A foreground-immune CMB-cluster lensing estimator

Abstract Galaxy clusters induce a distinct dipole pattern in the cosmic microwave back-ground (CMB) through effect of gravitational lensing. Extracting this lensing signal will enable us to constrain cluster masses, even for high redshift ( z ≳ 1) that are expected be detected by future CMB surveys. However, cluster-correlated foreground signals, like kinematic and thermal Sunyaev-Zel'dovich (kSZ tSZ) present challenge when extracting from temperature data. While polarization-based reconstruction is one way mitigate these biases, sensitivity temperature-based similar or higher than polarization In work, we extend estimator developed [1] test its robustness against systematic biases signals. We find kSZ only acts as an additional source variance provide simple stacking-based approach bias tSZ signal. Additionally, study induced due uncertainties positions show they can easily mitigated. The estimated signal-to-noise ratio (SNR) comparable other standard estimators such maximum likelihood (MLE) quadratic (QE) estimators. predict mass data current samples be: 6.6% SPT-3G with 7,000 clusters, 4.1% SO 3.9% + FYST 25,000 1.8% CMB-S4 100,000 clusters.