Generalized Lanczos algorithm for variational quantum Monte Carlo

摘要: We show that the standard Lanczos algorithm can be efficiently implemented statistically and self-consistently improved, using stochastic reconfiguration method, which has been recently introduced to stabilize Monte Carlo sign problem instability. With this scheme a few steps over given variational wave function are possible even for large size as particular case of more general accurate technique allows obtain lower energies. This method tested extensively strongly correlated model like $t\ensuremath{-}J$ model. it is compute any kind correlation functions, with no computational effort. By fact variance $〈{H}^{2}〉\ensuremath{-}〈H{〉}^{2}$ zero an exact eigenstate, we approach solution iterations indeed $\ensuremath{\sim}100$ electrons reasonably good initial functions. The presented here in many-parameter energy optimization computable many-body function, including instance generic long-range Jastrow factors arbitrary site-dependent orbital determinants. improves further accuracy calculation, especially long-distance