J1-J2 fractal studied by multi-recursion tensor-network method
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, and , chosen to transform a regular square lattice () onto a fractal lattice if decreasing to zero (the fractal fully reconstructs when ). 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 planar fractal whose Hausdorff dimension at is . The generalized tensor-network algorithm is applicable to a wide range of fractal patterns and is suitable for models without translational invariance.
Keywords
Cite
@article{arxiv.2107.11406,
title = {J1-J2 fractal studied by multi-recursion tensor-network method},
author = {Jozef Genzor and Andrej Gendiar and Ying-Jer Kao},
journal= {arXiv preprint arXiv:2107.11406},
year = {2022}
}