Beyond Windability: An FPRAS for The Six-Vertex Model

Autor:	Fu, Zhiguo, Li, Junda, Yang, Xiongxin
Rok vydání:	2022
Předmět:	Mathematics - Probability Computer Science - Computational Complexity F.2.0
Druh dokumentu:	Working Paper
Popis:	The six-vertex model is an important model in statistical physics and has deep connections with counting problems. There have been some fully polynomial randomized approximation schemes (FPRAS) for the six-vertex model [30, 10], which all require that the constraint functions are windable. In the present paper, we give an FPRAS for the six-vertex model with an unwindable constraint function by Markov Chain Monte Carlo method (MCMC). Different from [10], we use the Glauber dynamics to design the Markov Chain depending on a circuit decomposition of the underlying graph. Moreover, we prove the rapid mixing of the Markov Chain by coupling, instead of canonical paths in [10]. Comment: 15 pages, 2 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2202.02999 Zobrazit plný text záznamu View this record from Arxiv