Monte Carlo Diagonalization for Hubbard Model

Abstract

The Hubbard model has often been studied with exact diagonalization (ED). This impurity solver is fundamentally limited by the exponential scaling of the Fock space. To address this problem, we introduce Monte Carlo diagonalization. Using a truncated Fock space constructed with a Monte Carlo approach, we reduce the size of the basis required to represent the Hamiltonian. We can then apply the Lanczos and band Lanczos algorithms in this truncated basis to find the ground state and the Green function. This results in a significant economy of resources, an important speed up in the computational time and the capacity to break the $\sim 20$-site limit of ED.

12 pages, 10 figures