Abstract
The critical 2d classical Ising model on the square lattice has two topological conformal defects: the symmetry defect and the Kramers-Wannier duality defect . These two defects implement antiperiodic boundary conditions and a more exotic form of twisted boundary conditions, respectively. On the torus, the partition function of the critical Ising model in the presence of a topological conformal defect is expressed in terms of the scaling dimensions and conformal spins of a distinct set of primary fields (and their descendants, or conformal towers) of the Ising CFT. This characteristic conformal data can be extracted from the eigenvalue spectrum of a transfer matrix for the partition function . In this paper we investigate the use of tensor network techniques to both represent and coarse-grain the partition functions and of the critical Ising model with either a symmetry defect or a duality defect . We also explain how to coarse-grain the corresponding transfer matrices and , from which we can extract accurate numerical estimates of and . Two key new ingredients of our approach are (i) coarse-graining of the defect , which applies to any (i.e. not just topological) conformal defect and yields a set of associated scaling dimensions , and (ii) construction and coarse-graining of a generalized translation operator using a local unitary transformation that moves the defect, which only exist for topological conformal defects and yields the corresponding conformal spins .
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