Monte Carlo simulation with Tensor Network States
Abstract
It is demonstrated that Monte Carlo sampling can be used to efficiently extract the expectation value of projected entangled pair states with large virtual bond dimension. We use the simple update rule introduced by Xiang et al. to obtain the tensors describing the ground state wavefunction of the antiferromagnetic Heisenberg model and evaluate the finite size energy and staggered magnetization for square lattices with periodic boundary conditions of sizes up to L=16 and virtual bond dimensions up to D=16. The finite size magnetization errors are 0.003(2) and 0.013(2) at D=16 for a system of size L=8,16 respectively. Finite D extrapolation provides exact finite size magnetization for L=8, and reduces the magnetization error to 0.005(3) for L=16, significantly improving the previous state of the art results.
Cite
@article{arxiv.1010.5450,
title = {Monte Carlo simulation with Tensor Network States},
author = {Ling Wang and Iztok Pizorn and Frank Verstraete},
journal= {arXiv preprint arXiv:1010.5450},
year = {2011}
}
Comments
6 pages, 7 figures