Numerical Linked-Cluster Expansion Implemented Using igraph

Numerical linked-cluster expansions have been used to study exact finite-temperature properties of quantum lattice models in the thermodynamic model. The algorithm involves identifying unique clusters that can be embedded in a lattice, their symmetries, and other properties. Here, we demonstrate that the method can be implemented efficiently in Python using the igraph package. We extend the application to lattice geometries with more than one type of bond and study the thermodynamic properties of the Ising model with next-nearest-neighbor interactions.