A Bond weighted tensor renormalization group study of the q-state ferromagnetic Potts models on the square lattice
Abstract
It is known rigorously that the phase transition of the -state ferromagnetic Potts model on the square lattice is second order for . Despite this fact, some observables of the model show features of a first-order phase transition. For example, negative peak appears for the quantity of Binder ratio of this model. Such a non-monotonic behavior of is typically a consequence of phase coexistence, hence is served as a signal of a first-order phase transition. In particular, the negative peak should diverge with linear system size squared. Since the mentioned divergence phenomenon is not observed for the 4-state Potts model, the scenario of a first-order phase transition for this model is ruled out. Interestingly, a recent large scale Monte Carlo investigation of the 4-state Potts model observes that the two-peak structure of the energy density distribution becomes more noticeable when increases. This finding indicates the signal of coexistence of phases is getting stronger with . Due to these unusual critical behaviors, here we study the energy density and the specific heat of the 4-state Potts model on the square lattice using the technique of bond weighted tensor renormalization group (BWTRG). For a comparison purpose, and ferromagnetic Potts models on the square lattice are investigated using the same method as well. Remarkably, our results do imply there may be a small energy gap for model. While the appearance of the mentioned small energy gap can be explained plausibly and it will disappear with a more sophisticated investigation, our finding suggests that whether a message of a first-order phase transition is genuine or is an artificial effect requires further and detailed investigations.
Cite
@article{arxiv.2503.12361,
title = {A Bond weighted tensor renormalization group study of the q-state ferromagnetic Potts models on the square lattice},
author = {Yuan-Heng Tseng and Shang-Wei Li and Fu-Jiun Jiang},
journal= {arXiv preprint arXiv:2503.12361},
year = {2025}
}
Comments
10 pages, 17 figures