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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 Sloan Digital Sky Survey-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 an similar to 2.5 per cent negative bias at multipoles l less than or similar to 500 and transits to an similar to 9 per cent positive bias at l greater than or similar to 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 1 sigma significance at l less than or similar to 500 and more than 14 sigma significance at l greater than or similar to 1500, yielding an overall 14.8 sigma 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 5.5 sigma 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.
Frédéric Courbin, Georges Meylan, Yi Wang, Richard Massey
Frédéric Courbin, Georges Meylan, Gianluca Castignani, Maurizio Martinelli, Malte Tewes, Slobodan Ilic, Alessandro Pezzotta, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina
Jean-Paul Richard Kneib, Huanyuan Shan, Nan Li