Controlling intrinsic-shear alignment in three-point weak lensing statistics

Three-point weak lensing statistics provide cosmic information that complements two-point statistics. However, both statistics suffer from intrinsic-shear alignment, which is one of their limiting systematics. The nulling technique is a model-independent method developed to eliminate intrinsic-shear alignment at the two-point level. In this paper we demonstrate that the nulling technique can also be naturally generalized to the three-point level, thereby controlling the corresponding GGI systematics. We show that under the assumption of exact redshift information the intrinsic-shear alignment contamination can be completely eliminated. To show how well the nulling technique performs on data with limited redshift information, we apply the nulling technique to three-point weak lensing statistics from a fictitious survey analogous to a typical future deep imaging survey, in which the three-point intrinsic-shear alignment systematics is generated from a power-law toy model. Using 10 redshift bins, the nulling technique leads to a factor of 10 suppression of the GGI/GGG ratio and reduces the bias on cosmological parameters to less than the original statistical error. More detailed redshift information allowing for finer redshift bins leads to better bias reduction performance. The information loss during the nulling procedure doubles the statistical error on cosmological parameters. A comparison of the nulling technique with an unconditioned compression of the data suggests that part of the information loss can be retained by considering higher order nulling weights during the nulling procedure. A combined analysis of two-and three-point statistics confirms that the information contained in them is of comparable size and is complementary, both before and after nulling.