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Main Authors: Fang, Feng, Cai, Yan-Chuan, Li, Zhuoyang, Yue, Shiyu, Zhu, Weishan, Feng, Longlong
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2311.15903
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author Fang, Feng
Cai, Yan-Chuan
Li, Zhuoyang
Yue, Shiyu
Zhu, Weishan
Feng, Longlong
author_facet Fang, Feng
Cai, Yan-Chuan
Li, Zhuoyang
Yue, Shiyu
Zhu, Weishan
Feng, Longlong
contents The clustering of galaxies and their connections to their initial conditions is a major means by which we learn about cosmology. However, the stochasticity between galaxies and their underlying matter field is a major limitation for precise measurements of galaxy clustering. Efforts have been made with an optimal weighting scheme to reduce this stochasticity using the mass-dependent clustering of dark matter haloes. Here, we show that this is not optimal. We demonstrate that the cosmic-web environments (voids, sheets, filaments \& knots) of haloes, when combined linearly with the linear bias, provide extra information for reducing stochasticity in terms of two-point statistics. Using the environmental information alone can increase the signal-to-noise of clustering by a factor of 3 better than the white-noise level at the scales of the baryon acoustic oscillations. The information about the environment and halo mass are complementary. Their combination increases the signal-to-noise by another factor of 2-3. The information about the cosmic web correlates with other properties of haloes, including halo concentrations and tidal forces -- all are related to the assembly bias of haloes.
format Preprint
id arxiv_https___arxiv_org_abs_2311_15903
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Mass reconstruction and noise reduction with cosmic-web environments
Fang, Feng
Cai, Yan-Chuan
Li, Zhuoyang
Yue, Shiyu
Zhu, Weishan
Feng, Longlong
Cosmology and Nongalactic Astrophysics
The clustering of galaxies and their connections to their initial conditions is a major means by which we learn about cosmology. However, the stochasticity between galaxies and their underlying matter field is a major limitation for precise measurements of galaxy clustering. Efforts have been made with an optimal weighting scheme to reduce this stochasticity using the mass-dependent clustering of dark matter haloes. Here, we show that this is not optimal. We demonstrate that the cosmic-web environments (voids, sheets, filaments \& knots) of haloes, when combined linearly with the linear bias, provide extra information for reducing stochasticity in terms of two-point statistics. Using the environmental information alone can increase the signal-to-noise of clustering by a factor of 3 better than the white-noise level at the scales of the baryon acoustic oscillations. The information about the environment and halo mass are complementary. Their combination increases the signal-to-noise by another factor of 2-3. The information about the cosmic web correlates with other properties of haloes, including halo concentrations and tidal forces -- all are related to the assembly bias of haloes.
title Mass reconstruction and noise reduction with cosmic-web environments
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2311.15903