Message Passing Variational Autoregressive Network for Solving Intractable Ising Models

arXiv:2404.06225v1 Announce Type: cross
Abstract: Many deep neural networks have been used to solve Ising models, including autoregressive neural networks, convolutional neural networks, recurrent neural networks, and graph neural networks. Learning a probability distribution of energy configuration or finding the ground states of a disordered, fully connected Ising model is essential for statistical mechanics and NP-hard problems. Despite tremendous efforts, a neural network architecture with the ability to high-accurately solve these fully connected and extremely intractable problems on larger systems …

abstract arxiv cond-mat.dis-nn cond-mat.stat-mech convolutional neural networks cs.lg distribution energy graph graph neural networks network networks neural networks probability recurrent neural networks solve type