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Clusters of galaxies, being the largest collapsed structures in the universe,offer valuable insights into the nature of cosmic evolution. Precisecalibration of the mass of clusters can be obtained by extracting theirgravitational lensing signal on the Cosmic Microwave Background (CMB)fluctuations. We extend and test here the performance achieved on clusterscales by the parameter-free, maximum a posteriori (MAP) CMB lensingreconstruction method, which has been shown to be optimal in the broadercontext of CMB lensing mass map and power spectrum estimation. In the contextof cluster lensing, the lensing signal of other large-scale structures acts asan additional source of noise. We show here that by delensing the CMBfluctuations around each and every cluster, this noise variance is reducedaccording to expectations. We also demonstrate that the well-known bias in thetemperature quadratic estimator in this regime, sourced by the strongnon-Gaussianity of the signal, is almost entirely mitigated without any scalecuts. Being statistically speaking an optimal and blind lensing mass mapreconstruction, the MAP estimator is a promising tool for the calibration ofthe masses of clusters.

Cluster profiles from beyond-the-QE CMB lensing mass maps