids, quantified by their sphericity and triaxiality, remains stable across different reconstructions and tracer selections. In contrast, void size distributions and radial density profiles depend strongly on the identification algorithm, with watershed-based methods systematically producing larger voids and higher compensation walls than VoidFinder. Using the full ELUCID simulation box, we show that tracer bias mainly affects void density profiles, with noticeable changes only for the most massive subhaloes (>1011.5 h−1M⊙). The agreement between SDSS observations, the ELUCID reconstruction, and the full simulation box demonstrates the high fidelity of constrained simulations and reveals a clear hierarchy in the robustness of void statistics.
Reference Key
openalex_W7165151188 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Youcai Zhang, X L Yang, Hong Guo, P Wang, Feng Shi
Journal monthly notices of the royal astronomical society
Year 2026
DOI
10.1093/mnras/stag1160
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