Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Zhang, Wanzhou"'
Disordered lattice spin systems are crucial in both theoretical and applied physics. However, understanding their properties poses significant challenges for Monte Carlo simulations. In this work, we investigate the two-dimensional random-bond Ising
Externí odkaz:
http://arxiv.org/abs/2409.06538
Inspired by the stable bilayer water ice grown in the laboratory (Nature 577, 60, 2020), we propose a model representing water ice as a two-layer six-vertex model. Using the loop update Monte Carlo method, we unveil meaningful findings. While the squ
Externí odkaz:
http://arxiv.org/abs/2404.05996
Publikováno v:
Chin. Phys. B 33, 040503 (2024)
The two-component cold atom systems with anisotropic hopping amplitudes can be phenomenologically described by a two-dimensional Ising-XY coupled model with spatial anisotropy. At low temperatures, theoretical predictions [Phys. Rev. A 72, 053604 (20
Externí odkaz:
http://arxiv.org/abs/2310.20314
In recent years, developing unsupervised machine learning for identifying phase transition is a research direction. In this paper, we introduce a two-times clustering method that can help select perfect configurations from a set of degenerate samples
Externí odkaz:
http://arxiv.org/abs/2305.17687
We study the surface criticality of a three-dimensional classical antiferromagnetic Potts model, whose bulk critical behaviors belongs to the XY model because of emergent O(2) symmetry. We find that the surface antiferromagnetic next-nearest neighbor
Externí odkaz:
http://arxiv.org/abs/2301.08926
Percolation is an important topic in climate, physics, materials science, epidemiology, finance, and so on. Prediction of percolation thresholds with machine learning methods remains challenging. In this paper, we build a powerful graph convolutional
Externí odkaz:
http://arxiv.org/abs/2207.03368
Publikováno v:
Phys. Rev. E 107, 065303 (2023)
Unsupervised machine learning applied to the study of phase transitions is an ongoing and interesting research direction. The active contour model, also called the snake model, was initially proposed for target contour extraction in two-dimensional i
Externí odkaz:
http://arxiv.org/abs/2205.09699
Publikováno v:
Physical Review E, 2022, 105(2): 024144
Machine learning for phase transition has received intensive research interest in recent years. However, its application in percolation still remains challenging. We propose an auxiliary Ising mapping method for machine learning study of the standard
Externí odkaz:
http://arxiv.org/abs/2110.06776
Publikováno v:
Phys. Rev. E 104, 044132 (2021)
A cluster weight Ising model is proposed by introducing an additional cluster weight in the partition function of the traditional Ising model. It is equivalent to the O($n$) loop model or $n$-component face cubic loop model on the two-dimensional lat
Externí odkaz:
http://arxiv.org/abs/2107.10464
Publikováno v:
Phys. Rev. Research 3, 013074 (2021)
Machine learning methods have been recently applied to learning phases of matter and transitions between them. Of particular interest is the topological phase transition, such as in the XY model, which can be difficult for unsupervised learning such
Externí odkaz:
http://arxiv.org/abs/2010.06136