English

Petz recovery from subsystems in conformal field theory

High Energy Physics - Theory 2023-07-28 v1 Statistical Mechanics Strongly Correlated Electrons Quantum Physics

Abstract

We probe the multipartite entanglement structure of the vacuum state of a CFT in 1+1 dimensions, using recovery operations that attempt to reconstruct the density matrix in some region from its reduced density matrices on smaller subregions. We use an explicit recovery channel known as the twirled Petz map, and study distance measures such as the fidelity, relative entropy, and trace distance between the original state and the recovered state. One setup we study in detail involves three contiguous intervals AA, BB and CC on a spatial slice, where we can view these quantities as measuring correlations between AA and CC that are not mediated by the region BB that lies between them. We show that each of the distance measures is both UV finite and independent of the operator content of the CFT, and hence depends only on the central charge and the cross-ratio of the intervals. We evaluate these universal quantities numerically using lattice simulations in critical spin chain models, and derive their analytic forms in the limit where AA and CC are close using the OPE expansion. In the case where AA and CC are far apart, we find a surprising non-commutativity of the replica trick with the OPE limit. For all values of the cross-ratio, the fidelity is strictly better than a general information-theoretic lower bound in terms of the conditional mutual information. We also compare the mutual information between various subsystems in the original and recovered states, which leads to a more qualitative understanding of the differences between them. Further, we introduce generalizations of the recovery operation to more than three adjacent intervals, for which the fidelity is again universal with respect to the operator content.

Keywords

Cite

@article{arxiv.2307.14434,
  title  = {Petz recovery from subsystems in conformal field theory},
  author = {Shreya Vardhan and Annie Y. Wei and Yijian Zou},
  journal= {arXiv preprint arXiv:2307.14434},
  year   = {2023}
}

Comments

50+22 pages, 29 figures