Green Function Monte Carlo with Stochastic Reconfiguration

Abstract

A new method for the stabilization of the sign problem in the Green function Monte Carlo technique is proposed. The method is devised for real lattice Hamiltonians and is based on an iterative ``stochastic reconfiguration'' scheme which introduces some bias but allows a stable simulation with constant sign. The systematic reduction of this bias is possible in principle. The method is applied to the frustrated ${J}_{1}{\ensuremath{-}J}_{2}$ Heisenberg model, and tested against exact diagonalization data. Evidence of a finite spin gap for ${J}_{2}{/J}_{1}>\ensuremath{\sim}0.4$ is found in the thermodynamic limit.