Controlling and leveraging small-scale information in tomographic galaxy-galaxy lensing

The tangential shear signal receives contributions from physical scales in the galaxy-matter correlation function well below the transverse scale at which it is measured. Since small scales are difficult to model, this non-locality has generally required stringent scale cuts or new statistics for cosmological analyses. Using the fact that uncertainty in these contributions corresponds to an uncertainty in the enclosed projected mass around the lens, we provide an analytic marginalization scheme to account for this. Our approach enables the inclusion of measurements on smaller scales without requiring numerical sampling over extra free parameters. We extend the analytic marginalization formalism to retain cosmographic (shear-ratio) information from small-scale measurements that would otherwise be removed due to modelling uncertainties, again without requiring the addition of extra sampling parameters. We test the methodology using simulated likelihood analysis of a Dark Energy Survey Year 5-like galaxy-galaxy lensing and galaxy clustering datavector. We demonstrate that we can remove parameter biases due to the presence of an unmodelled one-halo contamination of the galaxy-galaxy lensing signal, and use the shear-ratio information on small scales to improve cosmological parameter constraints.