News

  • Title: "General Entanglement Branching in a Tensor Network" (invited)
  • Date of presentation: 14th Dec. 2016.
  • Conference: Fourth Workshop on Tensor Network States: Algorithms and Applications
  • Conference dates: From 12th Dec. 2016 to 15th Dec. 2016.
  • Venue: National Center for Theoretical Sciences, Hsinchu, Taiwan
  • URL:http://www.phys.cts.nthu.edu.tw/actnews/index.php?Sn=318

Tensor network is a new language for talking about many-body problems. Having emerged from quantum information description of simple wave functions, it is now regarded as an extremely precise method for computing partition functions of classical or quantum lattice models, a wave function describing novel quantum states, a new framework of real-space renormalization group, a representation manifesting hidden symmetries and orders, a cure to the notorious negative-sign problem, a systematic way of information compression, a computable representation of AdS/CFT correspondence, ...

The main objective of this workshop is to achieve a better understanding of tensor-network states and tensor-network methods in quantum many-body problems. Related physical systems and numerical methods will be also discussed.

REFERENCE Physical Review B 92 (2015) 134404
DOI 10.1103/PhysRevB.92.134404
AUTHOR Tsuyoshi Okubo, Kenji Harada, Jie Lou, and Naoki Kawashima
ABSTRACT The SU(N) symmetric antiferromagnetic Heisenberg model with multicolumn representations on the two- dimensional square lattice is investigated by quantum Monte Carlo simulations. For the representation of a Young diagram with two columns, we confirm that a valence-bond solid (VBS) order appears as soon as the Néel order disappears at N = 10, indicating no intermediate phase. In the case of the representation with three columns, there is no evidence for either the Néel or the VBS ordering for N >= 15. This is actually consistent with the large-N theory, which predicts that the VBS state immediately follows the Néel state, because the expected spontaneous order is too weak to be detected.

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