244 citations · 455 across the 16 of their papers we have counts for
6 papers · 1 filter
Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines
Song Cheng, Jing Chen, Lei Wang
We compare and contrast the statistical physics and quantum physics inspired approaches for unsupervised generative modeling of classical data. The two approaches represent probabi…
Asymptotic correlation functions and FFLO signature for the one-dimensional attractive Hubbard model
Song Cheng, Yu-Zhu Jiang, Yi-Cong Yu +2
We study the long-distance asymptotic behavior of various correlation functions for the one-dimensional (1D) attractive Hubbard model in a partially polarized phase through the Bet…
Universal thermodynamics of the one-dimensional attractive Hubbard model
Song Cheng, Yi-Song Yu, Murray T Batchelor +1
The one-dimensional (1D) Hubbard model, describing electrons on a lattice with an on-site repulsive interaction, provides a paradigm for the physics of quantum many-body phenomena.…
FFLO correlation and free fluids in the one-dimensional attractive Hubbard model
Song Cheng, Yi-Cong Yu, Murray T Batchelor +1
In this Rapid Communication we show that low energy macroscopic properties of the one-dimensional (1D) attractive Hubbard model exhibit two fluids of bound pairs and of unpaired fe…
Phase transition of the q-state clock model: duality and tensor renormalization
Jing Chen, Hai-Jun Liao, Hai-Dong Xie +6
We investigate the critical behavior and the duality property of the ferromagnetic -state clock model on the square lattice based on the tensor-network formalism. From the entan…
Equivalence of restricted Boltzmann machines and tensor network states
Jing Chen, Song Cheng, Haidong Xie +2
The restricted Boltzmann machine (RBM) is one of the fundamental building blocks of deep learning. RBM finds wide applications in dimensional reduction, feature extraction, and rec…