Worm Monte Carlo study of the honeycomb-lattice loop model
Qingquan Liu, Youjin Deng, Timothy M. Garoni

TL;DR
This paper introduces a new worm Monte Carlo algorithm for simulating the O(n) loop model on bipartite cubic graphs, rigorously proves its ergodicity, and uses it to analyze the model's critical behavior and phase transitions.
Contribution
The paper presents a novel worm algorithm applicable to the O(n) loop model on bipartite graphs, with rigorous proof of ergodicity and stationary distribution, enabling detailed study of critical phenomena.
Findings
Identified exact scaling exponents matching Coulomb gas theory.
Demonstrated the algorithm's effectiveness in simulating zero-temperature Potts antiferromagnets.
Confirmed phase transition in the 3-state Potts universality class for n>2.
Abstract
We present a Markov-chain Monte Carlo algorithm of "worm"type that correctly simulates the O(n) loop model on any (finite and connected) bipartite cubic graph, for any real n>0, and any edge weight, including the fully-packed limit of infinite edge weight. Furthermore, we prove rigorously that the algorithm is ergodic and has the correct stationary distribution. We emphasize that by using known exact mappings when n=2, this algorithm can be used to simulate a number of zero-temperature Potts antiferromagnets for which the Wang-Swendsen-Kotecky cluster algorithm is non-ergodic, including the 3-state model on the kagome-lattice and the 4-state model on the triangular-lattice. We then use this worm algorithm to perform a systematic study of the honeycomb-lattice loop model as a function of n<2, on the critical line and in the densely-packed and fully-packed phases. By comparing our…
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