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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.21509 |
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Table of Contents:
- In this study, we investigate the potential of mark-weighted angular correlation functions (MACFs), which integrate $β$-cosmic-web classification with angular correlation function analysis to improve cosmological constraints. Using SDSS DR12 CMASS-NGC galaxies and mock catalogs with $Ω_m$ varying from 0.25 to 0.40, we assess the discriminative power of different statistics via the average improvement in chi-squared, $Δ\overline{χ^2}$, across six redshift bins. This metric quantifies how effectively each statistic distinguishes between different cosmological models. Incorporating cosmic-web weights leads to substantial improvements. Using statistics weighted by the mean neighbor distance ($\bar{D}_{\rm nei}$) increases $Δ\overline{χ^2}$ by approximately 40%-130%, while applying inverse mean neighbor distance weighting ($1/\bar{D}_{\rm nei}$) yields even larger gains, boosting $Δ\overline{χ^2}$ by a factor of 2-3 compared to traditional unweighted angular statistics. These enhancements are consistent with previous 3D clustering results, demonstrating the superior sensitivity of the $β$-weighted approaches. Our method, based on thin redshift slices, is particularly suited for slitless surveys (e.g., Euclid, CSST) where redshift uncertainties limit 3D analyses. This study also offers a framework for applying marked statistics to 2D angular clustering.