Bias to CMB lensing reconstruction from temperature anisotropies due to large-scale galaxy motions

Gravitational lensing of the cosmic microwave background (CMB) is expected to be amongst the most powerful cosmological tools for ongoing and upcoming CMB experiments. In this work, we investigate a bias to CMB lensing reconstruction from temperature anisotropies due to the kinematic Sunyaev-Zel'dovich (kSZ) effect, that is, the Doppler shift of CMB photons induced by Compton scattering off moving electrons. The kSZ signal yields biases due to both its own intrinsic non-Gaussianity and its nonzero cross-correlation with the CMB lensing field (and other fields that trace the large-scale structure). This kSZ-induced bias affects both the CMB lensing autopower spectrum and its cross-correlation with low-redshift tracers. Furthermore, it cannot be removed by multifrequency foreground separation techniques because the kSZ effect preserves the blackbody spectrum of the CMB. While statistically negligible for current data sets, we show that it will be important for upcoming surveys, and failure to account for it can lead to large biases in constraints on neutrino masses or the properties of dark energy. For a stage 4 CMB experiment, the bias can be as large as ≈15 % or 12% in cross-correlation with LSST galaxy lensing convergence or galaxy overdensity maps, respectively, when the maximum temperature multipole used in the reconstruction is ℓma_x=4000 , and about half of that when ℓma_x=3000 . Similarly, we find that the CMB lensing autopower spectrum can be biased by up to several percent. These biases are many times larger than the expected statistical errors. We validate our analytical predictions with cosmological simulations and present the first complete estimate of secondary-induced CMB lensing biases. The predicted bias is sensitive to the small-scale gas distribution, which is affected by pressure and feedback mechanisms, thus making removal via "bias-hardened" estimators challenging. Reducing ℓma_x can significantly mitigate the bias at the cost of a decrease in the overall lensing reconstruction signal-to-noise. A bias ≲1 % on large scales requires ℓma_x≲2000 , which leads to a reduction in signal-to-noise by a factor of ≈3 - 5 for a stage 4 CMB experiment. Polarization-only reconstruction may be the most robust mitigation strategy.