activity
20192021
most citedVisualizing Quantum Phases And Identifying Quantum Phase Transitions By Nonlinear Dimensionality Reduction

23 citations · 40 across the 3 of their papers we have counts for

collaborators

6 papers

quant-ph2021

Quantum Heaviside Eigen Solver

Zheng-Zhi Sun, Gang Su

Solving Hamiltonian matrix is a central task in quantum many-body physics and quantum chemistry. Here we propose a novel quantum algorithm named as a quantum Heaviside eigen solver…

cond-mat.str-el2020★ 23 cited

Visualizing Quantum Phases And Identifying Quantum Phase Transitions By Nonlinear Dimensionality Reduction

Yuan Yang, Zheng-Zhi Sun, Shi-Ju Ran +1

Identifying quantum phases and phase transitions is key to understand complex phenomena in statistical physics. In this work, we propose an unconventional strategy to access quantu…

cs.LG2020★ 17 cited

Tangent-Space Gradient Optimization of Tensor Network for Machine Learning

Zheng-zhi Sun, Shi-ju Ran, Gang Su

The gradient-based optimization method for deep machine learning models suffers from gradient vanishing and exploding problems, particularly when the computational graph becomes de…

stat.ML2019

Quantum Compressed Sensing with Unsupervised Tensor-Network Machine Learning

Shi-Ju Ran, Zheng-Zhi Sun, Shao-Ming Fei +2

We propose tensor-network compressed sensing (TNCS) by combining the ideas of compressed sensing, tensor network (TN), and machine learning, which permits novel and efficient quant…

cond-mat.str-el2019

Reentrance of Topological Phase in Spin-1 Frustrated Heisenberg Chain

Yuan Yang, Shi-Ju Ran, Xi Chen +4

For the Haldane phase, the magnetic field usually tends to break the symmetry and drives the system into a topologically trivial phase. Here, we report a novel reentrance of the Ha…

cs.LG2019

Generative Tensor Network Classification Model for Supervised Machine Learning

Zheng-Zhi Sun, Cheng Peng, Ding Liu +2

Tensor network (TN) has recently triggered extensive interests in developing machine-learning models in quantum many-body Hilbert space. Here we purpose a generative TN classificat…