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We introduce a coarse-graining transformation for tensor networks that can be applied to study both the partition function of a classical statistical system and the Euclidean path integral of a quantum many-body system.
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As originally described by Levin and Nave in Ref. [ 4 ] , the breakdown
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In this work (as in Levin and Nave’s TRG paper [ 4 ] ) a fixed-point tensor is a tensor that is (explicitly) invariant under coarse-graining [ 26 ]
Cited in the paper.
TEFR contains an entanglement filtering
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An arbitrary n n -point correlator will then be computed by first inserting n n operators in the tensor network of Eq. 1
Cited in the paper.
The role disentanglers play in TNR, where they remove short-range correlations, is analogous to their role in the context of entanglement renormalization of ground state wave-functions, where they remove short-range entanglement [ 12 ] . Hence the name
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The gauge transformation is made such that the block of four A A tensors is manifestly invariant with respect to reflection along the horizontal axis, which is a convenient choice in order to preserve reflection symmetry in the network
Cited in the paper.
2015
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