English

Continuous tensor network renormalization for quantum fields

High Energy Physics - Theory 2018-09-17 v1 Strongly Correlated Electrons Quantum Physics

Abstract

On the lattice, a renormalization group (RG) flow for two-dimensional partition functions expressed as a tensor network can be obtained using the tensor network renormalization (TNR) algorithm [G. Evenbly, G. Vidal, Phys. Rev. Lett. 115 (18), 180405 (2015)]. In this work we explain how to extend TNR to field theories in the continuum. First, a short-distance length scale 1/Λ1/\Lambda is introduced in the continuum partition function by smearing the fields. The resulting object is still defined in the continuum but has no fluctuations at distances shorter than 1/Λ1/\Lambda. An infinitesimal coarse-graining step is then generated by the combined action of a rescalingrescaling operator LL and a disentanglingdisentangling operator KK that implements a quasi-local field redefinition. As demonstrated for a free boson in two dimensions, continuous TNR exactly preserves translation and rotation symmetries and can generate a proper RG flow. Moreover, from a critical fixed point of this RG flow one can then extract the conformal data of the underlying conformal field theory.

Keywords

Cite

@article{arxiv.1809.05176,
  title  = {Continuous tensor network renormalization for quantum fields},
  author = {Qi Hu and Adrian Franco-Rubio and Guifre Vidal},
  journal= {arXiv preprint arXiv:1809.05176},
  year   = {2018}
}

Comments

4+7 pages, 5 figures