J1-J2 fractal studied by multi-recursion tensor-network method

preprint2022arXivOpen access

Abstract

We generalize a tensor-network algorithm to study thermodynamic properties of self-similar spin lattices constructed on a square-lattice frame with two types of couplings, J1J_{1}^{} and J2J_{2}^{}, chosen to transform a regular square lattice (J1=J2J_{1}^{} = J_{2}^{}) onto a fractal lattice if decreasing J2J_{2}^{} to zero (the fractal fully reconstructs when J2=0J_{2}^{} = 0). We modified the Higher-Order Tensor Renormalization Group (HOTRG) algorithm for this purpose. Single-site measurements are performed by means of so-called impurity tensors. So far, only a single local tensor and uniform extension-contraction relations have been considered in HOTRG. We introduce ten independent local tensors, each being extended and contracted by fifteen different recursion relations. We applied the Ising model to the J1−J2J_{1}^{}-J_{2}^{} planar fractal whose Hausdorff dimension at J2=0J_{2}^{} = 0 is d(H)=ln⁡12/ln⁡4≈1.792d^{(H)} = \ln 12 / \ln 4 \approx 1.792. The generalized tensor-network algorithm is applicable to a wide range of fractal patterns and is suitable for models without translational invariance.

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