A New Wavelet Scattering Transform-Based Statistic for Cosmological Analysis of Large-Scale Structure
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866911289016582144 |
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| author | Jiang, Zhujun Luo, Xiaolin Du, Wenying Min, Zhiwei Yin, Fenfen Feng, Longlong Ding, Jiacheng Zhang, Le Li, Xiao-Dong |
| author_facet | Jiang, Zhujun Luo, Xiaolin Du, Wenying Min, Zhiwei Yin, Fenfen Feng, Longlong Ding, Jiacheng Zhang, Le Li, Xiao-Dong |
| contents | Large-scale structure (LSS) analysis in galaxy surveys is a powerful cosmological probe but is limited by tracer bias, which can obscure underlying information and weaken parameter constraints. Existing methods either model bias or restrict analyses to low-density regions, yet their sensitivity to bias remains poorly understood. We propose a novel method based on the wavelet scattering transform (WST) to distinguish LSS across cosmological models while mitigating tracer bias. Central to our approach are the WST $m$-mode ratios, $R^{\rm wst}$, a new statistical measure, and a high-density apodization preprocessing that smoothly rescales extreme values. We use a reduced chi-square to assess the cosmological parameter constraints and find that $R^{\rm wst}$, in the scale range $j \in [3,7]$, achieves $χ^2_{ν, \rm cos} \approx 6$ for cosmology while maintaining $χ^2_{ν, \rm bias} \sim 1$--a regime unattained by other statistics. $R^{\rm wst}$ thus provides robust cosmological sensitivity with effective bias mitigation for future surveys. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_14400 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A New Wavelet Scattering Transform-Based Statistic for Cosmological Analysis of Large-Scale Structure Jiang, Zhujun Luo, Xiaolin Du, Wenying Min, Zhiwei Yin, Fenfen Feng, Longlong Ding, Jiacheng Zhang, Le Li, Xiao-Dong Cosmology and Nongalactic Astrophysics Large-scale structure (LSS) analysis in galaxy surveys is a powerful cosmological probe but is limited by tracer bias, which can obscure underlying information and weaken parameter constraints. Existing methods either model bias or restrict analyses to low-density regions, yet their sensitivity to bias remains poorly understood. We propose a novel method based on the wavelet scattering transform (WST) to distinguish LSS across cosmological models while mitigating tracer bias. Central to our approach are the WST $m$-mode ratios, $R^{\rm wst}$, a new statistical measure, and a high-density apodization preprocessing that smoothly rescales extreme values. We use a reduced chi-square to assess the cosmological parameter constraints and find that $R^{\rm wst}$, in the scale range $j \in [3,7]$, achieves $χ^2_{ν, \rm cos} \approx 6$ for cosmology while maintaining $χ^2_{ν, \rm bias} \sim 1$--a regime unattained by other statistics. $R^{\rm wst}$ thus provides robust cosmological sensitivity with effective bias mitigation for future surveys. |
| title | A New Wavelet Scattering Transform-Based Statistic for Cosmological Analysis of Large-Scale Structure |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2505.14400 |