176 citations · 1.4k across the 70 of their papers we have counts for
7 papers · 1 filter
Tensor networks for interpretable and efficient quantum-inspired machine learning
Shi-Ju Ran, Gang Su
It is a critical challenge to simultaneously gain high interpretability and efficiency with the current schemes of deep machine learning (ML). Tensor network (TN), which is a well-…
Eigenstate Thermalization and its breakdown in Quantum Spin Chains with Inhomogeneous Interactions
Ding-Zu Wang, Hao Zhu, Jian Cui +5
The eigenstate thermalization hypothesis (ETH) is a successful theory that establishes the criteria for ergodicity and thermalization in isolated quantum many-body systems. In this…
Efficient Quantum Mixed-State Tomography with Unsupervised Tensor Network Machine Learning
Wen-jun Li, Kai Xu, Heng Fan +2
Quantum state tomography (QST) is plagued by the ``curse of dimensionality'' due to the exponentially-scaled complexity in measurement and data post-processing. Efficient QST schem…
Persistent Ballistic Entanglement Spreading with Optimal Control in Quantum Spin Chains
Ying Lu, Pei Shi, Xiao-Han Wang +2
Entanglement propagation provides a key routine to understand quantum many-body dynamics in and out of equilibrium. The entanglement entropy (EE) usually approaches to a sub-satura…
Nature of the 1/9-magnetization plateau in the spin-1/2 kagome Heisenberg antiferromagnet
Da-zhi Fang, Ning Xi, Shi-Ju Ran +1
The nature of the 1/9-magnetization plateau of the spin-1/2 kagome Heisenberg antiferromagnet remains controversial due to the exotic physical properties and high complexity induce…
Compressing Neural Networks Using Tensor Networks with Exponentially Fewer Variational Parameters
Yong Qing, Ke Li, Peng-Fei Zhou +1
Neural network (NN) designed for challenging machine learning tasks is in general a highly nonlinear mapping that contains massive variational parameters. High complexity of NN, if…