Abstract
We use a new non-parametric gravitational modelling tool - GLASS - to determine what quality of data (strong lensing, stellar kinematics, and/or stellar masses) are required to measure the circularly averaged mass profile of a lens and its shape. GLASS uses an underconstrained adaptive grid of mass pixels to model the lens, searching through thousands of models to marginalize over model uncertainties. Our key findings are as follows: (i) for pure lens data, multiple sources with wide redshift separation give the strongest constraints as this breaks the well-known mass-sheet or steepness degeneracy; (ii) a single quad with time delays also performs well, giving a good recovery of both the mass profile and its shape; (iii) stellar masses - for lenses where the stars dominate the central potential - can also break the steepness degeneracy, giving a recovery for doubles almost as good as having a quad with time-delay data, or multiple source redshifts; (iv) stellar kinematics provide a robust measure of the mass at the half-light radius of the stars r(1/2) that can also break the steepness degeneracy if the Einstein radius r(E) not equal r(1/2); and (v) if r(E) similar to r(1/2), then stellar kinematic data can be used to probe the stellar velocity anisotropy beta - an interesting quantity in its own right. Where information on the mass distribution from lensing and/or other probes becomes redundant, this opens up the possibility of using strong lensing to constrain cosmological models.