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T. Xiang

4 papers hereh-index 4446 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cond-mat.stat-mech2
  • hep-lat2
same name
  • T. Xiang — 176 papers, h 43
  • T. Xiang — 156 papers, h 16
  • T. Xiang — 98 papers, h 91
  • T. Xiang — 61 papers, h 7
  • T. Xiang — 36 papers
  • T. Xiang — 29 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122014
most citedTensor renormalization group study of classical XY model on the square lattice

99 citations · 204 across the 3 of their papers we have counts for

collaborators

4 papers

hep-lat2014★ 40 cited

Progress towards quantum simulating the classical O(2) model

Haiyuan Zou, Yuzhi Liu, Chen-Yen Lai +8

We connect explicitly the classical O(2) model in 1+1 dimensions, a model sharing important features with U(1) lattice gauge theory, to physical models potentially implementabl…

hep-lat2013★ 65 cited

Controlling sign problems in spin models using tensor renormalization

Alan Denbleyker, Yuzhi Liu, Y. Meurice +5

We consider the sign problem for classical spin models at complex β=1/g02​ on L×L lattices. We show that the tensor renormalization group method allows reliable calculat…

cond-mat.stat-mech2013★ 99 cited

Tensor renormalization group study of classical XY model on the square lattice

J. F. Yu, Z. Y. Xie, Y. Meurice +6

Using the tensor renormalization group method based on the higher-order singular value decom- position, we have studied the thermodynamic properties of the continuous XY model on t…

cond-mat.stat-mech2012

Coarse-graining renormalization by higher-order singular value decomposition

Z. Y. Xie, J. Chen, M. P. Qin +3

We propose a novel coarse graining tensor renormalization group method based on the higher-order singular value decomposition. This method provides an accurate but low computationa…

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