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arXiv · 2207.07713

Forecast of cross-correlation of CSST cosmic shear tomography with AliCPT-1 CMB lensing

Zhengyi Wang·Ji Yao·Xiangkun Liu·Dezi Liu·Zuhui Fan·Bin Hu
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Abstract

We present a forecast study on the cross-correlation between cosmic shear tomography from the Chinese Survey Space Telescope (CSST) and CMB lensing from Ali CMB Polarization Telescope (AliCPT-1) in Tibet. The correlated galaxy and CMB lensing signals were generated from Gaussian realizations based on inputted auto- and cross-spectra. To account for the error budget, we considered the CMB lensing reconstruction noise based on the AliCPT-1 lensing reconstruction pipeline; shape noise of the galaxy lensing measurement; CSST photo-$z$ error; photo-$z$ bias; intrinsic alignment effect, and multiplicative bias. The AliCPT-1 CMB lensing mock data were generated according to two experimental stages, namely the ``4 modules*yr'' and ``48 modules*yr'' cases. We estimate the cross-spectra in 4 tomographic bins according to the CSST photo-$z$ distribution in the range of $z\in[0,4)$. After reconstructing the pseudo-cross-spectra from the realizations, we calculate the signal-to-noise ratio (SNR). By combining the 4 photo-$z$ bins, the total cross-correlation SNR$\approx15$ (AliCPT-1 ``4 modules*yr'') and SNR$\approx22$ (AliCPT-1 ``48 modules*yr''). Finally, we study the cosmological application of this cross-correlation signal. Excluding intrinsic alignment (IA) in the template fitting would lead to roughly a $0.6\sigma$ increment in $\sigma_8$ due to the negative IA contribution to the galaxy lensing data. For AliCPT-1 first and second stages, the cross-correlation of CSST cosmic shear with CMB lensing gives errors on the clustering amplitude $\sigma_{\sigma_8}=^{+0.043}_{-0.038}$ or $\sigma_{S_8}=\pm 0.031$ and $\sigma_{\sigma_8}=^{+0.030}_{-0.027}$ or $\sigma_{S_8}=\pm 0.018$, respectively.

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Zhengyi Wang, Ji Yao, Xiangkun Liu, Dezi Liu, Zuhui Fan, Bin Hu. 2022-07-15. Forecast of cross-correlation of CSST cosmic shear tomography with AliCPT-1 CMB lensing. https://doi.org/10.1093/mnras%2Fstad1592

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