  Gaussian Quantum Monte Carlo (GQMC) is a stochastic phase space method for
fermions with positive weights. In the example of the Hubbard model close to
half filling it fails to reproduce all the symmetries of the ground state
leading to systematic errors at low temperatures. In a previous work [Phys.
Rev. B {\bf 72}, 224518 (2005)] we proposed to restore the broken symmetries by
projecting the density matrix obtained from the simulation onto the ground
state symmetry sector. For ground state properties, the accuracy of this method
depends on a {\it large overlap} between the GQMC and exact density matrices.
Thus, the method is not rigorously exact. We present the limits of the approach
by a systematic study of the method for 2 and 3 leg Hubbard ladders for
different fillings and on-site repulsion strengths. We show several indications
that the systematic errors stem from non-vanishing boundary terms in the
partial integration step in the derivation of the Fokker-Planck equation.
Checking for spiking trajectories and slow decaying probability distributions
provides an important test of the reliability of the results. Possible
solutions to avoid boundary terms are discussed. Furthermore we compare results
obtained from two different sampling methods: Reconfiguration of walkers and
the Metropolis algorithm.
