Abstract:
Gaussian Quantum Monte Carlo (GQMC) is a stochastic method to
simulate fermionic systems with positive weights. However, 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. We propose to restore these
symmetries a posteriori by a projection onto the ground state
symmetry sector. Recent results for Hubbard ladders are presented. We
show that non-vanishing boundary terms (fat tailed distributions) are
a possible source of the systematic errors.