Abstract
We present a matrix product state (MPS) algorithm to approximate ground states of translationally invariant systems with periodic boundary conditions. For a fixed value of the bond dimension of the MPS, we discuss how to minimize the computational cost to obtain a seemingly optimal MPS approximation to the ground state. In a chain with sites and correlation length , the computational cost formally scales as , where is a nontrivial function. For , this scaling reduces to , independent of the system size , making our method times faster than previous proposals. We apply the algorithm to obtain MPS approximations for the ground states of the critical quantum Ising and Heisenberg spin- models as well as for the noncritical Heisenberg spin- model. In the critical case, for any chain length , we find a model-dependent bond dimension above which the polynomial decay of correlations is faithfully reproduced throughout the entire system.
8 More- Received 27 May 2010
DOI:https://doi.org/10.1103/PhysRevB.83.125104
©2011 American Physical Society