Mapping Dark Matter in Merging Clusters with Weak Lensing for CSST: Morphology and Filament Recovery
6 affiliations
- 1Chinese Academy of Sciences
- 2University of Chinese Academy of Science
- 3Beijing Normal University
- 4Yunnan University
- 5Shanghai Astronomical Observatory (SHAO)
- 6University of Chinese Academy of Sciences
Abstract
Weak gravitational lensing offers a direct probe of the projected dark matter distribution in cluster-scale structures and the surrounding cosmic web. We investigate the capability of the China Space Station Telescope (CSST) to recover nonspherical dark matter morphologies using mock reduced-shear maps generated from cosmological N-body simulations. We apply the deep-learning-based MIU ² Net mass-reconstruction framework to CSST-like wide- and deep-field source densities, focusing on two representative systems: filament-connected halo pairs and elongated halos. MIU ² Net accurately recovers halo centers, elongated mass distributions, and the filamentary structures connecting halo pairs in both survey configurations. Halo centers are localized within about 0.1 h ⁻¹ Mpc, and elongated-halo shapes and orientations are reliably recovered. Filament paths are stable against shape noise, with mean normalized instability parameters I F , defined as the mean deviation from the true filament locus in units of R ₂₀₀ , decreasing from 0.041–0.037 in the low-redshift bin and from 0.051–0.045 in the high-redshift bin from the wide to deep field. The recovered filament shapes remain consistent with the true maps at the percent level. Compared with conventional Kaiser–Squires reconstruction, MIU ² Net better preserves low-contrast anisotropic structures while suppressing small-scale noise. These results demonstrate that CSST weak-lensing data, combined with machine-learning-based mass reconstruction, will enable statistical studies of cluster assembly, anisotropic matter accretion, and the connection between massive halos and the filamentary cosmic web.
Related
- Lensing in the Blue. III. Weak-lensing Shape Catalogs of 30 Merging Galaxy Clusters
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- ROLLIN': Rotating Globular Cluster Simulations: II. The complex morphology of globular clusters driven by multi-scale dynamics
- Euclid: Quick Data Release (Q1) -- Exploring the detailed visual morphology of galaxies in clusters
- AGN Reverberation Mapping with LITMUS: Fundamental Limits on lag Recovery Rates
BibTeX
@article{chen2026mapping,
title = {{Mapping Dark Matter in Merging Clusters with Weak Lensing for CSST: Morphology and Filament Recovery}},
author = {Xinyue Chen and Ran Li and Qiao Wang and Hengjie Lin and Liang Gao and Xiangkun Liu and Huanyuan Shan and Ji Yao and Ming Li},
journal = {The Astrophysical Journal},
year = {2026},
month = nov,
doi = {10.3847/1538-4357/aeb2fd},
url = {https://iopscience.iop.org/article/10.3847/1538-4357/aeb2fd},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Mapping Dark Matter in Merging Clusters with Weak Lensing for CSST: Morphology and Filament Recovery
AU - Xinyue Chen
AU - Ran Li
AU - Qiao Wang
AU - Hengjie Lin
AU - Liang Gao
AU - Xiangkun Liu
AU - Huanyuan Shan
AU - Ji Yao
AU - Ming Li
PY - 2026
DA - 2026/11/02
JO - The Astrophysical Journal
DO - 10.3847/1538-4357/aeb2fd
UR - https://iopscience.iop.org/article/10.3847/1538-4357/aeb2fd
AB - Weak gravitational lensing offers a direct probe of the projected dark matter distribution in cluster-scale structures and the surrounding cosmic web. We investigate the capability of the China Space Station Telescope (CSST) to recover nonspherical dark matter morphologies using mock reduced-shear maps generated from cosmological N-body simulations. We apply the deep-learning-based MIU ² Net mass-reconstruction framework to CSST-like wide- and deep-field source densities, focusing on two representative systems: filament-connected halo pairs and elongated halos. MIU ² Net accurately recovers halo centers, elongated mass distributions, and the filamentary structures connecting halo pairs in both survey configurations. Halo centers are localized within about 0.1 h ⁻¹ Mpc, and elongated-halo shapes and orientations are reliably recovered. Filament paths are stable against shape noise, with mean normalized instability parameters I F , defined as the mean deviation from the true filament locus in units of R ₂₀₀ , decreasing from 0.041–0.037 in the low-redshift bin and from 0.051–0.045 in the high-redshift bin from the wide to deep field. The recovered filament shapes remain consistent with the true maps at the percent level. Compared with conventional Kaiser–Squires reconstruction, MIU ² Net better preserves low-contrast anisotropic structures while suppressing small-scale noise. These results demonstrate that CSST weak-lensing data, combined with machine-learning-based mass reconstruction, will enable statistical studies of cluster assembly, anisotropic matter accretion, and the connection between massive halos and the filamentary cosmic web.
SN - 1538-4357
SN - 0004-637X
ER -