Cross-correlation of Planck CMB lensing with DESI galaxy groups

Sun, Zeyang; Yao, Ji; Dong, Fuyu; Yang, Xiaohu; Zhang, Le; Zhang, Pengjie

doi:10.48550/arxiv.2109.07387

Cited by 3 publications

(3 citation statements)

References 37 publications

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“…On the other hand, they provide essential information, such as the redshift information, to improve the cosmological applications of CMB lensing. Cross-correlation of CMB lensing with galaxies [43][44][45][46][47], galaxy groups and clusters [48][49][50][51] have already been detected. Since the AliCPT sky area is fully covered by the DESI footprint [52], AliCPT CMB lensing-DESI galaxy cross-correlation is a natural way of enhancing the science return of AliCPT.…”

Section: Introduction To Cmb Lensingmentioning

confidence: 94%

Forecasts on CMB lensing observations with AliCPT-1

Liu¹,

Sun²,

Han³

et al. 2022

Preprint

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AliCPT-1 is the first Chinese CMB experiment aiming for high precision measurement of Cosmic Microwave Background B-mode polarization. The telescope, currently under deployment in Tibet, will observe in two frequency bands centered at 90 and 150 GHz. We forecast the CMB lensing reconstruction, lensing-galaxy as well as lensing-CIB (Cosmic Infrared Background) cross correlation signal-to-noise ratio (SNR) for AliCPT-1. We consider two stages with different integrated observation time, namely "4 module*yr" (first stage) and "48 module*yr" (final stage). For lensing reconstruction, we use three different quadratic estimators, namely temperature-only, polarization-only and minimum-variance estimators, using curved sky geometry. We take into account the impact of inhomogeneous hit counts as well as of the mean-field bias due to incomplete sky coverage. In the first stage, our results show that the 150 GHz channel is able to measure the lensing signal at 15σ significance with the minimum-variance estimator. In the final stage, the measurement significance will increase to 31σ. We also combine the two frequency data in the harmonic domain to optimize the SNR. Our result show that the coadding procedure can significantly reduce the reconstruction bias in the multiple range > 800. Thanks to the high quality of the polarization data in the final stage of AliCPT-1, the EB estimator will dominate the lensing reconstruction in this stage. We also estimate the SNR of cross-correlations between AliCPT-1 CMB lensing and other tracers of the large scale structure of the universe. For its cross-correlation with DESI galaxies/quasars, we report the cross-correlation SNR = 10 ∼ 20 for the 4 redshift bins at 0.05 < z < 2.1. In the first stage, the total SNR is about 32. In the final stage, the lensing-galaxy cross-correlation can reach SNR=52. For lensing-CIB cross-correlation, in the first stage, the cross-correlation between AliCPT-1 lensing and Planck CIB 353, 545, 857 GHz channels are about SNR=18, 19, 23 respectively. In the final stage, the cross-correlation can reach SNR=25, 33 and 42. Due to the strong correlations between frequency bands, the total lensing-CIB cross-correlation by combining the three frequencies in Planck CIBs are SNR=23 and 43 for the AliCPT-1 first and final stage, respectively.

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Section: Introduction To Cmb Lensingmentioning

confidence: 94%

Forecasts on CMB lensing observations with AliCPT-1

Liu¹,

Sun²,

Han³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Marques & Bernui (2020) cross-correlated the combined galaxy clustering catalogue from SDSS, South Galactic Cap u-band Sky Survey (SCUSS), and Wide-field Infrared Survey Explorer (WISE) data with the Planck 2018 CMB lensing map, in order to estimate the linear growth of density fluctuations. Sun et al (2021) cross-correlated galaxy groups from the DESI Legacy Imaging Survey with the Planck 2018 CMB lensing to constrain the density bias of galaxy groups over various redshifts, mass and richness.…”

Section: Introductionmentioning

confidence: 99%

Impact of thermal SZ effect on cross-correlations between Planck CMB lensing and SDSS galaxy density fields

Chen,

Remazeilles

2022

Preprint

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Residual foreground contamination by thermal Sunyaev-Zeldovich (tSZ) effect from galaxy clusters in cosmic microwave background (CMB) maps propagates into the reconstructed CMB lensing field, and thus biases the intrinsic cross-correlation between CMB lensing and large-scale structure (LSS). Through stacking analysis, we show that residual tSZ contamination causes an increment of lensing convergence in the central part of the clusters and a decrement of lensing convergence in the cluster outskirts. We quantify the impact of residual tSZ contamination on cross-correlations between the Planck 2018 CMB lensing convergence maps and the SDSS-IV galaxy density data through cross-power spectrum computation. In contrast with the Planck 2018 tSZ-deprojected smica lensing map, our analysis using the tSZ-contaminated smica lensing map measures a ∼ 2.5% negative bias at multipoles 500 and transits to a ∼ 9% positive bias at 1500, which validates earlier theoretical predictions of the overall shape of such tSZ-induced spurious cross-correlation. The tSZ-induced lensing convergence field in Planck CMB data is detected with more than 1σ significance at 500 and more than 14σ significance at 1500, yielding an overall 14.8σ detection. We also show that masking galaxy clusters in CMB data is not sufficient to eliminate the spurious lensing signal, still detecting a non-negligible bias with 5.5σ significance on cross-correlations with galaxy density fields. Our results emphasize how essential it is to deproject the tSZ effect from CMB maps at the component separation stage and adopt tSZ-free CMB lensing maps for cross-correlations with LSS data.

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“…In addition to weak gravitational lensing (e.g. Han et al 2015;Luo et al 2018;Sun et al 2021), the total mass of galaxy clusters is often measured through dynamical modelling of observed tracer objects, such as the distribution of hot gas and satellite galaxies in clusters (e.g., Diaferio & Geller 1997;Biviano et al 2006;Wojtak et al 2008;Rasia et al 2012;Mamon et al 2013;Old et al 2014;Kodi Ramanah et al 2021;Li et al 2021).…”

Section: Introductionmentioning

confidence: 99%

What to expect from dynamical modelling of cluster haloes II. Investigating dynamical state indicators with Random Forest

Li,

Han,

Wang

et al. 2022

Preprint

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We investigate the importances of various dynamical features in predicting the dynamical state (DS) of galaxy clusters, based on the Random Forest (RF) machine learning approach. We use a large sample of galaxy clusters from the Three Hundred Project of hydrodynamical zoomed-in simulations, and construct dynamical features from the raw data as well as from the corresponding mock maps in the optical, X-ray, and Sunyaev-Zel'dovich (SZ) channels. Instead of relying on the impurity based feature importance of the RF algorithm, we directly use the out-of-bag (OOB) scores to evaluate the importances of individual features and different feature combinations. Among all the features studied, we find the virial ratio, 𝜂, to be the most important single feature. The features calculated directly from the simulations and in 3-dimensions carry more information on the DS than those constructed from the mock maps. Compared with the features based on X-ray or SZ maps, features related to the centroid positions are more important. Despite the large number of investigated features, a combination of up to three features of different types can already saturate the score of the prediction. Lastly, we show that the most sensitive feature 𝜂 is strongly correlated with the well-known half-mass bias in dynamical modelling. Without a selection in DS, cluster halos have an asymmetric distribution in 𝜂, corresponding to an overall positive half-mass bias. Our work provides a quantitative reference for selecting the best features to discriminate the DS of galaxy clusters in both simulations and observations.

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Cross-correlation of Planck CMB lensing with DESI galaxy groups

Cited by 3 publications

References 37 publications

Forecasts on CMB lensing observations with AliCPT-1

Forecasts on CMB lensing observations with AliCPT-1

Impact of thermal SZ effect on cross-correlations between Planck CMB lensing and SDSS galaxy density fields

What to expect from dynamical modelling of cluster haloes II. Investigating dynamical state indicators with Random Forest

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