Tensor network states and algorithms in the presence of a global U(1) symmetry

Physics – Condensed Matter – Strongly Correlated Electrons

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

22 pages, 25 figures, RevTeX 4

Scientific paper

10.1103/PhysRevB.83.115125

Tensor network decompositions offer an efficient description of certain many-body states of a lattice system and are the basis of a wealth of numerical simulation algorithms. In a recent paper [arXiv:0907.2994v1] we discussed how to incorporate a global internal symmetry, given by a compact, completely reducible group G, into tensor network decompositions and algorithms. Here we specialize to the case of Abelian groups and, for concreteness, to a U(1) symmetry, often associated with particle number conservation. We consider tensor networks made of tensors that are invariant (or covariant) under the symmetry, and explain how to decompose and manipulate such tensors in order to exploit their symmetry. In numerical calculations, the use of U(1) symmetric tensors allows selection of a specific number of particles, ensures the exact preservation of particle number, and significantly reduces computational costs. We illustrate all these points in the context of the multi-scale entanglement renormalization ansatz.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Tensor network states and algorithms in the presence of a global U(1) symmetry does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Tensor network states and algorithms in the presence of a global U(1) symmetry, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Tensor network states and algorithms in the presence of a global U(1) symmetry will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-332014

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.