  Using hydrodynamical simulations, we study how well the underlying
gravitational potential of a galaxy cluster can be modelled dynamically with
different types of tracers. In order to segregate different systematics and the
effects of varying estimator performances, we first focus on applying a generic
minimal assumption method (oPDF) to model the simulated haloes using the full
6-D phasespace information. We show that the halo mass and concentration can be
recovered in an ensemble unbiased way, with a stochastic bias that varies from
halo to halo, mostly reflecting deviations from steady state in the tracer
distribution. The typical systematic uncertainty is $\sim 0.17$ dex in the
virial mass and $\sim 0.17$ dex in the concentration as well when dark matter
particles are used as tracers. The dynamical state of satellite galaxies are
close to that of dark matter particles, while intracluster stars are less in a
steady state, resulting in a $\sim$ 0.26 dex systematic uncertainty in mass.
Compared with galactic haloes hosting Milky-Way-like galaxies, cluster haloes
show a larger stochastic bias in the recovered mass profiles. We also test the
accuracy of using intracluster gas as a dynamical tracer modelled through a
generalised hydrostatic equilibrium equation, and find a comparable systematic
uncertainty in the estimated mass to that using dark matter. Lastly, we
demonstrate that our conclusions are largely applicable to other steady-state
dynamical models including the spherical Jeans equation, by quantitatively
segregating their statistical efficiencies and robustness to systematics. We
also estimate the limiting number of tracers that leads to the
systematics-dominated regime in each case.
