5 papers
Generative Deep Learning for the Two-Dimensional Quantum Rotor Model
Yanyang Wang, Feng Gao, Kui Tuo +1
The advancement of diverse generative deep learning models and their variants has furnished substantial insights for investigating quantum many-body problems. In this work, we desi…
Critical dynamics of the directed percolation with Lévy-driven temporally quenched disorder
Yanyang Wang, Yuxiang Yang, Wei Li
Quenched disorder in absorbing phase transitions can disrupt the structure and symmetry of reaction-diffusion processes, offering a more accurate mapping to real physical systems.…
Supervised and unsupervised learning with numerical computation for the Wolfram cellular automata
Kui Tuo, Shengfeng Deng, Yuxiang Yang +4
The local rules of Wolfram cellular automata with one-dimensional three-cell neighborhoods are represented by eight-bit binary that encode deterministic update rules. These automat…
Autoencoder-assisted study of directed percolation with spatial long-range interactions
Yanyang Wang, Yuxiang Yang, Wei Li
Spatial L{é}vy-like flights are introduced as a way in the absorbing phase transitions to produce non-local interactions. We utilize the autoencoder, an unsupervised learning meth…
Machine learning of (1+1)-dimensional directed percolation based on raw and shuffled configurations
Shen Jianmin, Wang Shanshan, Li Wei +6
Machine learning (ML) can process large sets of data generated from complex systems, which is ideal for classification tasks as often appeared in critical phenomena. Meanwhile ML t…