Abstract
Spherical Jeans modelling is widely used to estimate mass profiles of systems from star clusters to galactic stellar haloes to clusters of galaxies. It derives the cumulative mass profile, M(<r), from kinematics of tracers of the potential under the assumptions of spherical symmetry and dynamical equilibrium. We consider the application of Jeans modelling to mapping the dark matter distribution in the outer reaches of the Milky Way using field halo stars. We present a novel non-parametric routine for solving the spherical Jeans equation by fitting B-splines to the velocity and density profiles of halo stars. While most implementations assume parametric forms for these profiles, B-splines provide non-parametric fitting curves with analytical derivatives. Our routine recovers the mass profiles of equilibrium systems with flattened haloes or a stellar disc and bulge excellently (less than or similar to 10 per cent error at most radii). Tests with non-equilibrium, Milky Way-like galaxies from the Latte suite of the Feedback In Realistic Environments model 2 (FIRE-2) simulations perform quite well (less than or similar to 15 per cent error for r less than or similar to 100 kpc). We also create observationally motivated data sets for the Latte suite by imposing selection functions and errors on phase-space coordinates characteristic of Gaia and the Dark Energy Spectroscopic Instrument (DESI) Milky Way Survey. The resulting imprecise and incomplete data require us to introduce a Markov chain Monte Carlo (MCMC)-based subroutine to obtain deconvolved density and velocity dispersion profiles from the tracer population. With these observational effects taken into account, the accuracy of the Jeans mass estimate remains at the level 20 per cent or better.